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Digital fluency and critically conscious computing: a curriculum for undergraduates

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Digital fluency and critically conscious computing: a curriculum for undergraduates

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Content Digital Fluency and Critically Conscious Computing:
A Curriculum for Undergraduates
by
Kendra Walther
Rossier School of Education
University of Southern California
A dissertation submitted to the faculty
in partial fulfillment of the requirements for the degree of
Doctor of Education
August 2024

© Copyright by Kendra Walther 2024
All Rights Reserved

The Committee for Kendra Walther certifies the approval of this Dissertation
Bhaskar Krishnamachari
Helena Seli
Kenneth Yates, Committee Chair
Rossier School of Education
University of Southern California
2024

iv
Abstract
With the rapid pace of technological progress, all undergraduate students need to be digitally
fluent and critical consumers of data and technology. New technology and AI innovations are
entering our lives at an alarmingly fast pace. Institutes of higher education need to adapt and
evolve by providing coursework addressing digital fluency for students. This curriculum centers
five core competencies integral to digital fluency, while weaving in the concept of critically
conscious computing and helping students to become lifelong learners in an increasingly
technological world. Informed by research on learning and motivation and leveraging the
European Union’s DigComp 2.2 framework as well as Ko’s (2024) research on critically
conscious computing, this 15-week course uses a spiral-curriculum approach to provide at least
two mastery opportunities for each competency. By the end of this course, students will
demonstrate competence in information and data literacy, enhance communication and
collaboration skills, demonstrate digital content creation, practice safety and cybersecurity skills,
and develop problem solving skills. While developing these competencies, learners will practice
critically conscious computing by considering social and ethical impacts of computing and
technology to help build a more just and equitable future. Curriculum implementation details and
an evaluation plan which measures student achievement of goals and outcomes is included. This
curriculum can serve not only to provide knowledge to students, but as a catalyst and model for
incorporating digital fluency competencies in curriculum efforts across disciplines.
Keywords: digital fluency, technology, curriculum, critically conscious computing, information
and data literacy, communication and collaboration, digital content creation, safety and
cybersecurity, problem solving skills

v
Acknowledgements
To my spouse, Andy, thank you for your love, support, and encouragement throughout
this doctoral journey; I couldn’t have done any of this without you. To my children, Bryce and
Eri, I apologize for all the things I missed out on when I was working (on this doctoral degree or
at work), thank you for not only understanding, but for cheering me on (and cheering me up)
throughout the process! To my parents, Kurt and Pam, thank you for not only giving me the love
of learning, but for truly setting the example of being lifelong learners. Dad, I miss you every
day and I’m sorry you aren’t around to celebrate this accomplishment. Mom, you are an
inspiration to me - today and every day, and I’m so thankful for your ongoing role in my life.
To the rest of my family, friends, classmates, and colleagues, thank you for challenging
and encouraging me. To Dr. Kenneth Yates, my dissertation chair, thank you for your feedback
and encouragement throughout this process. To my committee members, thank you for your time
and guidance. To all my students, past, present, and future, let’s keep encouraging ourselves and
others to be lifelong learners.

vi
Table of Contents
Abstract.......................................................................................................................................... iv
Acknowledgements......................................................................................................................... v
List of Tables .................................................................................................................................. x
List of Figures................................................................................................................................ xi
Overview of the Project and Needs Assessment............................................................................. 1
Problem of Practice..................................................................................................................... 2
Evidence for the Problem of Practice ......................................................................................... 3
Importance of Solving the Problem............................................................................................ 4
Instructional Needs Assessment ..................................................................................................... 5
The Learning Environment............................................................................................................. 8
Potential Issues with Power, Equity, and Inclusion.................................................................... 9
About the Author ...................................................................................................................... 11
Cognitive Task Analysis and Literature Review .......................................................................... 12
Literature Review ..................................................................................................................... 13
Prior Attempts........................................................................................................................... 13
The Content of the Curriculum................................................................................................. 16
Demonstrate Competency in Information and Data Literacy ............................................... 18
Tools to Enhance Communication and Collaboration Skills................................................ 20
Demonstrate competency with Digital Content Creation ..................................................... 21
Practice Safety and Cybersecurity ........................................................................................ 23
Constructing Knowledge and Using Problem Solving Skills............................................... 24
Summary of the Curriculum Content........................................................................................ 25
The Learning Environment and the Learners ............................................................................... 32

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Description of the Learning Environment ................................................................................ 32
Teacher/Trainers/Facilitator Characteristics......................................................................... 33
Existing Curricula/Programs................................................................................................. 34
Available Equipment and Technology.................................................................................. 34
Classroom Facilities and Learning Climate .......................................................................... 35
Description of the Learners....................................................................................................... 35
Cognitive Characteristics...................................................................................................... 36
Prior Knowledge ................................................................................................................... 36
Physiological Characteristics................................................................................................ 37
Motivation Characteristics.................................................................................................... 37
Social Characteristics............................................................................................................ 38
Implications of the Learning Environment and Learner Characteristics for Design................ 39
The Curriculum............................................................................................................................. 40
List of Units, Terminal, and Enabling Objectives.................................................................... 41
Demonstrate competency in information and data literacy .................................................. 41
Enhance communication and collaboration skills................................................................. 43
Demonstrate competency with digital content creation........................................................ 45
Practice safety and cybersecurity.......................................................................................... 48
Constructing knowledge and using problem solving skills .................................................. 50
Overview of the Units............................................................................................................... 52
Delivery Media Selection ............................................................................................................. 58
General Instructional Platform Selection in Terms of Affordances and Restrictions .............. 58
Access................................................................................................................................... 59

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Consistency ........................................................................................................................... 60
Cost ....................................................................................................................................... 61
Conceptual Authenticity ....................................................................................................... 62
Immediate Feedback ............................................................................................................. 63
Special Sensory Requirements.............................................................................................. 64
Client Preferences or Specific Conditions of the Learning Environment............................. 64
Specific Media Choices............................................................................................................ 66
General Instructional Methods Approach................................................................................. 68
Implementation and Evaluation Plan............................................................................................ 70
Implementation Plan................................................................................................................. 71
Evaluation Plan......................................................................................................................... 72
Evaluation Framework.......................................................................................................... 72
Level 4: Results and Leading Indicators............................................................................... 73
Level 3: Behavior.................................................................................................................. 75
Level 2: Learning.................................................................................................................. 80
Level 1: Reaction .................................................................................................................. 82
Evaluation Tools................................................................................................................... 83
Data Analysis and Reporting .................................................................................................... 85
Conclusion .................................................................................................................................... 87
References..................................................................................................................................... 88
Appendix A: Course Overview..................................................................................................... 99
Appendix B: Lesson Overviews................................................................................................. 104
Appendix C: Lesson Activities, Design, and Materials............................................................. 141

ix
Appendix D: Evaluation Administered Immediately Following the Program ........................... 232
Appendix E: Evaluation Administered Two Semesters After the Course.................................. 235

x
List of Tables
Table 1: Major Steps and Knowledge Types........................................................................... 26
Table 2: Media Choices in Digital Fluency Course................................................................. 66
Table 3: Indicators, Metrics, and Methods for External and Internal Outcomes.................... 74
Table 4: Critical Behaviors, Metrics, Methods, and Timing for Evaluation .......................... 76
Table 5: Required Drivers to Support Critical Behaviors....................................................... 78
Table 6: Evaluation of the Components of Learning for the Program ................................... 82
Table 7: Components to Measure Reactions to the Program.................................................. 83
Table A1: Learning Activities for the Course Overview........................................................ 101
Table C1: Learning Activities for Unit Six:
Introduction to Data Literacy................................................................................. 146
Table C2: Learning Activities for Unit Seven:
Building Problem Solving with Data Literacy....................................................... 195

xi
List of Figures
Figure 1: Digital Fluency Course Units in Spiral Curriculum................................................. 53
Figure 2: Scope and Sequence of the Curriculum, Part One ................................................... 56
Figure 3: Scope and Sequence of the Curriculum, Part Two................................................... 57
Figure 4: Sample Data Representation of Retrospective Pre-Post Test Results...................... 86
Figure 5: Sample Data Representation of Indicators for External and Internal Outcomes ..... 86
Figure A1: Visual Overview of Course Units in Spiral Curriculum ........................................ 100

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Overview of the Project and Needs Assessment
“Once upon a time, there was a student named Emily who had just started her first
semester of college. She was excited to start her classes and learn new things, but she was also a
little intimidated by the idea of studying technology. She had always been more interested in the
humanities and had never taken a computer science class before. However, as she began her
classes, Emily quickly realized that technology was becoming an integral part of every aspect of
her life. She noticed that her professors were using technology in their lectures, and many of her
assignments required her to use digital tools and resources. She also noticed that many of her
classmates were discussing the latest technology trends and innovations.
Despite her initial reservations, Emily decided to take a course on technology. She was
surprised to find that the class was not just about coding and computer science, but also covered
topics such as digital literacy, data privacy, and the social impact of technology. The class helped
her understand how technology was shaping the world around her and gave her the skills and
knowledge she needed to be a responsible and informed technology consumer. One of the
assignments in the class required her to work with her classmates on a project that used
technology to address a real-world problem. They chose to develop a mobile application that
helped people with disabilities navigate their city more easily. Emily was amazed by the impact
that the application had on people's lives and how she had been able to contribute to it. By the
end of the semester, Emily realized that technology was not something to be feared or avoided,
but an essential part of our world that needed to be understood and embraced. She was grateful
for the opportunity to learn about technology in a way that was relevant, engaging, and
meaningful to her. She felt confident that the knowledge and skills she had gained in the

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technology course would be valuable to her throughout her college and future career.” (OpenAI,
2023)
The above story was written by ChatGPT (Open AI, 2023) in response to the prompt: tell
a story about why a future college student needs a course about technology. As artificial
intelligence becomes more powerful and more prevalent, students need to understand the
possibilities and limitations of the technology that is the fabric of our modern society. As such,
this curriculum introduces a new undergraduate overview-level general education course for
digital fluency and critically conscious computing.
Problem of Practice
The Modern Applied Tech and Computing Hub (MATCH, a pseudonym) is a unit at
ZYX University (a pseudonym) which aims to provide high-quality technology courses for ZYX
students, not just those studying computer science and engineering. With the rapid pace of
technological progress, and the ground-breaking advances in the field of artificial intelligence,
all undergraduate students will soon need to be digitally fluent and know how to be critical
consumers of data and technology. As ZYX University is beginning a new campaign to focus on
computing and artificial intelligence across the campus, the development of new, high-quality
general education courses to address technology and computing for humanity will be essential to
prepare students for becoming 21st
-century critical thinkers. This course will introduce students
to the breadth of knowledge underlying technology and computing and provide an overview of
the core guiding principles for digital fluency. Students will need to know not only how to
leverage existing technologies for problem solving, but also how to make technology work for
them by creating integrations and providing interoperability between tools. Students will need to
think critically to detect if digital products are authentic, valid, truthful, and reliable. Students

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will need to understand basic programming concepts to apply computational thinking, data
science and analytics to make more informed decisions, cybersecurity principles to protect
themselves and their data, and be able to incorporate ethical considerations to not just AI and
technology, but to the social and environmental impact of these technologies as well.
Evidence for the Problem of Practice
This problem of practice is a moving target, with new technology and AI innovations
entering our lives at an alarmingly fast pace. With the Fall 2022 public release of Open AI’s
ChatGPT system, it seems that every day there are news articles about the changing nature of the
world (education, business, creative endeavors, etc.) due to technological advancements and
predictions of the future due to AI. While current cohorts of undergraduates may be considered
digital natives, as explained by (Tunbridge & Barlow, 1995, p. 2), "I would say that, generally
speaking, at this stage, if you're over 25, you're an immigrant. If you're under 25 you're closer to
being a native, in terms of understanding what it is having a real basic sense of it." It has been
observed that despite current individuals growing up in the digital age as natives, many are still
missing fundamentals of digital literacy, how technology works, and basic digital competencies
(Alexander et al., 2017; Anthonysamy et al., 2020; Davi̇d, 2022; Fleming et al., 2021; Santos &
Serpa, 2017; Spante et al., 2018). Given the rapid changes in the field of technology, and the
advent of sophisticated AI systems, it is critical that institutes of higher education adapt and
evolve by providing general education coursework that will address what digital fluency means
for students today and in the future and how and why all students will need to practice critically
conscious computing (Ko et al., 2023) while being critical consumers of data and technology.

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Importance of Solving the Problem
Technology has permeated all sectors of the post-college job market; now more than
ever, it is critical that college graduates are not only digitally literate, but also digitally fluent. As
Anthonysamy (2020, p. 2393) explained, “self-regulated learning strategies (SRLS) can foster
the enhancement of digital literacy in digital learning to increase efficiencies in human capital
for sustainable development in lifelong learning.” With the rapid pace of technological advances,
all citizens need to be taught the skills to be lifelong learners, especially within the realm of
digital technologies, to adapt to the ever-changing nature of the world.
Over the past 50 years, research from ZYX University has shaped the underlying
computing infrastructure critical to the development of our modern technological world in ways
that were previously unimaginable. As future researchers continue to explore, innovate, and
shape the next technological advances in areas such as computational systems and technology,
emerging tech, networking, cybersecurity and artificial intelligence, all ZYX undergraduate
students need to be poised with the knowledge and problem-solving capabilities to leverage
these technological advances across all aspects of their learning. ZYZ undergraduates expect to
become leaders within their chosen field, and as we look to the future job market, computational
thinking and digital fluency are key competencies, no matter what major these undergraduate
students pursue. As such, building student digital competencies needs to be addressed as part of
the first-year general education curriculum, and then integrated across the curriculum to ensure
that we graduate students who are digitally fluent and able to understand and apply new
technological advances to their individual fields of study. If ZYX University does not address
this critical educational need, it is possible that many of their graduates will be inadequately
prepared for future career endeavors. As a well-known source of cutting-edge research and

5
innovation in computation and technology, this curriculum will allow ZYX University to
become known for providing relevant and innovative undergraduate education that can serve as a
model for others to follow. This will increase student satisfaction, help with retention and
graduation rates, and help be part of the university’s overall branding strategy.
Instructional Needs Assessment
Smith and Ragan (2005) proposed that instructional designers conduct a needs
assessment to determine whether instruction should be designed. In their framework, there are
three conditions to consider regarding the need to develop curriculum: the problem model, the
innovation model, and the discrepancy model. The needs assessment may be conducted in an
informal or formal process and helps determine the type of model that should be applied. In the
problem model, constituents are not satisfied because learning outcomes are not being reached;
thus, the designer needs to understand what is causing the lack of performance to better
understand how to address the instructional needs. In the discrepancy model, instruction is
already occurring, but the focus is on evaluating if the curriculum is addressing the learning
goals for all constituents. Finally, the innovation model is needed when there is something new
that needs to be learned and the designer must understand and analyze what learning goals are
needed.
The digital fluency curriculum described in this dissertation will apply the innovation
model outlined by Smith and Ragan (2005). The first step in the innovation model process is to
determine the nature of the innovation or change. Undergraduate students are entering college
with varying degrees of background knowledge in applying and using digital technology, and
while many may appear to be competent users of digital applications, they do not necessarily
understand appropriate and efficient ways of learning about new technological advances and

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applying that knowledge to problem solving across multiple disciplines. The technology tools
themselves are constantly evolving and changing, with new features constantly rolling out in
updated software versions of existing tools, and new tools being developed at an alarmingly fast
rate. Additionally, huge paradigm shifts, like the explosion of large language model artificial
intelligence tools have emerged for wide-spread consumer use over the past year. Workplaces
and educational environments in general have not yet caught up with these advances, which
means that overall knowledge, policies, education, and training surrounding digital fluency is
lacking, and will likely continue to lag until a more steady-state situation arises.
The second step of the Smith and Ragan (2005) innovation model for needs assessment is
determining the learning goals for the innovation. In applying this step, the designer needs to
anticipate how the achievement and performance of learners will be affected by the innovation,
and more specifically, identify what learners need to know, understand, or be able to do because
of the innovation, and determine if this material can be taught through instruction. Given the
rapid development and nature of constant change in technological advances, in the case of digital
fluency, the exact nature of the innovation is not (and perhaps cannot be) entirely known. This
means that the design of a digital fluency curriculum will need to apply principles from emergent
strategy (Brown, 2017) in order to prioritize the idea of expecting change as the fundamental
component of lifelong learning. The needs assessment, learning goals, and curriculum for digital
fluency will need to be approached through the lens of emergent strategy: dynamic complexity,
evolving concepts, and the expectation of constant change.
The third step of the Smith and Ragan (2005) innovation model involves determining
whether the learning goals are appropriate and high priority in the learning system. This entails
working with the stakeholders (students, faculty, staff, and administrators) to define an

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overarching goal of achieving digital fluency, with the understanding that the process of
developing concrete learning goals will be ongoing and constantly and consistently changing.
Ultimately, this third step is critical for the needs assessment for this digital fluency curriculum
because this is where we ask, “Are the resources available to support this new instruction? Are
they adequate to design and develop this instruction?” (Smith & Ragan, 2005, p. 46), and in the
case of this specific curriculum, it will ultimately only be successful in the long term if the
stakeholders all realize that generous resources will need to be allocated to apply an emergent
design to the development of the learning goals and curriculum. Finally, if after reflection, it has
been determined that the learning goals are both important and feasible, then the Smith and
Ragan (2005) innovation model says that the designer should begin learning environment
analysis design activities.
Faculty within the MATCH unit have been providing technology education to nonengineering students for the past 40 years and have experienced exponential growth in the
number of students pursuing technology courses and minors. As more undergraduate students
from a variety of backgrounds express a desire or need to learn various computational skills,
MATCH faculty have found that many are lacking in digital literacy and competencies that are
fundamental to be able to understand and apply computational thinking for problem solving. As
more jobs demand applicants with computational skills and advanced technological
understanding, it is unreasonable to expect that undergraduate students pick up these skills
independently. ZYX University leaders have deemed that digital fluency is an important
consideration for the future education of all undergraduate students. Thus, this curriculum is
intended to teach undergraduate students at ZYX University how to develop digital fluency and
become critical thinkers and critically conscious consumers of computing, information, data, and

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technology, with a focus on information and data literacy, exploring technology applications,
including communication and collaboration tools for problem-solving, emerging trends in
privacy and cybersecurity, creating digital content, and following advances in artificial
intelligence.
The Learning Environment
Smith and Ragan define the learning environment as the “system in which the instruction
will be implemented” (2005, p. 49) and includes the learners, all instructional materials, the
teacher, instructional equipment, facilities, and the overarching community or organization (p.
49). This curriculum is designed as an undergraduate course, to meet general education
requirements for students with varying technological backgrounds. At ZYX University,
classroom spaces are assigned at a central level, so the instructor may not have control over the
facilities or instructional equipment, beyond that which can be brought in, or is standard in all
instructional spaces.
As a college-level course for credit, this curriculum will be part of a formal learning
environment in which students will complete assessments and receive a grade. However, as
discussed in Malcolm et al, “all (or almost all) learning situations contain attributes of
formality/informality, but the nature of, and balance between them varies significantly from
situation to situation” (2003, p. 317). This highlights the importance of approaching curriculum
design for digital fluency in a way that embraces formal, informal, and nonformal attributes in
the process, location and setting, purpose, and content of the learning environment (Malcolm et
al., 2003).
By the dictionary meaning, traditional education tends to be synchronous, with
expectations and deadlines delineated for students (Worthington, 2013, p. 1). In exploring

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educational settings more systematically, there are combinations of synchronous/asynchronous
interactions between participants (learners and teachers) as well as with the course materials that
must be considered to understand the full learning environment (Soo & Bonk, 1998;
Worthington, 2013). The curriculum will be designed to be delivered in a blended mode; with a
combination of synchronous or “real-time” and asynchronous “store and forward” learning
(Worthington, 2013). To be as inclusive as possible, it is anticipated that students will be allowed
to participate in real-time interactions either in the classroom environment or through a videoconferencing environment. Furthermore, with a digital learning platform explicitly designed for
improving learning in programming (Ed, n.d.), this curriculum may overcome the fragmented
approaches that occur due to traditional learning management systems (LMS) lacking support for
real-time learning (Worthington, 2013, p. 2).
Potential Issues with Power, Equity, and Inclusion
Ladson-Billings (2006) introduced the concept of the Education Debt and implores
leaders to address the inequities that have been persistent in our educational systems. By learning
about historical oppressions and examining the role of deculturalization (Spring, 2016), settler
colonialism (V. Andreotti, Stein, et al., 2015; Tuck et al., 2014), systemic racism, anti-blackness,
White privilege (V. Andreotti, 2016; Love, 2019), and the normalization of the social construct
of Whiteness (Picower, 2009; Utt & Tochluk, 2020) that were the foundation of our educational
systems, educators and administrators can begin to understand the role historical events played in
current educational inequities (Anderson, 1988; Tuck & Gaztambide-Fernández, 2013; Tuck &
Gorlewski, 2016) and how individuals need to examine their positionality (Douglas & Nganga,
2013; Fraise & Brooks, 2015) in order to disrupt systems to begin transformation. People must
think in big institutional terms to end systemic oppression, so educators must focus on building

10
coalitions, coalescing, creating change, and maintaining and integrating changes into everyday
life (Harro, B. in Adams, et al, 2013).
To transform the status quo in relation to education inequities in the Higher Education
context, Marshall et al. (2011) discuss the need to: “establish a direction or a vision,
communicating that vision and aligning stakeholders, strategy and resources with that vision, and
enabling, motivating, and inspiring … key stakeholders to participate in and contribute to the
realization of that vision” (pp. 91-92). Systems level thinking (Senge, 1990) is necessary to build
a learning organization, and a genuine focus on learning could help reduce educational
inequities. Systems can be used to encourage adaptive and generative learning in higher
education, encourage employees to think outside the box and work in conjunction with other
employees, or they can create a physical environment where collaboration easily can happen
(Bolman & Deal, 2017).
Within the fields of technology and computer science, knowledge has historically been
viewed as theoretical and technical skills devoid of human and ethical elements. There has been
a shift occurring in the last decade, and the inclusion and positionality of individuals other than
white males influencing education and corporate culture has led to the beginning of more
culturally relevant computer science knowledge (Ko et al., 2023). Opportunities to provide
holistic student learning and development through culturally relevant pedagogy – by focusing on
critical self-reflection, learning, deconstruction, reconstruction, and leadership (Fraise & Brooks,
2015) in a digital fluency curriculum can lead educators to reimagine systems and structures in
classrooms to offer meaningful learning collaborations while maintaining high expectations and
accountability (Childress et al., 2006).

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About the Author
Villaverde (2008) defines positionality as “how one is situated through the intersection of
power and the politics of gender, race, class, sexuality, ethnicity, culture, language, and other
social factors” (p. 14). As a female in post-secondary schools where the student population was
75% male (or more in graduate school), gender played a critical role in my identity. While my
socioeconomic and cultural background often differed from my peers, being a female in
computer science meant that gender was, and continues to be, the area in which I understand
(and fight against being marginalized by) the impact of institutional power structures. Through
reflection, I am integrating and deepening my knowledge and understanding of how race and
colonialism deeply affect positionality and power, and I recognize that the privileges I hold in
areas such as race, ethnicity, or sexual orientation give me certain advantages over others.
However, those advantages often seem secondary as it was not until the 1990s that gender
disparities in technology/engineering became an issue that was pursued as a topic of study (Bix,
2013), and I actively struggle against ingrained gender-based power injustices in my daily life as
a female in computer science.
Two theories in particular have influenced my positionality, critical race theory (CRT)
and emergent strategy. Based upon the work of Ladson-Billings and Tate (2006), CRT posits
that racism is “deeply ingrained in American life" (p. 18), therefore racism is rooted in the
educational system. Recent work by Ko et al., explicitly asks computer science educators to
think critically about the content knowledge and foundations of computer science through a CRT
lens, thinking specifically about “diversity, equity, inclusion, justice, oppression, and power”
(2023, p. Introduction). To keep pushing myself away from White privilege and traditional ways
of knowing, I want to continue centering and leaning into brown’s (2017) tenets of emergent

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strategy, allowing my work to be iterative, fractal, adaptive, reflective, interdependent, and to
evolve as I “step outside of the comfort of the current and lean into the unknown, together” (p.
113) because it will be through working with undergraduate students and continuously
undergoing a process of lifelong, iterative, learning that this digital fluency curriculum will itself
evolve.
Cognitive Task Analysis and Literature Review
Developing the content for the curriculum starts with a cognitive task analysis (CTA)
which identifies the major steps for becoming digitally fluent. CTA is the process of using
literature, interviews, and observations to discern the knowledge (both implicit and explicit) that
experts use to perform tasks (Clark et al., 2008). The CTA process used to design this curriculum
has two main components: the literature review and an interview with a subject matter expert
(SME). The literature review was conducted using an iterative, ‘bootstrapping’ process (Potter et
al., 2000). Using a rapid research protocol and recognizing that CTA is more of a “craft than
technology” (Yates & Feldon, 2011), multiple phrases were used to try to capture and refine the
steps of how to become digitally fluent. By first attempting to locate results in Google and
ChatGPT (OpenAI, 2023), useful and germane search terms and sub-components of digital
fluency were identified. This process led to the discovery of several frameworks for digital
literacy, digital competence, digital fluency, and computational thinking, which are leveraged in
this curriculum. The second part of the CTA process involved conducting an interview with a
SME. The SME interview helps provide more detailed knowledge as part of the information
processing analysis (Smith & Ragan, 2005). The CTA and SME interview confirmed that the
major competencies for digital fluency are:
● Demonstrate competency in information and data literacy

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● Enhance communication and collaboration skills
● Demonstrate competency with digital content creation
● Practice safety and cybersecurity
● Constructing knowledge and using problem solving skills
The most relevant search phrases, as well as the competencies listed in various
frameworks, were then used in Google Scholar and other digital library databases in order to find
academic literature supporting each of the major tasks/competencies for digital fluency. These
major competencies, as well as the concept of “critically conscious computing” (Ko et al., 2023)
will be used to create learning goals, course outcome analysis, and terminal objectives.
Literature Review
This literature review is divided into three parts. First, prior attempts of curriculum
efforts for digital fluency will be discussed. Next, the major steps for developing digital fluency
in undergraduate students will be explored. Finally, learning outcomes will be classified
according to Gagné’s categories of learning outcomes.
Prior Attempts
While many universities have offered information technology courses over the past
several decades that address how to use word processors, spreadsheets, and other software tools,
these prior attempts focused primarily on skill-building and the use of technology as a tool
(Margaryan et al., 2011). Other universities have offered courses highlighting information
literacy and teaching students to be “Net Savvy” (Miller & Bartlett, 2012). While the aspirational
aims of these courses may have been to inspire independent and critical thinking, as Resnick
(2002) points out, the actual curricula content was often focused more on information and
declarative knowledge instead of “how to become better thinkers and learners” (Resnick, 2002,

14
p. 1). In The Children’s Machine, (Papert, 1993) discusses his philosophy of constructionism,
and how technological advances can help transform the educational process. More than 30 years
later, our current curriculum still falls short of providing learners with the “ability to express,
explore, and realize ideas with new technological media” (Papert & Resnick, 1995, p. abstract).
The College Board’s AP Computer Science Principles (APCSP) course is a somewhat
related curriculum effort that focuses on introducing students to the breadth of the field of
computer science (College Board, 2023). The APCSP curriculum has a more direct computerscience focus than this digital fluency curriculum, as it is designed to specifically help students
design, develop, and implement programs and algorithms through the practice of computational
thinking skills. These concepts are critical for programming and computer science and while
there is overlap with many aspects of digital fluency, the curriculum presented in this
dissertation is geared to a more diverse and general population than that of an introductory
computer science course. For example, in the APCSP curriculum, data is presented at the bit
(binary digit) level, and students focus on the mathematical limitations of that representation as
well as exploring compression algorithms for storing data, which are important concepts for
computer science but are not especially relevant for digital fluency.
With the rapid pace of technological advancement and major disruptors to education with
AI advances in large language models (like ChatGPT), it is more critical than ever before that all
university students become digitally fluent, but there is not necessarily agreement on what
“digital fluency” really means as a core competency. In a strategic brief about digital literacy in
higher education, the New Media Consortium (NMC) discusses three models, or levels, of digital
literacy, including universal, creative, and across disciplines; and highlights the need for all
individuals to acclimate to emerging technologies and cultivate lifelong learning and mastery of

15
new skills (Alexander et al., 2017). While many of the frameworks reviewed in the NMC report
(American Library Association, 2015; Massachusetts Department of Elementary and Secondary
Education, 2016) discuss core concepts and competencies for digital literacy or fluency, these
alone are not enough to develop a curriculum. The American Library Association highlights this
distinction quite deliberately:
The Framework offered here is called a framework intentionally because it is based on a
cluster of interconnected core concepts, with flexible options for implementation, rather than on
a set of standards or learning outcomes, or any prescriptive enumeration of skills. (American
Library Association, 2015, p. 7)
As an educator approaching this curriculum from a traditional computer science
background instead of from a library or information science perspective, this dissertation is
proposing a curriculum that embraces the concepts proposed while focusing on an
implementation that will provide students with conceptual knowledge about technology and
computing fundamentals. Students need not only to understand how to use new technologies,
they need to build the confidence to continue adapting to emerging technologies by leveraging a
basic understanding of technology, computer, and networking knowledge to leverage
technologies and construct new knowledge to solve problems across multiple domains or
disciplines. Hence, this curriculum aims to develop a dynamic approach to teaching
undergraduates digital fluency through building knowledge, skills, and attitudes toward
technology and computing so that they become lifelong thinkers, learners, creators, and
innovators in our increasingly technological world.

16
The Content of the Curriculum
This curriculum focuses not on building specific technology skills (for example,
effectively using search engines or tools like word processors or spreadsheets), but rather on
providing students with the opportunity to learn and apply the knowledge, skills, and attitudes
about technology and computing so that they will be confident in their ability to continue to learn
and explore new technological advances throughout their lifetimes. The digital landscape is
constantly changing, and even though current college students have grown up as “tech-natives”
(Kivunja, 2014; Margaryan et al., 2011; Ng, 2012; Tunbridge & Barlow, 1995), many are still
missing a fundamental understanding of how technology works. In this curriculum, students
explore various technological concepts and domains through the exploration of standard and
emerging systems, frameworks, protocols, and tools (software, algorithms, apps, APIs, and AI).
Students will explore what digital fluency means for the areas of information and data literacy,
communication and collaboration, digital content creation, privacy, safety and cybersecurity, and
problem solving. Finally, students will be expected to think critically about computing and
technology, exploring the historical, economic, and social ramifications of our digital world and
how it relates to diversity, equality, equity, inclusion, justice, oppression, and power. This
curriculum aims to help students develop a growth mindset (Dweck, 2008) toward digital
fluency so that they will become lifelong thinkers, learners, and creators in our increasingly
technological world.
The design for this curriculum is guided by leveraging frameworks for digital literacy,
digital competence, digital fluency, and computational thinking. The concepts used to develop
this curriculum were identified by leveraging tools such as ChatGPT (OpenAI, 2023) and
Google to identify search terms and topics which yield productive results and then searching

17
Google Scholar and digital library databases (such as JSTOR, ERIC, ProQuest) to find relevant
scholarly work which verified the results. This process revealed a set of core competencies that
learners need to develop to become digitally fluent. This curriculum will be developed by using
each of the five general competencies outlined in the European Union DigComp 2.2 framework
(Vuorikari et al., 2022) as a guide to help learners explore computing and new or existing
technologies. Students in the course will need to adopt a growth mindset (Dweck, 2008; Fleming
et al., 2021) toward learning about technology and computing while developing positive selfefficacy and self-regulation through practicing metacognition and reflection. Students in the
course will demonstrate digital fluency by researching and identifying technology tools to help
them achieve learning goals and developing declarative and procedural knowledge about
technology and computing concepts as they complete a set of individual and group projects.
Additionally, this curriculum will weave the concept of “critically conscious computing” (Ko et
al., 2023) throughout the course, encouraging learners to consider social and ethical impacts of
computing and technology in order to help build a more just and equitable future.
As a result of CTA, specifically the literature review and the interview with a SME, the
content of the curriculum and the literature review below is organized around these major
competencies:
● Information and data literacy
● Communication and collaboration
● Digital content creation
● Safety and cybersecurity
● Problem solving

18
Demonstrate Competency in Information and Data Literacy
At a fundamental level, before students can become digitally fluent, they need to
understand the nature of data and digital sources of information. Building upon basic digital
information literacy skills, which students hopefully covered in their K-12 education, students
should be able to use the internet to find reliable and relevant information, as well as become
adept at how to store, manage, and organize that information for future endeavors (Alexander et
al., 2017; Vuorikari et al., 2022). Beyond information literacy, data literacy involves critical
thinking in understanding that data is an abstraction of information that is imperfect and often
biased (Bhatt & MacKenzie, 2019; Forstag, n.d.; Ko et al., 2023; Miller & Bartlett, 2012;
Vuorikari et al., 2022). Additionally, data literacy for students involves a basic understanding of
the computational aspects of data science, such as statistics and data analysis (Forstag, n.d.; Ko
et al., 2023; Vuorikari et al., 2022).
A focus on digital sources of information involves students being able to “articulate
information needs, to locate and retrieve digital data, information and content” as well as
determine the “relevance of the course and its content” (Vuorikari et al., 2022, p. 7), including,
as Miller and Bartlett (2012, p. 38) state, “the ability to judge, evaluate, analyze, or interpret the
veracity, bias, and integrity of the information that one encounters.” With the explosion of AI
companies and AI integration into existing software, the challenge of being able to recognize
deep fakes and/or other sources of misinformation will continue to grow, and students will need
to continue to develop strategies and critical thinking skills to explore, examine, identify, and
find original and authentic sources of information (Miller & Bartlett, 2012; Vuorikari et al.,
2022). Being able to leverage and efficiently utilize software tools to store, manage, and
organize sources of information is also an important component of digital fluency (Alexander et

19
al., 2017; Vuorikari et al., 2022) and can contribute to undergraduate academic success.
Furthermore, students need to know how to use software to collect data, process and visualize
trends in data, and use databases and repositories to organize and find complex information
(Vuorikari et al., 2022).
Additionally, in order for students to demonstrate competency with information and data
literacy, they need to think critically about data and not be passive consumers of data and
information (Bhatt & MacKenzie, 2019; Ko et al., 2023). Students need to be introduced to
statistical computations and fundamentals of data science and develop an understanding of how
to work with data sets in a variety of computing contexts (College Board, 2023; Forstag, n.d.;
Vuorikari et al., 2022). Students should be introduced to the concept of interrogating how data
was collected and discussing explicit or implicit biases that may exist within the data (Ko et al.,
2023). Also, students need to understand what steps may need to be carried out to process data
so that it can be effectively used by software tools and think critically about how each of those
steps may additionally alter the original information the data was captured to portray (College
Board, 2023; Ko et al., 2023).
Thus, all undergraduate students need to build an understanding of the difference
between information and data, locate relevant information, and think critically about sources of
information and data. This includes incorporating literacy skills typically covered in library or
information science domains, but in the current era of “big data” (Hatt, 2019; Hotz, 2024), this
also involves abstracting information in the form of data so computers can store and manipulate
it easily. In this curriculum on digital fluency, students will apply the knowledge from this
competency in at least two different projects. In the information project, students will use
electronic library resources to locate relevant information resources for a research project and

20
then leverage a reference management system to help store and manage those resources. In the
data project, students will work in small groups to explore pre-existing data sets, abstract
information in the form of data, interrogate what kinds of systems may use that data set, discuss
the (explicit or implicit) values encoded within the data (such as predictive policing algorithms
relying on historical data that disproportionately targeted Black people), and evaluate the
implications of how systems use and manipulate data in visible and invisible ways. While
students practice developing competence in information and data literacy, the curriculum will
weave in technology tools to enhance communication and collaboration skills.
Tools to Enhance Communication and Collaboration Skills
Throughout this curriculum and their studies in higher education, undergraduates will
continually need to interact, communicate, and collaborate with others through the use of a
variety of technology tools and platforms (Reyna & Meier, 2020; Vuorikari et al., 2022). This
curriculum will build upon skills that students may have been exposed to in previous studies,
making sure that all learners are adept at researching, finding, and testing tools for asynchronous
and synchronous communication, including exploring pros and cons of various collaboration and
shared planning tools (Vuorikari et al., 2022). Learners will engage in generating a shared
understanding of the ways that computers, the internet, and artificial intelligence can shape and
affect one-to-one communication, one-to-many communication, and collaboration: both that
between one or more humans as well as collaboration between one or more humans with AI
tools (Salopek, 2000). Enhancing communication skills means that learners must be able to
understand the importance of ensuring digital accessibility, assessing the capabilities of existing
tools, and striving to follow accessibility guidelines (including WCAG 2.1) when creating all
forms of digital assets (Vuorikari et al., 2022; W3C World Wide Web Consortium, 2023). As

21
Reyna and Meier (2020) highlight, all learners need to be able to communicate using digital
assets across a variety of audiences effectively.
Being digitally fluent means that undergraduate students must be able to use technology
to effectively communicate and collaborate with others, both synchronously and asynchronously.
Learners will need to practice discovering, evaluating, and effectively adapting new tools,
standards, and guidelines to stay current with best practices for communication and collaboration
in an increasingly global marketplace. Finally, students will need to consider accessibility to
make sure that their communication and collaboration efforts reach everyone. This competency
will be revisited several times throughout the curriculum, as students work together throughout
the course on projects. Communication and collaboration will be interweaved for all group
projects, and students will be expected to work together both synchronously and asynchronously.
Various communication and collaboration tools will be leveraged to allow students the
opportunity to discover affordances offered by existing and emerging technology. Additionally,
students will create digital artifacts that are meant to communicate information with outside
entities. Thus, enhancing communication and collaboration skills will continue throughout the
curriculum, and as learners create digital content, it will be important for them to consider how
they are communicating with others through their digital artifacts.
Demonstrate competency with Digital Content Creation
Digital content creation is a critical component of digital fluency and will likely be a skill
that learners will need to continuously revisit with new and emerging technologies across a
variety of contexts. Students will need to focus on the process of acquiring new digital skills
with previous knowledge as tools and technologies continuously evolve (Vuorikari et al., 2022).
Currently, programming concepts are considered an important part of digital content creation,

22
but it is unclear how the rapidly emerging growth of generative artificial intelligence might
impact the necessity for students to learn programming skills, so this curriculum will need to
remain responsive to meet the changing and evolving needs of our learners (Ala-Mutka, 2011;
Brodnik et al., 2021; College Board, 2023; Mok & Joseph, 2021; Vuorikari et al., 2022).
Learners will demonstrate competency with digital content creation across several
different levels in this course and develop attitudes to support future exploration and learning.
Students will use multimedia principles to create images and videos while demonstrating an
understanding of accessibility and file formats (Ala-Mutka, 2011; Reyna & Meier, 2020;
Vuorikari et al., 2022; W3C World Wide Web Consortium, 2023). Students will explore the uses
and limitations of generative artificial intelligence. Students will be introduced to the nature of
programs and use block-based programming languages to execute an algorithm and explore how
information is stored, processed, and manipulated in a computer (Brodnik et al., 2021; College
Board, 2023; Vuorikari et al., 2022). Being digital fluent with digital content creation involves
lifelong learning, especially as new tools and technologies emerge. Learners need to understand
the nature of programs (Brodnik et al., 2021) and digital content and be adept at the abstraction
of information and expressing their thought processes in order to create content that
demonstrates opinions, knowledge, and innovations.
As learners create digital content, especially through the use of programming or
generative artificial intelligence, they will need to develop an understanding of the complexities
that occur through the use of these technologies, including how programs are both concrete and
abstract entities (Brodnik et al., 2021). As algorithms and programs become more embedded in
all aspects of our lives, being digitally fluent “requires grasping the relation between a program
and its interpretation … being aware of the duality of instructions and data, accepting the need

23
for and the power of extreme precision and unambiguity, and the unavoidable abstraction
involved” (Brodnik et al., 2021, p. 3). As learners create content, whether that be infographics,
presentations, programs, algorithms, or other digital artifacts, they also need to consider
accessibility, legal concerns, and safety concerns for themselves and others. Thus, it is critical
that this curriculum helps learners develop the awareness and skills necessary for practicing
personal safety in the digital world by applying cybersecurity principles.
Practice Safety and Cybersecurity
With almost all our personal and business data and information stored online, learners
need to develop awareness of cybersecurity practices to protect themselves, their academic
institutions, their future employers, and society at large. Students can approach learning in safety
and cybersecurity by applying the skills from the five main functions of the NIST framework:
identify, protect, detect, respond, and recover (2018). This curriculum will integrate specific
cybersecurity skill sets to help learners protect devices, content, personal data, and privacy
(Vuorikari et al., 2022, p. 7). Safety and cybersecurity for digital fluency units will be created by
curating and integrating content from freely available cybersecurity modules (Carlton & Levy,
2015; Estes et al., 2016; Fleming et al., 2021; Khader et al., 2021; Mountrouidou et al., 2018;
Payne & Colleagues, 2021; Vuorikari et al., 2022). Learners will demonstrate their competency
by creating a public service announcement teaching others basic privacy and cybersecurity
practices such as creating strong, unbreakable passwords, encrypting data, and identifying
phishing and other online scams exploiting individual vulnerabilities.
While there are many approaches and ideas for teaching the fundamentals of safety and
cybersecurity, the literature shows that this is an emerging and interdisciplinary field. No matter
what type of curriculum or modules are adapted, at the most basic level, learners from all

24
backgrounds and majors need to understand how to protect data and devices as new threats and
risks emerge. As such, this competency will also include the need to develop an attitude towards
continuous learning to understand and apply basic skills to new situations. As learners
demonstrate sufficient knowledge, skills, and attitudes to protect themselves, their data, and their
devices, they can focus on developing the ongoing confidence, knowledge, skills, and attitudes
to be lifelong learners who continue to explore emerging technologies while developing more
sophisticated problem-solving skills.
Constructing Knowledge and Using Problem Solving Skills
In our data and information-rich world, technology is changing how individuals learn.
Connectivism, a learning pedagogy that claims itself as a learning theory, looks at how learning
and knowledge are changing and explores how this may impact pedagogy (Goldie, 2016;
Siemens, 2004). Being able to form connections and create (or notice) patterns between sources
of information is a requirement of learning in a knowledge economy (Siemens, 2004).
Additionally, practicing and demonstrating creativity and innovation through problem solving
skills, or computational thinking, is an important component of digital fluency and lifelong
learning (Fleming et al., 2021; Goldie, 2016; Kim et al., 2013; Siemens, 2004; Sparrow, 2018;
Vuorikari et al., 2022; Wing, 2006). Sparrow discusses that digital fluency is about generating
ideas and solving problems by leveraging technology by combining multiple evolving fluencies,
including curiosity fluency, communication fluency, data fluency, and innovation fluency (2018,
p. 54). Kim et al. (2013) present a creative thinking spiral involving experimenting, creating,
imagining, reflecting, and sharing.
Whatever the context, as students find, develop, and construct knowledge, through using,
exploring, or creating digital tools, they will be engaging with problem solving skills, using

25
abstraction and computational thinking to solve novel problems in an interdisciplinary manner
(Vuorikari et al., 2022; Wing, 2006). In this curriculum, learners will explore how to
troubleshoot problems, apply step-by-step approaches, use recursion, decipher or create flow
charts, use machine translation, apply machine learning, practice abstraction and decomposition,
think about solutions by applying top-down and bottom-up approaches, and generally explore a
variety of problem-solving methodologies from various domains (Priemer et al., 2020). They
will show that they can work individually and collaboratively to resolve conceptual problems
and propose solutions to challenging situations. Technology is changing the nature of knowledge
and how we approach the world. Developing an interdisciplinary but systematic approach to
learning and problem solving will allow the learner to expand their knowledge while they
design, imagine, experiment, and create using new technologies.
Summary of the Curriculum Content
In the Smith and Ragan model, each major step toward digital competency becomes a
learning goal, that is, an observable and measurable behavior that follows instruction (2005). To
design instruction, we apply Gagné’s model of instructional design to specify the learning
outcomes for each major step/competency based on type: declarative knowledge, intellectual
skills, cognitive strategies, and attitudes (E. Gagné, 1985; R. Gagné, 1985. Declarative
knowledge is the information a learner can state or recall (Gagné, 1984). Intellectual skills (or
procedural knowledge) is the application of knowledge that a learner uses to do a task (Gagné,
1984). Cognitive strategies are the skills that a learner applies to manage their own learning, also
known as executive processing or strategic knowledge (Gagné, 1984). Attitudes involve an
internal state of a learner valuing and choosing to apply the knowledge they have learned

26
(Gagné, 1984). Table 1 shows each of the core competencies for the curriculum, the
corresponding learning goal, and the Gagné learning outcomes.
Table 1
Major Steps and Knowledge Types
Major steps Learning goal Knowledge types
Demonstrate
competency in
information and data
literacy
When using information
and/or data, the learner will
assess and, when required,
explain the reliability,
relevance, credibility, and
biases in the information
and/or data.
Declarative knowledge
Concept of information literacy
Concept of data and biases
Concept of credibility
Intellectual skills
Differentiate between
information and data
Locate relevant and credible
information
Think critically about sources of
information and data
Abstract information in the form
of data
Explain the reliability, relevance,
credibility, and biases in the
information and/or data
Cognitive Strategies
Monitor, watch, and guide selfprogress of finding, storing,
managing, and organizing
information
Evaluate effectiveness of locating
good information and data
Attitudes
Values critical thinking
Enhance
communication and
collaboration skills
When learning or working, the
learner interacts,
communicates, and
collaborates with others
effectively in synchronous
and asynchronous digital
environments and, when
Declarative knowledge
Concept of synchronous versus
asynchronous
Concept of learning
Concept of effective
communication (1-1 or 1 to
many), collaboration (many to

27
Major steps Learning goal Knowledge types
required, can articulate best
practices and guidelines for
accessibility and
demonstrate common
features of digital tools for
communication and
collaboration
many, fewer than 10), and
interaction
Concept of digital environments
Concept of accessibility
guidelines for inclusivity
Recall WCAG 2.1 standards for
accessibility
Familiarity with communication
and collaboration tools
Intellectual skills
Organize digital files for ease and
effectiveness of sharing and
collaborating
Perform tasks using common
communication and
collaboration platforms and
tools
Create accessible digital content
following accessibility
standards (WCAG 2.1)
Present information in a medium
appropriate for intended
audience
Sharing and using digital content
legally
Cognitive Strategies
Reflect, monitor, evaluate, and
self-regulate communication
and collaboration behaviors
Asking for and using feedback to
improve communication and
collaboration skills
Seeking new knowledge and
strategies to improve
communication and
collaboration skills
Attitudes
Values continuing learning and
self-improvement

28
Major steps Learning goal Knowledge types
Values professionalism and
demonstrating respect for
others.
Confidence in using
collaboration and
communication tools.
Demonstrate
competency with
digital content
creation
When needing to demonstrate
a concept or idea, learner
will independently create
and publish digital content
(using visual design
principles) or develop a
computer program to
accomplish a task, using an
iterative design process
Declarative knowledge
Concept of digital content and
file formats for content
categories
Concept of digital creation
platforms and tools for content
creation
Concept of programming
instructions
Concept of program execution
Concept of tasks solvable by
computer programs
Concept of iterative design
process
Intellectual skills
Identifying, selecting, and using
software tools for graphic
design, video editing, web
content, and programming
tasks
Integrate text, images, videos,
audio, and animations into
digital content
Applying design principles to
digital content
Programming concepts, including
algorithm development, input
and output, and execution
order of instructions
Cognitive Strategies
Monitor, watch, and guide selfprogress for content creation
Identify areas for improvement
and set goals for growth

29
Major steps Learning goal Knowledge types
Seeking out and reflecting on
feedback for improvement
Attitudes
Values attention to detail
Values lifelong learning
Values the perspective of others
and designing for the end user.
Confidence in creating and
publishing digital content.
Practice safety and
cybersecurity
When using computing
devices, learner will
implement safety measures
to protect information and
digital assets by setting
strong passwords, using
two-factor authentication,
installing anti-virus
software, and frequently
updating software
Declarative knowledge
Attributes of a strong password
and password management
List and explain cybersecurity
threats including phishing,
malware, social engineering,
ransomware, identity theft, and
data breaches
Concept of authentication
methods for devices
Knowledge of NIST cycle of
Identify, protect, detect,
respond, recover functions of
cybersecurity
Knowledge of CIA triad model
confidentiality, integrity, and
availability
Measures to protect data and
devices, including anti-virus
software and software updates
Intellectual skills
Develop and maintain high level
of security awareness,
following emerging trends
Identify, understand, and evaluate
likelihood of potential threats
Practice security with browsing,
downloading, emails, and
regular software updates
Explain incidence response and
be ready to take action to

30
Major steps Learning goal Knowledge types
mitigate impact of a
cybersecurity incident
Use encryption or secure
communication methods to
protect sensitive information
Apply steps to protect data and
devices, including anti-virus
software and software updates
Apply CIA Triad model
principles to maintain personal
and organizational information
security
Cognitive Strategies
Monitor, watch, and guide selfprogress of knowledge, skills,
and behaviors related to safety
and cybersecurity
Assess and evaluate risk
awareness and tolerance
Attitudes
Values vigilance, responsibility,
and caution
Values ethical and responsible
behavior
Values and advocates for privacy
rights and personal data
protection
Confidence in applying steps to
protect data and devices,
including anti-virus software and
software updates
Constructing
knowledge and using
problem solving
skills
When learning something new
and/or solving a problem,
the learner will use a
systematic and organized
approach for gathering and
synthesizing information.
Learners will demonstrate
persistence and willingness
to fail when approaching
novel problems and use
Declarative knowledge
Concept of systematic and
organized approach for
information gathering
Concept of synthesizing
information
Concept of failure as necessity
for problem-solving

31
Major steps Learning goal Knowledge types
abstraction and
computational thinking
skills to iterate through
possible solutions to a
problem.
Concept that problem-solving
can be domain specific and
interdisciplinary
Concept of abstraction for
problem solving
Concept of computational
thinking
Listing problem-solving
strategies such as
brainstorming, critical
thinking, decision-making,
hypothesis testing, root cause
analysis, and systems thinking
Intellectual skills
Form connections between
sources of information
Critical assess knowledge gaps
and seek opportunities for
obtaining and integrating new
knowledge construction
Synthesize information
Using failure as an opportunity to
learn and iterate to explore new
ideas and innovations
Applies computational thinking
as a process for solving
problems
Applies creative thinking spiral
(experiment, create, imagine,
reflect, share, experiment,
create, imagine)
Utilize applicable problemsolving strategies for tasks
Cognitive Strategies
Monitor, watch, and guide selfprogress towards new
knowledge acquisition and
creative problem solving
Willingness to experiment and
fail while learning
Attitudes

32
Major steps Learning goal Knowledge types
Values curiosity, openmindedness, persistence,
adaptability, and creativity
Growth mindset and willingness
to be a lifelong learner
Attributes success and failure to
their own effort
Confidence in Constructing
knowledge and using problem
solving skills
The Learning Environment and the Learners
All learning happens in context, and so, to be successful, the curriculum should be
designed with the learning environment and characteristics of individual learners in mind (Smith
& Ragan, 2005). A learning environment is the “system” in which instruction takes place and
consists of the people, equipment, facilities, and community that impact (or are impacted by) the
learning (Smith & Ragan, 2005, p. 49). For this digital fluency curriculum, the learning
environment is the main campus of ZYX University. Analyzing the characteristics of the learners
means identifying the target audience and assessing what they are like and what they already
know (Smith & Ragan, 2005, p. 58). For this digital fluency curriculum, the learners are
expected to be first-year undergraduate students at ZYX University.
Description of the Learning Environment
ZYX University is a private institution located in a major metropolitan area in the
western region of the United States. Several thousand new undergraduates annually enter the
university as new first-year students. ZYX classrooms are all equipped with systems to support
projection and hybrid learning, but the technology provided within specific classrooms may
differ. Instructors generally need to bring their own computers and may need to verify the room

33
system to ensure they have the correct adaptors to connect to the classroom system. While some
classrooms may contain desktop computer systems that students can use, generally, students
bring their own laptop computers to class. The university library system offers a temporary
laptop loaner program, and the MATCH academic unit has its own laptop loaner program to
ensure students have access to a computer that will meet the needs of their technical coursework.
ZYX University has a campus-wide learning management system (LMS) and a plethora
of software programs that may be used for instructional purposes. For software that may require
expensive licenses, classes held within the MATCH unit have access to a virtual private network
(VPN) which allows students to access the software remotely. As a formal academic course, the
instruction of this curriculum must comply with the university’s contact hour requirements,
which specify in-class sessions of a minimum of 50 minutes per unit per week, as well as out-ofclass work of at least two hours per unit per week. Within MATCH, instructors generally
provide additional academic support in person or via video-conferencing software during office
hours as well as providing asynchronous support through email or discussion board forums.
Courses within MATCH typically include additional support through tutoring or office hour help
from past students working as course learning assistants. By providing a plethora of options for
supporting students, this curriculum is situated within a learning environment that strives to help
all learners succeed.
Teacher/Trainers/Facilitator Characteristics
This curriculum is designed to be used by faculty members in the MATCH unit, who
have a terminal STEM degree and a passion for teaching technology and computing to
undergraduate students. MATCH faculty members generally value lifelong learning and have a
predisposition to follow emerging trends in education and technology and a willingness to

34
explore new tools and techniques. Faculty are confident using a variety of media and technology
inside and outside the classroom environment to support learning. For this first iteration of
delivering this curriculum, the faculty will be highly experienced teachers, but as the need for
this course grows, it is likely that more inexperienced faculty may be recruited to deliver the
curriculum. Given this and the ever-changing landscape of digital fluency as new technology
emerges, it is expected that the curriculum itself will be consistently updated and expanded to
keep up with new technology trends and provide scaffolding for newer or less inexperienced
faculty.
Existing Curricula/Programs
This curriculum is being envisioned as a new general education survey course that
introduces students to the breadth of knowledge necessary to become digitally fluent. It is not
expected that it would need to fit into any existing curricula. ZYX University expects all general
education courses to provide learners with critical thinking skills to effectively, thoughtfully, and
productively function in a complex world (organization’s website1
). Learners at ZYX are
expected to become informed citizens who value lifelong learning, which is a value espoused
throughout this digital fluency curriculum.
Available Equipment and Technology
All classrooms at ZYX University are equipped with digital projectors and support
hybrid learning. Faculty will bring their own laptop computers and, if necessary, adapters for
connecting to the classroom hardware. Students will be expected to bring their own laptops;
however, some classrooms may have desktop computers that can be utilized and students

1 The actual URL is not provided because that would reveal the identity of the organization.

35
without a personal laptop will be provided instructions on how to obtain a loaner laptop through
the university or the MATCH program. No other specialized hardware is required, as all
multimedia resources will be available on the Internet, and all faculty and students will have
access through the University’s wireless network. The curriculum will be designed to use
software that is licensed by the University for use by all faculty, students, and staff, open-source
or other freely available software, or, if necessary, software that is accessible via ZYX
University’s remote desktop or virtual private network (VPN) systems.
Classroom Facilities and Learning Climate
The available classroom facilities at ZYX University can vary dramatically in
functionality and setup. Classes may be held in rooms with fixed auditorium seating, with mobile
tables and chairs, or with individual mobile rolling desks. Faculty may request specific
classroom spaces, but requests are not guaranteed, and the room style may impact the learning
climate.
This curriculum aligns with ZYX University’s values of accountability, integrity,
excellence, open communication, well-being, and diversity, equity, and inclusion. General
education courses are designed to support learners at ZYX to become informed citizens who
value lifelong learning, which is integral to this curriculum. Learners are encouraged to
challenge themselves and others through critical thinking and intellectual inquiry.
Description of the Learners
When designing a curriculum, it is important to purposefully create instruction with the
target audience in mind and focus on the similarities and differences between learners (Smith &
Ragan, 2005). In this section, I examine four major areas of learner characteristics. First,
cognitive characteristics, including prior knowledge, are explored. Next, physiological, affective,

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and motivational characteristics are addressed. Finally, the learners' social characteristics are
described.
Cognitive Characteristics
This curriculum is designed for first-year undergraduate students. ZYX students typically
demonstrate high aptitude for learning, and this curriculum assumes that students will have the
background knowledge and skills (language, reading level, visual literacy) to effectively engage
with the course content. However, following Gardner’s theory of frames of mind, or multiple
intelligences, learners may have higher aptitudes in different areas, including linguistic, musical,
logical-mathematical, spatial, bodily-kinesthetic, intrapersonal, or interpersonal (Gardner, 2011).
As such, instructors should recognize the kinds of intelligences that are involved in digital
fluency activities or processes and be cognizant of helping learners strengthen competencies
across intelligence areas as appropriate. Learners will be encouraged to think metacognitively
and recognize cognitive differences and specific aptitudes for themselves and others as they
support each other in knowledge construction during collaborative learning events.
Prior Knowledge
It is likely that learners will vary greatly in their prior knowledge, both general and
specific prior knowledge. General world knowledge varies with age, culture, and other factors
(Smith & Ragan, 2005). While most first-year students come to ZYX directly after completing
high school in the United States, the curriculum at high schools in the US can vary dramatically.
Students who start college later in life will have different life experiences that affect their general
world knowledge. International students attending ZYX will likely also have different prior
general knowledge. This diversity of background general knowledge should be considered an
asset for the classroom learning experience and used to enrich the curriculum.

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All students will have basic computer knowledge, which is necessary for even applying
to university, but the curriculum does not depend on any specific prior knowledge beyond those
basic skills. However, given the diversity of backgrounds and interests of ZYX University
students, it is likely that some students enrolled in the course will have significant prior
knowledge in multiple areas of the curriculum. This means that the design of the curriculum
needs to support learners who have more advanced knowledge as well as those learners who are
digital novices and need more support and scaffolding.
Physiological Characteristics
It is highly likely that most students will be healthy young adults, but ZYX University
has a diverse student body, and within that population, there may be other-abled learners. The
university has support systems to help provide accommodations for students who are visually or
auditorily impaired, as well as students with other learning disabilities. This curriculum should
be accessible to all learners at ZYX University and thus should follow accessibility guidelines
and comply with WCAG 2.1 standards to be inclusive of all learners.
Motivation Characteristics
Motivation is highly correlated with learning, and this curriculum will need to consider
the socioemotional characteristics of the learners. Learners will likely have variable levels of
interest in digital fluency. Undergraduate students are sometimes dismissive of their general
education courses, so while some students may welcome the opportunity to learn this material,
others may have little interest. By recognizing and acknowledging these differences in interest,
this curriculum can be designed to help increase student motivation and provide an effective
learning environment for all learners.
In order to help students value becoming digitally fluent and increase motivation, this

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curriculum can employ achievement goal theory (Ames, 1992; Urdan & Kaplan, 2020) and
expectancy value theory (Eccles & Wigfield, 2020; Wigfield, 1994) as frameworks to support
the design of the course content. As new technology emerges, learners will need to continuously
acquire, develop, and refine knowledge, skills, and attitudes across the competencies in this
curriculum to remain digitally fluent. Achievement goal theory highlights the importance of a
mastery orientation to learning, which is appropriate in this curriculum because in order to
remain digitally fluent, learners will need to be lifelong learners who set personal learning goals.
Expectancy value theory explains that the learners’ self-efficacy and values interact to predict
outcomes like engagement, continued interest, and achievement. Self-efficacy is the learners’
belief in their ability to succeed at a specific task (Zimmerman et al., 1992), and especially in
regards to technology, students may need feedback and scaffolding to build self-efficacy for
digital fluency competencies. Learners’ values are related to their prior experiences, beliefs, and
goals and affect if a student wants to complete a task. There are four types of values: attainment
value, intrinsic value, utility value, and cost (Wigfield, 1994; Wigfield et al., 2021). This
curriculum design can employ strategies to increase motivation by explaining how becoming
digitally fluent relates to the learners’ identity and future career goals (attainment value),
providing choices to make learning more enjoyable (intrinsic value), creating authentic realworld tasks that connect to the learners’ major or future career (utility value), and using
examples to explain how time and effort spent now can support future achievements (cost)
(Mathew et al., 2022).
Social Characteristics
The social characteristics of the learners that should be considered when designing a
curriculum include relationships with peers, feelings toward authority, tendencies toward

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cooperation or competition, moral development, socioeconomic background, racial/ethnic
background, and role models (Smith & Ragan, 2005). Undergraduate students at ZYX
University come from a diversity of backgrounds, and it is unlikely that all learners will share
the same social characteristics. As such, this curriculum should select examples from a variety of
different perspectives and contexts to be inclusive, relevant, and interesting for diverse learners.
To facilitate the competency of enhancing communication and collaboration skills, the instructor
should be prepared to model cooperative learning behaviors and help undergraduate students
recognize the benefits of working together to support learning. During instruction of this
curriculum, the instructor should be aware of the learners’ stage of moral development.
Undergraduate students are typically stabilizing the post-conventional, autonomous, or
principled level of moral development, which involves two stages: (Stage 5) the social-contract
legalistic orientation and (Stage 6) universal ethical principle orientation (Kohlberg & Kramer,
1969). Supporting moral development is especially important regarding aspects of legal and
ethical considerations of artificial intelligence and cybersecurity.
Implications of the Learning Environment and Learner Characteristics for Design
Carefully considering the learning environment and the learner characteristics is an
important component of curriculum design because these aspects affect the content of the
curriculum as well as the instructional strategies used to present the curriculum to the learners.
Smith and Ragan (2005) discuss many instructional techniques that instructors may want to
consider adjusting to meet the needs of learners. To keep the diverse population of ZYX
undergraduate students who may enroll in this general education course engaged and motivated
throughout the semester-long course, the instructor will need to consider employing many of
these instructional techniques (Kirschner & Hendrick, 2020).

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Given the diversity of prior knowledge in any cohort of undergraduate students, the
instructor should be prepared to vary the presentation speed or pacing of material to meet the
learners at their current level of knowledge and understanding. Some aspects of the curriculum
may need to be offered as optional asynchronous video recordings to provide scaffolding and
background information to learners who have less prior knowledge of digital fluency concepts.
The size and scope of instructional units or chunks may need to be adjusted to help reduce
cognitive overload.
To support students who may lack motivation or self-efficacy for digital fluency
competencies, the instructor may want to consider having a repertoire of different examples or
descriptions to help provide content relevancy for students from different backgrounds or
majors. Some students may need additional examples to practice skills and achieve mastery, and
instructors will need to consider providing choices for the difficulty level of practice items.
Another consideration would be to vary the level of concreteness or abstraction or vary the
amount of scaffolding or organizational support provided to the learner so that they can
experience an appropriate level of challenge, according to Vygotsky’s zone of proximal
development (Schunk, 2020).
The Curriculum
The purpose of this course is to teach undergraduate students how to become digitally
fluent and critically conscious consumers of computing. To accomplish this, students will
explore what digital fluency means for the areas of information and data literacy, communication
and collaboration, digital content creation, safety and cybersecurity, knowledge construction and
problem solving. Students will demonstrate their competency with each learning goal through a
series of individual and group assignments and projects. Additionally, students will think

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critically about computing and technology, exploring the historical, economic, and social
ramifications of our digital world and how they relate to diversity, equality, equity, inclusion,
justice, oppression, and power. This section has two main components: the curriculum analysis
and the lesson analysis.
List of Units, Terminal, and Enabling Objectives
Based on the literature review, the learning goals and Gagné outcomes have been
described in detail in Part 4 in the Summary of the Curriculum Content section. The learning
goals and Gagné outcomes become the basis for the learning objectives or behaviors that are
demonstrated for specific criteria during instruction. Learning objectives are defined by Smith
and Ragan as “precise, concrete, and specific” (2005, p. 96) goal statements with three parts: “1)
a description of the terminal behavior or actions that will demonstrate learning, 2) a description
of the condition of demonstration of that action, and 3) a description of the standard or criterion”
(Smith & Ragan, 2005, p. 97). Given the learning goals and Gagné outcomes, the instructional
designer can derive the terminal and enabling learning objectives, which focus on observable
behavior that can demonstrate what has been learned.
Demonstrate competency in information and data literacy
● Learning goal: When using information and/or data, the learner will assess and, when
required, explain the reliability, relevance, credibility, and biases in the information
and/or data.
○ Terminal Objective 1: Given a data set (during class), the learner will be able to
explain the reliability, relevance, credibility, and biases per program guidelines.

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○ Terminal Objective 2: After selecting a topic to research, the learner will locate
relevant and credible information and explain the reliability, relevance,
credibility, and biases in the information sources chosen per program guidelines.
● Declarative knowledge
○ Given a list of terms, learners will describe the meaning of and give examples and
nonexamples of the following, per the course materials
■ Concept of information literacy
■ Concept of data and biases
■ Concept of credibility
■ Concept of data types and variables (in programs and databases)
■ Abstract information in the form of data
■ Methods for storing, managing, and organizing data
■ Presenting information and data in an accessible manner.
○ Learners can summarize the differences between information and data.
○ Learners can describe credibility and bias in their own words
● Intellectual skills
○ Given information, learners can abstract the information in the form of data to be
stored in a computer, with skills measured according to a course rubric.
○ Given a source, learners can accurately classify it as data or information.
○ Given an information source, the learner can identify if it is relevant and credible
information, according to a course rubric.
○ Given information or data, the learner can explain the reliability, relevance,
credibility, and biases present, according to a course rubric.

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○ Given an existing data set, the learner can evaluate and explain biases in data sets,
according to a course rubric.
○ Learners can explain power dynamics that affect data and explain how technology
companies may manipulate data in visible and invisible ways, according to a
course rubric.
● Cognitive Strategies
○ In situations dealing with information or data, learners will monitor, watch, and
guide self-progress of finding, storing, managing, and organizing information and
record it in their journal.
○ When performing research or data gathering, learners will evaluate effectiveness
of locating good information and data using their journal.
● Attitudes
○ Learners will choose to apply critical thinking when dealing with sources of
information or data.
Enhance communication and collaboration skills
● Learning Goal: When learning or working, the learner interacts, communicates, and
collaborates with others effectively in synchronous and asynchronous digital
environments and, when required, can articulate best practices and guidelines for
accessibility and demonstrate common features of digital tools for communication and
collaboration.
○ Terminal Objective 1: When learning and working on class assignments, the
learner interacts, communicates, and collaborates with others effectively in
synchronous and asynchronous digital environments, according to course rubric.

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○ Terminal Objective 2: When required, the learner can articulate best practices and
guidelines for accessibility and demonstrate common features of digital tools for
communication and collaboration.
● Declarative knowledge
○ Given a list of terms, learners will describe the meaning of and give examples and
nonexamples of the following, per the course materials
■ Synchronous versus asynchronous
■ Learning
■ Effective communication (1-1 or 1 to many)
■ Collaboration (many to many, fewer than 10)
■ Interaction
■ Digital environments
■ Accessibility guidelines for inclusivity
■ WCAG 2.1 standards for accessibility
○ Learners can describe common features of several communication and
collaboration tools
● Intellectual skills
○ Upon generating digital files, learners can organize and share digital files (and
folders) for ease and effectiveness for collaborations with peers and instructors,
according to course guidelines.
○ Given a task, learners can collaborate with others on a given communication or
collaboration platform and tool to create accessible digital content following
accessibility standards (WCAG 2.1)

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○ Given a task, learners can collaborate with others to present information in a
medium appropriate for intended audience, according to a course rubric
○ Given a task, learners will share and use digital content legally, according to US
laws.
● Cognitive Strategies
○ In situations where learners are communicating and/or collaborating with others,
they will reflect, monitor, evaluate, and self-regulate their behaviors, ask for and
use feedback to improve skills, and seek new knowledge and strategies to
improve skills, and record it in their journals.
● Attitudes
○ Learners will choose to find new opportunities for learning and self-improvement.
○ Learners will choose to treat others professionally and with respect.
○ Learners will demonstrate confidence in using collaboration and communication
tools and learning new skills within those tools.
Demonstrate competency with digital content creation
● Learning Goal: When needing to demonstrate a concept or idea, the learner will
independently create and publish digital content (using visual design principles) or
develop a computer program to accomplish a task, using an iterative design process.
○ Terminal Objective 1: When given a task to demonstrate a concept or idea, the
learner will independently create and publish digital content (using visual design
principles), according to a course rubric.

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○ Terminal Objective 2: When given a programming task, the learner will develop a
computer program to accomplish a task, using an iterative design process,
according to a course rubric.
● Declarative knowledge
○ Given a list of terms, learners will describe the meaning of and give examples and
nonexamples of the following, per the course materials
■ Digital content and file formats for content categories
■ Programming instructions
● Nature of computer programs
● Conditionals, loops, functions
● Program input and output
● Flow-charts
● Algorithms
■ Program execution
■ Tasks solvable by computer programs
■ Iterative design process
■ Artificial intelligence
■ Ethics of using and creating artifacts with AI
■ Pair programming, AI pair programming
○ Learners can describe common features of several digital creation platforms and
tools for content creation
● Intellectual skills

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○ Given a task, the learner can identify, select, and use the appropriate software
tool(s) for graphic design, video editing, web content, and programming tasks,
according to a course rubric
○ Given a task, the learner can integrate text, images, videos, audio, and animations
into digital content, according to a course rubric
○ Given specifications for creating digital content, the learner can successfully
apply design principles, according to a course rubric
○ Given specifications for a programming task, the learner can apply programming
concepts, including algorithm development, input and output, and execution order
of instructions to complete task, according to a course rubric
● Cognitive Strategies
○ In situations involving content creation, the learner will monitor, watch, and guide
self-progress for content creation and record it in their journal.
○ In situations involving content creation, the learner will identify areas for
improvement and set goals for growth and will seek out and reflect on feedback
for improvement using their journal.
● Attitudes
○ Learners will choose to find new opportunities for learning and self-improvement.
○ Learners will choose to value the perspective of others and design for the end
user.
○ Learners will choose to pay close attention to details within digital content
creation.

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○ Learners will choose opportunities to build confidence in creating and publishing
digital content.
Practice safety and cybersecurity
● Learning Goal: When using computing devices, the learner will implement safety
measures to protect information and digital assets by setting strong passwords, using twofactor authentication, installing anti-virus software, and frequently updating software.
○ Terminal Objective 1: When using computing devices, learners will implement
safety measures to protect information and digital assets by setting strong
passwords, using two-factor authentication, installing anti-virus software, and
frequently updating software, according to a course rubric.
● Declarative knowledge
○ Given a list of terms, learners will describe the meaning of and give examples and
nonexamples of the following, per the course materials
■ Attributes of a strong password and password management
■ Cybersecurity threats including phishing, malware, social engineering,
ransomware, identity theft, and data breaches
■ Authentication methods for devices
■ Knowledge of NIST cycle of Identify, protect, detect, respond, recover
functions of cybersecurity
■ Knowledge of CIA triad model confidentiality, integrity, and availability
■ Measures to protect data and devices, including anti-virus software and
software updates
● Intellectual skills

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○ When using any computing devices connected to a network, the learner will
practice high levels of security awareness, following emerging trends. This
includes identifying, understanding, and evaluating the likelihood of potential
threats; practicing security with browsing, downloading, emails, and regular
software updates; explaining incident response and be ready to take action to
mitigate impact of a cybersecurity incident; using encryption or secure
communication methods to protect sensitive information; and applying steps to
protect data and devices, including anti-virus software and software updates, all
according to a course rubric
● Cognitive Strategies
○ In situations involving safety and cybersecurity, learners will monitor, watch, and
guide self-progress of knowledge, skills, and behavior and record in their journal
○ In situations involving safety and cybersecurity, learners will assess and evaluate
risk awareness and tolerance, and record it in their journals.
● Attitudes
○ Learners will choose to be vigilant, responsible, and cautious when using any
computing devices connected to a network.
○ Learners will choose to practice ethical and responsible behavior.
○ Learners will choose to advocate for privacy rights and personal data protection.
○ Learners will seek opportunities to continue to develop confidence in applying
steps to protect data and devices, including frequent anti-virus software and
software updates.

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Constructing knowledge and using problem solving skills
● Learning Goal: When learning something new and/or solving a problem, the learner will
use a systematic and organized approach for gathering and synthesizing information.
Learners will demonstrate persistence and willingness to fail when approaching novel
problems and use abstraction and computational thinking skills to iterate through possible
solutions to a problem.
○ Terminal Objective 1: When learning something new and/or solving a problem,
the learner will use a systematic and organized approach for gathering and
synthesizing information, according to a course rubric.
○ Terminal Objective 2: When given a task, learners will demonstrate persistence
and willingness to fail when approaching novel problems and use abstraction and
computational thinking skills to iterate through possible solutions to a problem,
according to a course rubric.
● Declarative knowledge
○ Given a list of terms, learners will describe the meaning of and give examples and
nonexamples of the following, per the course materials
■ Systematic and organized approach for information gathering
■ Synthesizing information
■ Failure as necessity for problem-solving
■ Problem-solving can be both domain specific and interdisciplinary
■ Abstraction for problem solving
■ Computational thinking

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○ Learner can summarize a variety of problem-solving strategies such as
brainstorming, critical thinking, decision-making, hypothesis testing, root cause
analysis, and systems thinking
● Intellectual skills
○ Given a problem to be solved, learners will show competency in the following
skills measured by a course rubric:
■ Forming connections between sources of information
■ Critically assess knowledge gaps and seek opportunities for obtaining and
integrating new knowledge construction
■ Synthesizing information
■ Using failure as an opportunity to learn and iterate to explore new ideas
and innovations
■ Applying computational thinking as a process for solving problems
■ Applying creative thinking spiral (experiment, create, imagine, reflect,
share, experiment, create, imagine)
■ Utilizing applicable problem-solving strategies for tasks
● Cognitive Strategies
○ In situations dealing with new knowledge acquisition and creative problem
solving, learners will monitor, watch, and guide self-progress record it in their
journal
○ In situations dealing with new knowledge acquisition and creative problem
solving, learners will experiment and fail while learning and record successes and
failures in their journal.

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● Attitudes
○ Learners will choose to be curious, open-minded, persistent, adaptable, and
creative and approach knowledge acquisition and problem solving with a growth
mindset and willingness to be a lifelong learner.
○ Learners will choose to attribute success and failure to their own effort while
continuously building confidence in constructing knowledge and using problem
solving skills.
Overview of the Units
Learners within this course will have various degrees and levels of prior knowledge and
experience with technology, and because the digital landscape is constantly changing, this
curriculum, like the learners in this course, will need to remain adaptable and flexible to meet the
specific needs of the learners enrolled in each section of the course. By applying a spiral
curriculum approach, where content and concepts are visited at different times in the course with
increasing complexity (Kirschner & Hendrick, 2020), this curriculum design should provide a
meaningful experience for all learners. Kirschner and Hendrick (2020) describe that a spiral
curriculum uses the concept of “zooming out to zoom in,” which allows learners to have a
meaningful context for instructional content and the application of learning. Unlike instruction
that aims to teach a specific technology tool or skill, this curriculum structures learning around
helping students explore technological concepts and domains as they build fluency in the areas
of information and data literacy, communication and collaboration, digital content creation,
privacy, safety and cybersecurity, and knowledge acquisition and problem solving, as seen in
Figure 1.

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Given this, there is no a priori sequencing of topics or units; rather, topics are built upon
across various units of the curriculum. However, it can be argued that the competency of
constructing knowledge and problem solving is at the core of all the other competencies, so it
would make sense that this competency should appear first in the curriculum. By initially
exploring the competency of constructing knowledge and problem solving, the instructor can
provide an initial context, vocabulary, and approach for all the other competencies in this
curriculum, given the zoomed-out view of how to approach developing fluency in each of the
competency areas. A final note: during this course, it is expected that each learner may achieve
different levels of mastery or fluency regarding each of these competencies; but that everyone
will gain knowledge, skills, and attitudes for each fluency that will help them become lifelong
learners who continue to develop as new technology emerges.
Figure 1
Digital Fluency Course Units in Spiral Curriculum

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Given the traditional 15-week semester at ZYX University, the instruction has been
broken into weekly topics for the first 13 weeks, with the last two weeks devoted to a final group
project. Using the spiral curriculum concept as a guide to revisit each competency multiple times
across the semester, a summary of the individual weekly units was created and analyzed using a
scope and sequence diagram, as explained in Smith and Ragan (2005). This process not only
helped guide lesson planning but highlighted that the original plan included some gaps within the
units and did not offer enough opportunities to master all the competencies. Units (and
corresponding assessment opportunities) were refined so that each competency had at least two
levels of mastery developed across the semester. This process led to these units:
● Unit 1: Introduction to learning and problem solving
● Unit 2: Introduction to information literacy
● Unit 3: Introduction to digital content creation
● Unit 4: Introduction to communication and collaboration
● Unit 5: Introduction to safety and cybersecurity
● Unit 6: Introduction to data literacy
● Unit 7: Building problem solving with data literacy
● Unit 8: Using AI (Content creation, communication, problem-solving, and cybersecurity)
● Unit 9: Programming (as content creation)
● Unit 10: Collaboration and programming
● Unit 11: Programming, data science, and AI
● Unit 12: Problem solving in cybersecurity
● Unit 13: Creation, collaboration, and accessibility
● Unit 14: Last two weeks + finals: Problem solving in practice (Group Project)

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Within the scope and sequence diagram (Figure 2 and Figure 3), the concept of levels of
mastery was introduced to demonstrate the idea that true “mastery” of digital fluency skills is not
possible given the dynamic nature of innovation in the field of technology. This curriculum thus
provides at least two mastery opportunities (levels) for each competency, demonstrating that the
learner has reached a level of learning that would allow them to transfer a specific subset of
knowledge, skills, and attitudes to new learning opportunities. The scope and sequence diagram
for this curriculum (as presented in Figure 2 for Units 1 through 8 and Figure 3 for Units 9
through 14) includes the intermediate assessments (projects and assignments) in which learners
can demonstrate mastery across each core competency. These intermediate assessments are
marked with the letter “m” and are included at the point in the curriculum during which these
assessments would be due.

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Figure 2
Scope and Sequence of the Curriculum, Part One
Note. The letters in the diagram represent the following: Assessment (A), Introduced (I), Reinforced (R), or Mastered (M or m) - with
intermediate levels of fluency mastered through periodic assessments marked with a lowercase (m) and course level mastery denoted
with an uppercase (M). Colors correspond to the five core competency areas: purple for problem solving, blue for information and
data literacy, yellow for communication and collaboration, green for digital content creation, orange for safety and cybersecurity, and
gray for assessments.
Part One
Core Competencies
Unit 1 Unit 2 Unit 3 A Unit 4 Unit 5 A Unit 6 Unit 7 A Unit 8 A
Problem solving I R R m1 R R m2 I, R R
Information and data
literacy I R m1 I, R R m2
Communication and
collaboration I R R m1 I, R m2
Digital content creation I
R,
m1 R I, R m2
Safety and cybersecurity I R R m1
Critically conscious
computing I I R I I, R R m1 I, R m2

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Figure 3
Scope and Sequence of the Curriculum, Part Two
Part Two
Core Competencies Unit 9 A Unit 10 A Unit 11 A Unit 12 Unit 13 A Unit 14
Summative
Evaluation
Problem solving I, R R R m3 I, R R m4 R M*
Information and data
literacy R m3 R M*
Communication and
collaboration R m3 R m4 R M*
Digital content creation I, R R I, R R m3 R m4 R M*
Safety and cybersecurity I, R m2 R M*
Critically conscious
computing I,R I, R m3 R m4 R M*
Note. The letters in the diagram represent the following: Assessment (A), Introduced (I), Reinforced (R), or Mastered (M or m) - with
intermediate levels of fluency mastered through periodic assessments marked with a lowercase (m) and course level mastery denoted
with an uppercase (M). Colors correspond to the five core competency areas: purple for problem solving, blue for information and
data literacy, yellow for communication and collaboration, green for digital content creation, orange for safety and cybersecurity, and
gray for assessments.

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Delivery Media Selection
In the context of curriculum design, media selection involves considering the most
appropriate way to deliver instruction to support the cognitive processes of learning. As Clark
(1983) noted, careful consideration of the methods underlying media is the most important
component of learning. This means that prior to media selection, one must consider the
instructional principles and methods that will best support student learning (Clark et al., 2010).
Media is not just computers and technology but includes all aspects of the delivery of instruction.
In this section, I explore media selection based on the Clark et al. (2010) framework of selecting
media based on questions and considerations of affordances, restrictions, and client preferences.
General Instructional Platform Selection in Terms of Affordances and Restrictions
ZYX University considers in-person learning a critical component of high-quality
undergraduate education, and so this curriculum is designed to be delivered in a blended mode;
with a combination of synchronous or “real-time” classroom learning and asynchronous “store
and forward” learning (Worthington, 2013). Within this blended mode of learning, there are
numerous options for media use. This curriculum makes extensive use of multiple types of
media. Media includes human resources, including the instructor and learning assistants;
standard resources used in higher education like the Learning Management System (LMS);
written resources; links to websites and articles; PowerPoint slides, and videos. Additionally,
more specialized content-specific media like the Ed Stem platform and various other specialized
software tools and applications are also used in this curriculum.
According to Clark et al. (2010) there are three key affordances that should be considered
when selecting media for a curriculum: access, consistency, and cost. Each media type affords,
or allows, certain opportunities or benefits compared with other media selections. In addition to

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considering affordances when selecting media, Clark et al. (2010) also emphasize the
consideration of three key restrictions. The three key restrictions that should inform media
selection for curriculum development are conceptual authenticity, immediate feedback, and
special sensory requirements. Specific learning tasks or goals may restrict the use of some media
types. Finally, consideration of client preferences or other conditions of the learning environment
must be factored into the media selection process. Below, client preferences and each of these
key affordances and restrictions are defined and discussed regarding media selection for this
digital fluency curriculum.
Access
Access refers to the number of learners and the platform or location, such as in-person or
synchronous training versus asynchronous training. This curriculum is designed to support firstyear undergraduate students with several important competencies related to digital fluency, a
topic that is constantly evolving as new technologies emerge. Students with vastly different
levels of background knowledge and experiences will need to be supported. As such, the number
of learners within the class will need to be capped to a reasonable size (30 maximum) to create a
learning community that can adapt to individual student needs.
The blended format of the course design supports access in two ways: during the inperson, synchronous class sessions, students will have immediate feedback and access to the
instructor and learning assistants, while the asynchronous “flipped-classroom” readings and
videos will allow students to have 24-hour access to materials, along with the ability to replay
and control the presentation speed to better support learning. Media used during the in-person
synchronous class sessions includes instructor and learning assistants, PowerPoint presentations,
and the LMS. Media used during the asynchronous sessions includes instructor-created videos,

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other online videos, and written resources. To be as inclusive as possible and allow access for
students who may be ill or unable to attend class for other reasons, it is anticipated that students
will be allowed to participate in the real-time class sessions either in the classroom environment
or through a video-conferencing environment. Recording the live class sessions and making
those recordings available through the LMS affords learners the opportunity to review portions
of class that may have been challenging or misunderstood during the initial exposure, further
supporting more in-depth learning through on-going access to materials. Furthermore, by
incorporating collaborative learning technologies explicitly designed for learning skills in
programming (Ed, n.d.), students will have better access to material and real-time learning
support than what is traditionally afforded by traditional learning management systems (LMS)
(Worthington, 2013, p. 2).
Consistency
Consistency examines how important it is to have the same content and pedagogy
delivered to all learners Clark et al. (2010). This may apply in part or as a whole. It is important
to note that some content should be consistently delivered, but other content should be
customized to the learner.
The consideration of affordances for consistency involves determining what content and
pedagogy should be delivered in the same manner for all learners and what content should be
customized for individual learners. Higher education courses typically use learning management
systems (LMS), which afford consistency for learners to access course materials and grades.
However, for specialized disciplines like programming, the experience can still be fragmented.
By leveraging newer collaborative digital learning platforms like EdStem (Ed, n.d.), this
curriculum can offer learners an even more consistent learning experience. The Ed platform

61
offers a series of tools, including discussion boards, course modules and lessons, and integrated
coding workspaces for development in multiple programming languages, all of which are
specifically designed to support coding and more technology-centric learning. All media
selections within this curriculum are selected to provide consistency in content delivery for
learners. For content that may need to be further customized for individual learners, alternative
pathways through the content, or inclusion of prerequisite modules can offer a consistent but
more customizable approach for learning.
Cost
Lastly, the selection of media is also determined by the costs to deliver content to
learners (Clark et al., 2010). As a new general education course at ZYX University, this
curriculum can leverage the infrastructure already in place at the University. A traditional LMS
environment is provided for all undergraduate courses, but faculty teaching within the MATCH
unit also have the option of using the Ed platform, so no additional costs are incurred for the
learning platforms. Additionally, cost for the instructor and learning assistant staff, classroom
resources (hardware and software), Zoom video conferencing software, and licenses for common
software applications are covered by ZYX University.
Given the changing nature of technology and how that may affect many aspects of this
curriculum, care must be taken to identify the modules and content that will remain relatively
constant over time and those which may rapidly change, within or across semesters. For the
purposes of media selection, more stable content within a module could be recorded as
asynchronous videos that could be used across different offerings of the course, whereas content
involving emerging trends and technologies would be better presented during an in-person class
session or presented through the use of available online videos. On an adjacent, but related note,

62
there will likely be ongoing costs each year to revamp portions of the course to stay relevant as
well as one-time or on-going subscription costs for some of the technologies. While these costs
may not be due to (or affect) media selection, keeping in mind the ongoing costs for human
resource development and software needs is an important consideration for this curriculum.
Additionally, while course preparation and curriculum updates are typically considered part of
the normal teaching load for faculty, this course may involve a higher-than-normal update and
refresh cycle, which might potentially affect costs, as course load calculations or a supplemental
stipend might be necessary to account for this additional faculty effort.
Conceptual Authenticity
Conceptual authenticity involves considering the requirements for applying the new
learning and what, if any, conditions must be present to accurately (or adequately) demonstrate
or practice the task (Clark et al., 2010, p. 288). These requirements might serve to restrict what
media would be appropriate for content delivery. While there are aspects and topics within this
curriculum that can be applied anywhere, throughout many modules of the curriculum, learners
will be engaging with each other and technology in ways that will require them to think critically
about their current learning conditions and determine how to approach solving a task based on
that conditional knowledge. Learners may be required to use media such as search engines,
library databases, AI systems, as well as software to create visual representations or videos to
convey information to others. In all these situations, conceptual authenticity is paramount; the
instructor must help guide the students to select and utilize the correct media for the task that
they want to accomplish. Additionally, when considering developing communication and
collaboration competency, the only way to authentically practice and develop those skills is
through team projects and engagement with peers on those projects. Teaching methods and

63
media used to develop this competency will need to ensure that students are not just dividing and
conquering tasks, but that they are using communication and collaboration technology and media
to effectively work together to accomplish the learning objectives.
Immediate Feedback
Restrictions on media selection for feedback involves thinking about what situations may
require live, immediate, synchronous feedback to promote learning, especially for complex
knowledge, which Clark et al. (2010, p. 288) explain as knowledge needing “integration and
coordinated performance of task-specific constituent skills.” Throughout this curriculum,
learners will be exposed to and expected to use a wide variety of media for learning. Some of the
media tools may themselves offer immediate feedback for learning, while others will need to be
explored within the classroom environment so that instructors and learning assistants can help
provide immediate feedback and guidance to students. For example, many coding environments
are set up to automatically give syntactical feedback as well-run automated test cases for
specification verification, which help learners receive partial corrective feedback. While this
might not be comprehensive enough to offer all the feedback a learner may need to master
coding skills, it can help to build confidence and maintain motivation when working on
complicated learning tasks, and the instructor (or course learning assistants) can supplement with
additional asynchronous feedback at the conclusion of the learning task (which is supported in
the Ed learning environment.) For other learning tasks within this curriculum, immediate
feedback can be given based on observations of students practicing skills by themselves or with
others during a class session. For tasks that do not require immediate feedback, learners may
engage with the task outside of class and use appropriate media to submit a finished work
product for summative feedback.

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Special Sensory Requirements
Finally, use of certain media may be restricted by special sensory requirements for a
learning task. If learners are required to use their senses of smell, taste, and touch for a specific
concept, then online or virtual media would be inappropriate choices to meet those learning
objectives. The current learning objectives for this course do not require sensory information
beyond visual and aural. However, it should be noted that to provide an accessible learning
environment that is inclusive for learners with visual or auditory disabilities, all instructional
media should follow accessibility guidelines. For learners with visual impairments, providing
detailed descriptions of tables, charts, diagrams, or images used in learning materials would be
necessary. For learners with hearing impairments, including captions for in-class activities and
all videos are required if live support for sign language translation is not already available for the
learner(s). Future iterations of this course may include technologies such as augmented or virtual
reality (AR/VR) systems, which could necessitate the selection of media to meet sensory
requirements.
Client Preferences or Specific Conditions of the Learning Environment
ZYX University has traditionally required that undergraduate courses be offered as live,
in-person instructional experiences. Faculty have the freedom to adapt a flipped-classroom or
blended learning approach, but there is still a minimum number of live contact hours that are
required, so undergraduate courses generally cannot be fully online and asynchronous. During
the COVID-19 pandemic, learning immediately transitioned to an online-only modality, and
many instructors adapted their materials to accommodate that switch. While the online modality
worked for many students and instructors and, in some cases, may have been preferred for some,
after the pandemic, classes were expected to return to in-person, while adding an option for

65
Zoom participation for learners who could not attend class due to illness or travel restrictions.
Many faculty found supporting students live and in class and those participating online through
Zoom to be extremely challenging. Not only did faculty face technology challenges using
inconsistent setups within different classroom environments; hy-flex learning often involves
limitations such as laptop screen size for presenting course materials while running Zoom, which
leads to additional challenges engaging with online participants while also managing the learners
physically present in the classroom. Due to these challenges, along with a drop in student
attendance when class sessions were recorded, many faculty abandoned the Zoom remote
participation option when it was no longer required by the University. However, these actions
and resulting decisions were often reactionary and were not necessarily thoroughly explored
through the lens of considering all possible affordances and restrictions of remote participation
and asynchronous recordings for student learning. Additionally, the flexibility and access
afforded to students by offering hy-flex and asynchronous options for class participation is worth
considering, even if the in-person learning environment remains the preferred choice for optimal
learning.
Offering accommodations for hy-flex or asynchronous participation remains the choice
of individual faculty members at ZYX University. To be as inclusive as possible, this curriculum
design recommends that students be allowed to participate in class sessions either in the
classroom space or online through Zoom participation. Furthermore, students who can not attend
synchronously should be allowed to watch class recordings. However, since participating online
or asynchronously may lead to inferior learning outcomes (compared to purely online or purely
in-person learning), the course syllabus will set clear guidelines and limitations to help ensure
that students meet the overall course learning objectives. Whether required or not, setting up the

66
learning environment to allow for accommodations to support remote or asynchronous
participation is a choice that may help promote accessibility and educational equity for learners
who need it, either temporarily or on a more permanent basis. As long as course policies help
ensure that students choose options that best support achieving their learning goals while
considering any extenuating circumstances, learners can feel supported and encouraged to
continue learning, even when facing temporary setbacks.
Specific Media Choices
Based on the considerations above, this course is designed to be taught in a blended
mode, with a combination of synchronous and asynchronous learning activities. Different media
types help achieve specific content and learning goals within the curriculum. Table 2 shows
curricular media choice, along with the purpose and benefits of that media type.
Table 2
Media Choices in Digital Fluency Course
Media Purpose Benefits
Ed platform or
traditional
LMS
Structure and organization of
content for ease of locating all
course materials, used in both
synchronous and asynchronous
sessions.
Provides discussion boards as
well as submission of materials
or learning artifacts.
Supported and paid for by
university and/or school.
Content can be duplicated or
modified easily from one
course offering to another.
Coding support built in to Ed
platform.
Instructor Facilitates acquisition of
knowledge, skills, and attitudes
for digital fluency.
Provide expertise, guidance,
clarification, and immediate
feedback during live class
sessions.
Provide additional synchronous
Expert in field.
Consistency in curriculum
delivery.
Provides learning models and
examples.
Building a learning community
for students.

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Media Purpose Benefits
support during office hours.
Provide asynchronous feedback
or support using LMS.
Learning
assistants
Additional support during class
and office hours.
Provide feedback and help with
technical questions.
Near-peer support of learning.
Lower cost (for the university) or
free (for the students) support
for extra help and feedback.
Written
resources
Step by step instruction for tasks
or activities or facilitations.
Help manage the learners’
cognitive load for approaching
learning.
Specific to the course.
Easily modified.
Supports content delivery.
Links to
external
websites or
articles
Contemporary information.
Knowledge acquisition and
connections.
Sharing of peer-reviewed
resources.
Leverage high-quality existing
resources.
Promote diversity, provide
different perspectives.
Easily adaptable.
PowerPoint
slides
To provide organization and
structure to class sessions.
Serves as an after-class
reference.
Guidance and scaffolding for
class activities and discussions.
Easily modified and adapted.
Instructor
created videos
Flipped video lectures for
information dissemination.
Consistency in content delivery.
Can be reused while topics
remain relevant.
Online videos Provides expertise or viewpoints
on content.
No internal video production
costs.
Consistency in content delivery.
Software tools
and
applications
Provide hands-on experience
with technologies.
Opportunity to learn by doing
with support from instructor,
learning assistants, and/or

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Media Purpose Benefits
peers.
Builds communication and
collaboration skills.
General Instructional Methods Approach
The instructional methods used to structure the design for this curriculum are based on
educational research involving instructional principles, guided experiential learning, and lessonlevel organizational strategies. Merrill (2002) identifies five principles of instruction that are
foundational components of many design theories and models for learning. Clark et al. (2010)
provide a translation of those principles into instructional methods. Below is a summary of these
five principles and corresponding instructional methods (Clark et al., 2010; Merrill, 2002, pp.
276–277):
1. Problem-centered: Promote learning by encouraging students to solve real-world
problems.
2. Activation: Promote learning by activating learners’ previous knowledge or experiences
(use analogies and examples that rely on prior knowledge).
3. Demonstration: Promote learning by providing clear demonstrations of knowledge, tasks,
or skills rather than just saying or telling what is to be learned.
4. Application: Promote learning by requiring students to frequently practice using new
knowledge, tasks, or skills to solve problems while providing formative feedback.
5. Integration: Promote learning by encouraging transfer of new knowledge or skills into
everyday life by offering opportunities to practice small parts of tasks as well as whole,
complete tasks, during and after instruction.

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These principles and corresponding instructional methods are applicable to the Gagné
events of instruction: gaining attention, informing the learner of the objective, stimulating recall
of prerequisite knowledge, presenting stimulus materials, providing learning guidance, eliciting
performance, providing feedback, assessing performance, and enhancing retention and transfer
(Smith & Ragan, 2005, p. 129). Guided experiential learning (GEL) is an evidence-based
approach to instructional design that combines Merrill’s principles, cognitive task analysis
(CTA), and problem-centered learning (Clark et al., 2010). The GEL system recommends the
use of CTA to determine accurate and exact content to be included within each lesson, focusing
on an expert's problem-solving process (including the objective, equipment, conceptual and
procedural knowledge, and performance standards) for completing a given task. GEL requires
that lessons include each of the following in this order:
1. Objectives: the actions, conditions, or standards to be accomplished in lesson
2. Reasons for learning: benefits or advantages for learning and risks if not learned
3. Overview: content outline, knowledge models - advanced organizer
4. Conceptual knowledge: what concepts, processes, and principles are needed to perform a
task or solve a problem (includes examples and analogies to support learning)
5. Demonstration of the procedure: the how-to description, including all steps
6. Part and whole-task practice – including corrective or formative feedback during practice
of the procedure
7. Challenging, competency-based tests - including assessment of reactions like confidence
and value rating and performance, i.e., assessment of ability to remember and apply
conceptual knowledge and skills (Clark et al., 2010, pp. 277–278)

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Throughout the curriculum design process and all learning activities, it is helpful to
consider how to reduce cognitive load and increase the learners’ sense of self-efficacy (Smith &
Ragan, 2005). One way to do this is to consider Vgotsky’s theory of the zone of proximal
development (ZPD) , which looks at the difference between what learners can accomplish on
their own versus what they can do with assistance from others (Schunk, 2020). Another way of
thinking about ZPD is based on the level of scaffolding or locus of cognitive processing (Smith
& Ragan, 2005, p. 130). Curriculum designers can provide alternative activities for events
depending on the needs of learners. Generative activities are low scaffolded activities where the
student is primarily responsible for arranging learning conditions, whereas supplantive activities
are high scaffolded activities where the cognitive processing for practicing learning is primarily
supplied by the instructor or lesson instructions (Smith & Ragan, 2005). This curriculum design
leverages real-world problem-solving for all digital fluency competencies and provides students
with choices of problems to work on, which increases self-determination and in-turn, motivation
(Ryan & Deci, 2000). Finally, by emphasizing attitudes in addition to knowledge and skills for
each competency, students are supported with recognizing the value of learning tasks, which also
supports increased motivation (Schunk, 2020).
Implementation and Evaluation Plan
To increase the likelihood of a curriculum’s success, it is important to consider
implementation and evaluation plans as part of the design process. In the most general sense,
implementation involves putting the curriculum into use in the real-world environment for which
it was designed (Smith & Ragan, 2005). Evaluation involves assessing what learning occurs as a
result of the curriculum. For this curriculum design, an evaluation will be completed using the
New World Kirkpatrick model (J. D. Kirkpatrick & Kirkpatrick, 2016).

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Implementation Plan
Smith and Ragan (2005) discuss six specific stages of the implementation process:
awareness, interest, evaluation, trial, adoption, and integration. This model is not directly
applicable to higher education contexts that often introduce new courses without the benefit of a
trial or pilot. However, their idea that curriculum designers treat implementation as a process to
support the integration of new content can be applied (Smith & Ragan, 2005). As part of this
implementation process, Smith and Ragan discuss the Concerns-Based Adoption Model
(CBAM) and four corresponding instruments: the Stages of Concern Questionnaire (SoCQ), the
Levels of Use Questionnaire (LoUQ), the Innovation Configuration Matrix (ICM), and the
Intervention Taxonomy (2005, p. 307) and suggest that the CBAM tool can support
implementation efforts. While the application of the CBAM model is beyond the scope of this
dissertation, if ZYX University wants to expand the impact and scope of this digital fluency
course to reach all undergraduate students, it may be worthwhile to engage a small team to
determine how CBAM data may help improve and expand future offerings of this digital fluency
curriculum.
For purposes of this design, the initial offering of the digital fluency course may be
treated like a pilot program, for internal implementation and evaluation purposes. Throughout
the initial offering, the instructor can gather information from the learners and use that data to
revise the course, considering if changes can be made immediately, or for the next
implementation of the course. To collect this data, learners will be prompted to complete
feedback after each unit. This feedback should be formative in nature, and ideally will also serve
to facilitate and reinforce student learning. This formative feedback can be easily gathered
through weekly exit tickets in which students can provide interest feedback in a simple Likert

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survey, but also include a summary of the main take-aways for the unit, raise any additional
content questions that they may have, and provide a metacognitive reflection. With carefully
constructed prompts, this data can be quickly synthesized by AI, and then used to revise the
course.
Evaluation Plan
Technology has permeated all sectors of the post-college job market; now more than
ever, it is critical that college graduates are not only digitally literate, but also digitally fluent.
This curriculum aims to develop a dynamic approach to teaching undergraduates digital fluency
through building knowledge, skills, and attitudes towards technology and computing so that they
become lifelong thinkers, learners, creators, and innovators in our increasingly technological
world. The purpose of this course is to teach undergraduate students how to become digitally
fluent and critically conscious consumers of computing. To accomplish this, students will
explore what digital fluency means for the areas of information and data literacy, communication
and collaboration, digital content creation, safety and cybersecurity, knowledge construction and
problem solving. As such, evaluation of the success of the course to achieve these outcomes is
critical.
Evaluation Framework
The New World Kirkpatrick Model (J. D. Kirkpatrick & Kirkpatrick, 2016) is the basis
for the curriculum evaluation presented in this section. Much like the traditional Kirkpatrick
model (D. L. Kirkpatrick, 2006), there are four distinct levels in the New World Kirkpatrick
Model: Level 1 (reaction), Level 2 (learning), Level 3 (behavior), and Level 4 (results). The
difference between the old Kirkpatrick evaluation model and the New World Model is the order
of planning and implementation of these levels. In the New World Model, the evaluation is

73
planned in reverse, focusing on the desired outcomes or results and working backwards to
thinking about engagement and satisfaction. The evaluation process in the New World Model
may be implemented in chronological order but may also be completed in a non-sequential
manner. By planning first for results and leading indicators, it is more likely that the evaluation
of a curriculum will reach the desired outcomes, whereas the old model sometimes led to an
evaluation focused almost exclusively on Levels 1 and 2.
Level 4: Results and Leading Indicators
The New World Kirkpatrick Model (J. D. Kirkpatrick & Kirkpatrick, 2016) defines Level
4 as a measurement of the overall outcome of the curriculum, in other words, did the curriculum
itself contribute to reaching the outcome that the organization expected? Organizations
ultimately have only one Level 4 outcome (J. D. Kirkpatrick & Kirkpatrick, 2016, p. 12), and
thus, for higher education curriculum such as this one, to achieve success at Level 4, the
curriculum must support reaching the overall mission of the University which means recognizing
that learning is not just about transmission of knowledge, but is transformative in nature.
Ultimately, to achieve Level 4 success, key stakeholders must recognize the value and positive
impact of the curriculum in supporting the mission of the organization.
Kirkpatrick and Kirkpatrick (2016) define leading indicators as the internal or external
short-term observations and measurements that connect learning and critical behaviors with the
overall organizational outcome. This curriculum has been developed to help support students at
ZYX University with the knowledge and problem-solving capabilities to leverage technological
advances across all aspects of their learning. This curriculum supports the Level 4 vision of ZYX
University to graduate students who are knowledgeable about technology and who are ready to
become leaders in their chosen fields. Table 3 outlines the external and internal leading

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indicators for achieving digital fluency.
Table 3
Indicators, Metrics, and Methods for External and Internal Outcomes
Outcome Metric Method
External outcomes
Being at the forefront of
universities offering digital
fluency skills, meeting
emerging needs
Ranking and/ or number of
positive recognitions
Data collected by
communication office
Improvement in external
rankings
Increased positive comments
from employers
Number of positive
recognitions
Data collected by career services
Increased mention of the
University in the press due
to students’ technological
skills
Number of positive
recognitions
Data collected by
communication office
Increased number of students
enrolling in course from
across the University
Number of students
enrolled
Data collected by registrar’s
office
Increased number of students
minoring in MATCH
programs
Number of students
enrolled
Data collected by advisors
Internal outcomes
Increased positive comments
from other faculty
Number of positive
recognitions
Data collected by advisors or
other office support staff
Increased student use of
technology
Number of digital tools
used in student papers or
projects
Cooperating faculty provide data
Increased students doing
capstone projects or other
innovation and
entrepreneurship projects
with technology
Number of projects Data collected by advisors,
support staff, or other faculty

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Level 3: Behavior
The New World Kirkpatrick Model (J. D. Kirkpatrick & Kirkpatrick, 2016) defines Level
3 as a measurement of how well participants in the instruction apply what they have learned in
future situations. In the field of educational psychology, the practice of applying knowledge to
new situations is known as transfer of learning. Mayer (2011) defines three degrees of transfer:
retention, or the ability to solve the same or similar problems; near transfer, or the ability to
solve new problems by applying the same overarching principle in a new situation; and far
transfer which involves applying a new principle to a new problem and new situation. Helping
learners transfer knowledge across new domains or situations is critical because without it,
learning is “unproductive and inefficient” (Goldstone & Day, 2012, p. 149). As Kirkpatrick and
Kirkpatrick point out, “Level 3 Behavior is the most important level because training alone will
not yield enough organizational results to be viewed as successful” (2016, p. 49). Therefore, it is
of critical importance that the evaluation of this curriculum includes detailed plans for exploring
how learners apply the knowledge, skills, and attitudes taught throughout this course into the rest
of their undergraduate experience and future careers.
Critical Behaviors Required to Perform the Course Outcomes
Critical behaviors are defined in the New World Model as the actions that learners will
consistently perform to achieve the organization’s Level 4 outcomes and involves both
monitoring and seeking to improve performance (J. D. Kirkpatrick & Kirkpatrick, 2016). In the
case of this curriculum, the critical behaviors correspond to the overall five learning goals
presented in Table 1. Critical behaviors (or learning goals) need to be “specific, observable, and
measurable”; in other words, an observer of the learner must be able to capture when and how
the behavior occurs, and if possible, measure the “quality or accuracy of the performed

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behavior,” which may involve defining a measurement threshold (J. D. Kirkpatrick &
Kirkpatrick, 2016, p. 51). See Table 4 includes the critical behaviors for each of the five major
competencies: a) information and data literacy; b) communication and collaboration; c) digital
content creation; d) safety and cybersecurity; and e) problem solving, along with the metrics,
methods, and timing for evaluation for each corresponding critical behavior.
Table 4
Critical Behaviors, Metrics, Methods, and Timing for Evaluation
Critical behavior Metric(s) Method(s) Timing
When using information
and/or data, the learner
will assess and, when
required, explain the
reliability, relevance,
credibility, and biases in
the information and/or
data.
Number of
observations or
self-report
Student surveys
Faculty survey
reports
During the
course and
subsequent
courses
Annual surveys
When learning or working,
the learner interacts,
communicates, and
collaborates with others
effectively in
synchronous and
asynchronous digital
environments and, when
required, can articulate
best practices and
guidelines for
accessibility and
demonstrate common
features of digital tools
for communication and
collaboration.
Number of
observations or
self-report
Student surveys
Faculty
observations or
surveys
During the
course and
subsequent
courses
Annual
surveys
When needing to
demonstrate a concept or
idea, the learner will
Number of
observations or
self-reports
Student surveys During the
course and

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independently create and
publish digital content
(using visual design
principles) or develop a
computer program to
accomplish a task, using
an iterative design
process.
Faculty
observations or
surveys
subsequent
courses
Annual
surveys
When using computing
devices, learner will
implement safety
measures to protect
information and digital
assets by setting strong
passwords, using twofactor authentication,
installing anti-virus
software, and frequently
updating software.
Number of
observations or
self-reports
Student surveys
Faculty
observations or
surveys
Data collected
by IT staff
During the
course and
subsequent
courses
Annual
surveys
Biannual
reports
When learning something
new and/or solving a
problem, the learner will
use a systematic and
organized approach for
gathering and
synthesizing information.
Learners will
demonstrate persistence
and willingness to fail
when approaching novel
problems and use
abstraction and
computational thinking
skills to iterate through
possible solutions to a
problem.
Number of
observations or
self-reports
Student surveys
Faculty
observations or
surveys
During the
course and
subsequent
courses
Annual
surveys
Required Drivers
Level 3 success is critical to achieve the organization’s Level 4 outcomes, and so it is

78
important to develop methods for ensuring that learning goals are met. In the Kirkpatrick New
World Model, these methods are called required drivers which are related to either support or
accountability and are defined as “the processes and systems that reinforce, monitor, encourage,
and reward performance of the critical behaviors” (J. D. Kirkpatrick & Kirkpatrick, 2016, p. 53).
Drivers can take many forms and educators can incorporate both intrinsic and extrinsic
motivators to help learners reach the desired critical behaviors. Kirkpatrick and Kirkpatrick give
numerous examples of support drivers including checklists, self-directed learning, job aids,
reminders, executive modeling, communities of practice, coaching, mentoring, and recognition;
as well as accountability drivers including interviews, observations, self-monitoring, dashboard,
surveys and meetings to touch base (2016, p. 53). Required drivers for this digital fluency
curriculum are outlined in Table 5.
Table 5
Required Drivers to Support Critical Behaviors
Method(s) Timing Critical behaviors supported
Project checklists
Reminders
Online learning resources and
job aids
Reinforcing
Incorporated into each
assignment and project in
the course
Throughout the semester
Throughout the semester
1-5
1-5
1-5
Faculty feedback
Peer mentoring
Encouraging
Throughout the semester
Throughout the semester
1-5
1-5
Recognition
Rewarding
Throughout the semester 1-5
Monitoring

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Self-monitoring through
online software systems
Faculty observation and
progress tracking through
LMS
Checkpoints for longer
projects
Throughout the semester
Throughout the semester
Throughout the semester, as
needed
1-5
1-5
1-5
Organizational Support
In the new Kirkpatrick model ongoing inquiry into the critical behaviors and drivers
supporting achieving those critical behaviors is vital to overall organizational success, which
means that success is dependent not just on what happens during a course or training, but how
learners are subsequently supported in applying their new knowledge and skills (J. D.
Kirkpatrick & Kirkpatrick, 2016). Students, faculty, staff, and administrators alike will all need
to practice being curious, open-minded, persistent, adaptable, and creative and approach
knowledge acquisition and problem solving with a growth mindset and willingness to be a
lifelong learner. For this general education course on digital fluency, this means that leaders
across all departments and schools at ZYX University will need to recognize, support, and
encourage all members of the higher education community to achieve these outcomes and adapt
as AI innovations and new technologies continue to emerge. In the MATCH unit, all faculty will
support learners in subsequent courses to reinforce the critical behaviors from this curriculum
and report back refinements or improvements that may be necessary to ensure student success.
Across ZYX University, support from the Provost’s office is necessary to implement universitywide support and reinforcement of these digital fluency critical behaviors across all general
education courses.

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Level 2: Learning
As defined by Schunk: “Learning is an enduring change in behavior; or in the capacity to
behave in a given fashion, which results from practice or other forms of experience” (2020, p. 3).
Kirkpatrick and Kirkpatrick (2016) elaborate that learning requires the acquisition of five
elements: a) knowledge, b) skills, c) attitude, d) confidence, and e) commitment, which should
be evaluated at the completion of the course. This corresponds to the course learning goals,
which as defined by Smith and Ragan (2005) are the observable actions of what the learner can
accomplish after instruction. As discussed in Part 6, the learning goals, combined with Gagné
outcomes become the terminal learning objectives which are the measurements that demonstrate
Level 2 Learning.
Terminal Learning Objectives
After completion of this digital fluency course, learners will be able to demonstrate the
knowledge, skills, attitude, confidence, and commitment to achieve the following terminal
learning objectives:
1. Given a data set (during class), the learner will be able to explain the reliability,
relevance, credibility, and biases per program guidelines.
2. After selecting a topic to research, the learner will locate relevant and credible
information and explain the reliability, relevance, credibility, and biases in the
information sources chosen per program guidelines.
3. When learning and working on class assignments, the learner interacts, communicates,
and collaborates with others effectively in synchronous and asynchronous digital
environments, according to course rubric.

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4. When required, the learner can articulate best practices and guidelines for accessibility
and demonstrate common features of digital tools for communication and collaboration.
5. When given a task to demonstrate a concept or idea, the learner will independently create
and publish digital content (using visual design principles), according to a course rubric.
6. When given a programming task, the learner will develop a computer program to
accomplish a task, using an iterative design process, according to a course rubric.
7. When using computing devices, learners will implement safety measures to protect
information and digital assets by setting strong passwords, using two-factor
authentication, installing anti-virus software, and frequently updating software, according
to a course rubric.
8. When learning something new and/or solving a problem, the learner will use a systematic
and organized approach for gathering and synthesizing information, according to a course
rubric.
9. When given a task, learners will demonstrate persistence and willingness to fail when
approaching novel problems and use abstraction and computational thinking skills to
iterate through possible solutions to a problem, according to a course rubric.
Components of Learning Evaluation
Kirkpatrick and Kirkpatrick emphasize the importance of being “purposeful and
deliberate” (2016, p. 42) when deciding how to assess Level 2 learning, as evaluation at this
level is often over-done. In general, they indicate that it is best to focus on the minimum
acceptable level necessary to demonstrate that learning outcomes have been met. Given that this
curriculum will be delivered in a formal higher education setting, both formative and summative
evaluation will be implemented throughout the course. Additionally, this type of curriculum will

82
likely benefit from the data collected in a retrospective pre- and post-assessment test, as
participants entering the course may not have enough knowledge to accurately assess their
digital fluency before taking the course, and it is expected that the content and details for the
curriculum will need to be continuously adapted as new technology emerges. Table 6 outlines
the evaluation of each of the five elements of learning for this curriculum.
Table 6
Evaluation of the Components of Learning for the Program
Method(s) or activity(ies) Timing
Declarative knowledge “I know it.”
Checks on learning During class sessions
Knowledge tests During class sessions
Small group discussions of key concepts During class session
Procedural skills “I can do it right now.”
Online activities in LMS During class sessions or as out of class
assignments
Group activities During class sessions
Assignments and projects Outside of class, at the conclusion of
corresponding units
Attitude “I believe this is worthwhile.”
Small group or partner discussions During class sessions
Reflection assignments Outside of class, throughout the semester
Survey At the end of the course
Confidence “I think I can do it on the job.”
Small group or partner discussions During class sessions
Reflection assignments Outside of class, throughout the semester
Survey At the end of the course
Commitment “I will do it on the job.”
Small group or partner discussions During class sessions
Reflection assignments Outside of class, throughout the semester
Survey At the end of the course
Survey During a subsequent semester
Level 1: Reaction
Level 1 evaluation looks at the learners’ reactions to learning, measuring how engaging,
relevant, and satisfying they find the course content (Kirkpatrick & Kirkpatrick, 2016).
Summative evaluations are popular ways to gather Level 1 evaluation data, and ZYX University

83
learners all have an opportunity to provide feedback via a standard end of course student
evaluation form. Additionally, it can be both simple, quick, efficient, and inexpensive to
implement formative Level 1 evaluation throughout a course. Formative evaluations may include
mid-semester surveys, but can also be accomplished by instructor observation, periodic class
pulse-checks, or a dedicated observer focused on class dynamics. Results from these formative
evaluation methods can be used immediately, to modify content or teaching approaches as
needed, to meet instructional needs of the learners. Additionally, this data can help identify
environmental factors which may be negatively impacting learning, allowing remedies to be
found as problems occur. Table 7 provides a summary of the methods, tools, and timing of
assessments to measure the engagement, relevance, and satisfaction of learners in this course.
Table 7
Components to Measure Reactions to the Program
Method(s) or tool(s) Timing
Engagement
Instructor observations During class sessions
Participation and engagement in activities During class sessions
Pulse-checks Periodically throughout the semester
Usage of course resources on LMS Periodically throughout the semester
Survey Mid-semester and end of course
Relevance
Reflection assignments Weekly
Survey Mid-semester and end of course
Customer satisfaction
Pulse-checks Periodically throughout the semester
Observation (by course learning assistants or
other faculty)
Periodically throughout the semester
Survey Mid-semester and end of course
Evaluation Tools
Kirkpatrick and Kirkpatrick (2016) discuss the importance of treating evaluation as an
ongoing process of gathering and analyzing data to continuously improve both current and future

84
learning opportunities. The three most important questions to answer with formative and
summative evaluation are a) is the program meeting expectations, b) if not, why not, c) if so,
why (J. D. Kirkpatrick & Kirkpatrick, 2016, p. 122). Rather than focusing on evaluating one
specific level at a time in a survey, Kirkpatrick and Kirkpatrick recommend using a blended
evaluation approach to avoid survey fatigue (2016). Survey forms should be learner centered, be
clear, unambiguous, and carefully constructed, considering psychological measurement
principles (J. D. Kirkpatrick & Kirkpatrick, 2016). Various formative evaluation methods will
occur throughout the semester. A summative evaluation survey for this curriculum on digital
fluency will be administered twice: once at the conclusion of the course and again approximately
two semesters after the course has concluded.
Immediately Following the Program Implementation
At the end of the semester, a summative evaluation survey will be distributed to
participants. The survey will include various questions to evaluate Level 1 and Level 2
outcomes. Participants will answer three Likert-scale questions to describe their experiences in
the course with numeric ratings. Two open-ended questions are included to gather qualitative
feedback. Additionally, this survey includes ten retrospective pretest questions which are
versatile, convenient, and generally more accurate than traditional pre-post self-assessments
because learners are not always aware of what they don’t know and learners’ frame of reference
for their knowledge level can change as a result of learning (Lee et al., 2015; Stevahn et al.,
2020). The instrument is provided in Appendix D, with each question labeled with the
corresponding evaluation level.

85
Delayed For a Period After the Program Implementation
Approximately two semesters after the completion of the course, another evaluation
survey can be given, which gathers data for all four evaluation levels. This survey included ten
Likert-scale questions and four open-ended questions and is found in Appendix E. This
instrument is designed so that participants are prompted to provide additional information if their
answers indicate that they have not achieved Level 3 behaviors.
Data Analysis and Reporting
As data is gathered, it is important to take the time to analyze the data collected and use
any insights from the data to improve the curriculum (J. D. Kirkpatrick & Kirkpatrick, 2016). As
Kirkpatrick and Kirkpatrick discuss, the process of reporting useful Level 4 data can help
important stakeholders recognize the value of the curriculum (2016). As Tufte (1997, 2013,
2018, 2020) demonstrates in all of his books about the visualization of data, a focus on how to
present data in a fast, efficient, and visually appealing way makes it easier for stakeholders to
understand the meaning of what the data captures. For the evaluation of this curriculum, the data
visualization should clearly show a) if the curriculum is meeting expectations; b) if not, why not;
and c) if so, why (J. D. Kirkpatrick & Kirkpatrick, 2016, p. 122). Figures 4 and 5 below
demonstrate (using fictitious data) samples of how Level 3 and Level 4 data from this curriculum
might be used to communicate key evaluation information to stakeholders. Figure 4 shows two
of the learning outcomes (or critical behaviors) with the percentage of students who indicated
each proficiency level, based on retrospective pretest questions, with bar charts showing the
distribution of change scores. Figure 5 shows a few of the external and internal indicators of
Level 4 evaluation, showing the mean of measurements from before the curriculum was
implemented and three years after the implementation.

86
Figure 4
Sample Data Representation of Retrospective Pre-Post Test Results
Figure 5
Sample Data Representation of Indicators for External and Internal Outcomes

87
Conclusion
This curriculum introduces a new undergraduate overview-level general education course
for digital fluency and critically conscious computing. Throughout the development of this
curriculum, advances in AI continually made headlines, with companies competing to provide
new and better AI tools while promising to enhance human potential. This time is being referred
to as the Fourth Industrial Revolution (McKinsey & Company, 2022), and digital fluency is a
requirement for productive citizenship. With sentiments like “Data is the New Oil” (Talagala,
2022), all college graduates need to be able to manage the influx of technology and data in all
aspects of life. This curriculum addresses these emerging needs, with a focus on lifelong
learning, critically conscious computing (Ko et al., 2023), and on building five competencies of
digital fluency: competency in information and data literacy, enhancing communication and
collaboration skills, demonstrating competency with digital content creation, practicing safety
and cybersecurity, and constructing knowledge, and using problem solving skills. It is again
worth noting that concrete learning goals for this curriculum will be ongoing and constantly and
consistently changing, and stakeholders will need to support instructors and designers with
ongoing innovation using an emergent design philosophy (Brown, 2017), to allow future
adaptation and development of the learning goals and curriculum as technology continues to
change and evolve. All people need to be lifelong thinkers, learners, creators, and innovators in
our increasingly technological world, and through the dynamic approach of this curriculum, it is
expected that undergraduates at ZYX University will build the knowledge, skills, and attitudes
towards technology and computing to be exemplars to follow.

88
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Appendix A: Course Overview
The purpose of this course is to teach undergraduate students how to become digitally
fluent and critically conscious consumers of computing. The major competencies for digital
fluency are:
● Demonstrate competency in information and data literacy
● Enhance communication and collaboration skills
● Demonstrate competency with digital content creation
● Practice safety and cybersecurity
● Construct knowledge and use problem solving skills
To accomplish these learning goals, a fourteen-unit spiral curriculum has been
developed. Figure A1 shows a visual representation of the curriculum. This curriculum will be
delivered as an in-person general education course over the course of a traditional 15-week
semester at ZYX University. General education courses are designed to support learners at ZYX
to become informed citizens who value lifelong learning, which is integral to this curriculum.
Learners are encouraged to challenge themselves and others through critical thinking and
intellectual inquiry.

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Figure A1
Visual Overview of Course Units in Spiral Curriculum
This course will utilize the campus-wide learning management system (LMS) as well
other relevant software tools, some of which may be freely available, others of which may be
accessed through a virtual private network. Instructors will provide additional academic support
in person and/or via video-conferencing software during office hours as well as providing
asynchronous support through email or discussion board forums. Courses within the Modern
Applied Tech and Computing Hub (MATCH) typically include additional support through
tutoring or office hour help from past students working as course learning assistants. By
providing a plethora of options for supporting students, this curriculum is situated within a
learning environment which strives to help all learners succeed.
The course overview will take place during the first day of class, where the students will
be presented with the course syllabus and given an opportunity to discuss expectations and
personal learning goals. Students will be given the opportunity to complete both individual and

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group projects throughout the semester, including a cumulative final project. A summative
evaluation survey with retrospective pretest questions will be administered to all learners at the
conclusion of the system. Table A1 shows the learning activities for the course overview.
Table A1
Learning Activities for the Course Overview
Instructional
sequence
Time
(mins)
Description of the
learning activity
Instructor action
(supplantive)
Learner action
(generative)
Introduction 8 Welcome and
introduction of the
instructional team
(faculty and
learning
assistants).
Include name,
pronouns, and a
brief personal
anecdote
regarding
technology.
Introduce the
instructional team.
Share anecdote(s).
Ask learners to
actively listen.
Course goal 5 Provide the
introduction to the
digital fluency
course. Tell
learners that they
will develop skills
to help them
navigate the everchanging
landscape of
technology and
computing.
Present overall course
goal.
Demonstrate where to
find the course
syllabus.
Ask learners to listen
and ask questions.
Learners should
confirm that they
have access to the
syllabus.
Reasons for
the course
12 This course has
been designed to
help all students
gain the
knowledge, skills,
and attitudes to
become 21st
century thinkers.
Present reasons for
the course and give
an example of a
recent technology
development which
learners may not be
aware of.
Ask learners to reflect
on their current
knowledge and
comfort level with
technology.
Ask learners to
discuss experiences

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Instructional
sequence
Time
(mins)
Description of the
learning activity
Instructor action
(supplantive)
Learner action
(generative)
Benefits of
completing the
course are
learning how to
leverage existing
technologies for
problem solving,
how to think
critically about
information and
data, how to
apply
computational
thinking, and how
to protect
themselves and
their data.
Risks that learners
avoid are
struggles with
emerging
technology and
expectations of
using technology
and
computational
thinking in
coursework.
Invite students to
share stories about
recent successes or
failures with
technology.
and concerns about
the course in small
groups.
Ask small groups to
share a summary of
their discussions
with the whole
class.
Course
overview
25 Introduce the core
competencies and
how those are
woven throughout
the various units.
Preview the units
and the concepts,
topics, or tools
corresponding to
those units.
Review the course
syllabus, the course
overview visual
(Figure A1), the
learning
management
system, and other
course resources.
Ask learners to
review the
syllabus, identify
potential concerns
or questions with
a peer, and ask
the instructor any
clarifying or
follow up
questions.

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Instructional
sequence
Time
(mins)
Description of the
learning activity
Instructor action
(supplantive)
Learner action
(generative)
Preview the eight
assignments and
how each provides
an opportunity to
apply what they
are learning in
class.
Total Time 50

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Appendix B: Lesson Overviews
This section contains the lesson overviews for each of the 14 units of this semester-long
curriculum. The overviews contain the terminal objectives, the prerequisite knowledge or
enabling objectives, and the overview the learning activities. The summative assessment for each
unit of instruction is also described. For instructional components in all the units, it is expected
that lessons will be taught with the aid of slides (PowerPoint or Google Slides) projected on a
screen in the classroom. The slides will also be made available through the learning management
system (LMS) for students to preview ahead of class, annotate during class, or navigate with the
use of assistive technologies. Additionally, all class sessions will be recorded and made available
through the LMS.
Due to the spiral approach used in this curriculum, several units focus on combinations of
terminal learning objectives from the five main core competencies. Additionally, elements of
critically conscious computing (C3) will be woven throughout the majority of the units. In the
following lesson overviews, the following acronyms will be used to indicate the area from which
the terminal objectives and enabling objects (including declarative knowledge, intellectual skills,
cognitive strategies, and attitudes) most closely align.
● Demonstrate competency in information and data literacy (ID)
● Enhance communication and collaboration skills (CC)
● Demonstrate competency with digital content creation (DC)
● Practice safety and cybersecurity (SC)
● Constructing knowledge and using problem solving skills (PS)
● Critically conscious computing (C3)

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Finally, it is worth noting that the specific technologies referred to herein will likely
change on a regular basis, based on recent and new and emerging technologies. The teaching and
facilitation of this course will need to adapt and change through a process of emergent strategy
driven by technological advances. No matter the specific tools and frameworks being taught, the
curriculum will leverage building mastery of all the core competencies throughout the semester
by providing multiple opportunities for part-whole task practice of each competency through the
spiral nature of the curriculum.
Unit 1: Introduction to Learning and Problem Solving
Students enrolled in this general education course are likely to have very different
backgrounds regarding formal instruction of problem solving and using technology. This initial
synchronous in-person unit will serve as a first introduction to how people learn, debunking
some of the common misconceptions, as well as discussing research-based learning strategies.
Learners will share and explore strategies for learning new material, practice finding information
using electronic library resources, and discuss how to use technology to help organize and
synthesize information; all of which will serve as a foundational knowledge for building
competency in constructing knowledge and using problem solving skills.
Terminal Learning Objective (Constructing Knowledge and Using Problem Solving Skills)
During this unit, students will begin to build mastery towards the following terminal
learning objective:
● When learning something new and/or solving a problem, the learner will use a systematic
and organized approach for gathering and synthesizing information, according to a course
rubric.

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Enabling Objectives
● Declarative knowledge
○ Given a list of terms, learners will describe the meaning of and give examples and
nonexamples of the following, per the course materials
■ systematic and organized approach for information gathering
■ Problem-solving can be both domain specific and interdisciplinary
● Intellectual skills
○ Given a problem to be solved, learners will show competency in the following
skills measured by a course rubric:
■ Forming connections between sources of information
■ Articulate the need to critically assess knowledge gaps and seek
opportunities for obtaining and integrating new knowledge construction
■ Using failure as an opportunity to learn and iterate to explore new ideas
and innovations
● Cognitive Strategies
○ In situations dealing with new knowledge acquisition and creative problem
solving, learners will monitor, watch, and guide self-progress record it in their
journal
○ In situations dealing with new knowledge acquisition and creative problem
solving, learners will experiment and fail while learning and record successes and
failures in their journal.
● Attitudes

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○ Learners will choose to be curious, open-minded, persistent, adaptable, and
creative and approach knowledge acquisition and problem solving with a growth
mindset and willingness to be a lifelong learner.
○ Learners will choose to attribute success and failure to their own effort while
continuously building confidence in constructing knowledge and using problem
solving skills.
Learning Activities
● After introductions and attention activities and learning objectives, watch The Learning
Scientist videos on effective learning strategies (n.d.), and assess prior knowledge of
strategies for learning.
● Review necessary prerequisite knowledge by providing definitions and examples and
nonexamples. Allow learners to generate their own examples.
● Model how to use Notion (or other document and database software) as a technology tool
for organizing notes, data, information, and more.
● Provide practice and feedback for setting up Notion as an organized personal
dashboard with tasks, projects, and a digital journal.
● Provide practice and feedback for using Notion to organize course notes for
this digital fluency course.
● Provide opportunities to transfer knowledge and skills of this unit to other
contexts by exploring how individuals and companies use Notion and/or other
software applications as knowledge management systems.
● Teach strategies for gathering, storing, organizing, sharing, and managing
information and provide opportunities to practice those strategies.

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● Discuss and have students reflect upon the importance of experimentation in
both learning and organization of knowledge systems.
● Provide an opportunity for learners to record their progress and self-reflections in their
digital journal.
Summative Assessment
Learners will create a personal dashboard (in Notion) to systematically organize course
materials, project information, tasks, notes, and reflections, according to a rubric.
Unit 2: Introduction to Information Literacy
This unit builds upon topics, knowledge, and skills explored in Unit 1. This synchronous
in-person unit will go into more depth about what it means for information to be relevant,
credible, and free from bias. Learners will continue to practice finding information using
electronic library resources, focusing on finding sources that are relevant, credible, and free from
bias. Additionally, learners will practice using a reference management system to help store,
organize, and synthesize information in an organized way.
Terminal Learning Objective (Demonstrate Competency in Information and Data
Literacy)
During this unit, students will begin to build mastery towards the following terminal
learning objective:
● After selecting a topic to research, the learner will locate relevant and credible
information and explain the reliability, relevance, credibility, and biases in the
information sources chosen per program guidelines.
Enabling Objectives
● Declarative knowledge

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○ Given a list of terms, learners will describe the meaning of and give examples and
nonexamples of the following, per the course materials
■ Concept of information literacy
■ Concept of data and biases
■ Concept of reliability, credibility, and relevance
○ Learners can describe credibility and bias in their own words
● Intellectual skills
○ Given an information source, the learner can identify if it is relevant and credible
information, according to a course rubric.
○ Given information, the learner can explain the reliability, relevance, credibility,
and biases present, according to a course rubric.
● Cognitive Strategies
○ In situations dealing with information, learners will monitor, watch, and guide
self-progress of finding, storing, managing, and organizing information and
record it in their journal.
○ When performing research or data gathering, learners will evaluate effectiveness
of locating good information and data using their journal.
● Attitudes
○ Learners will choose to apply critical thinking when dealing with sources of
information.
Learning Activities
● After introductions and attention activities and learning objectives, assess prior
knowledge of reliability, relevance, credibility, and biases.

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● Review necessary prerequisite knowledge by providing definitions and examples and
nonexamples. Allow learners to generate their own examples and nonexamples.
● Model how to use Google Scholar and link to university library systems.
● Model how to effectively use University library resources to locate reliable, relevant,
credible, and bias-free information (can be done by the instructor or member of library
staff).
● Provide practice and feedback for assessing reliability, relevance, credibility, and biases
in information sources.
● Model how to set up and use Zotero or other Reference Management System (RMS) as a
technology tool for storing and organizing references.
● Provide practice and feedback for using online resources to find relevant information,
and for storing and managing resources that information using RMS.
● Provide an opportunity for learners to record their progress and self-reflections in their
digital journal, with a prompt to consider the importance of applying critical thinking
when evaluating any information source.
Summative Assessment
After selecting an approved topic to research, learners will create an annotated bibliography of
information sources which explains how they assessed the reliability, relevance, credibility, and
biases in each source, per a course rubric.

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Unit 3: Introduction to Digital Content Creation
This unit introduces the topic of digital content creation. Learners will develop a shared
understanding of concepts integral to digital content and practice creating content following best
practice guidelines. Additionally, in following concepts in critically conscious computing,
learners will be introduced to the topic of accessibility of documents and technology tools.
Terminal Learning Objective (Demonstrate Competency with Digital Content Creation)
● When given a task to demonstrate a concept or idea, the learner will independently create
and publish digital content (using visual design principles), according to a course rubric.
Enabling Objectives
● Declarative knowledge
○ Given a list of terms, learners will describe the meaning of and give examples and
nonexamples of the following, per the course materials:
■ Digital content and file formats for content categories.
○ Learners can describe common features of a chosen digital creation platform or
tool for content creation.
● Intellectual skills
○ Given a task, the learner can identify, select, and use the appropriate software
tool(s) for graphic design.
○ Given a task, the learner can integrate text, images, videos, audio, and animations
into digital content, according to a course rubric.
○ Given a task, the learner can apply accessibility requirements into digital content,
according to a course rubric.

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○ Given specifications for creating digital content, the learner can successfully
apply design principles, according to a course rubric.
● Cognitive Strategies
○ In situations involving content creation, the learner will monitor, watch, and
guide self progress for content creation and record it in their journal.
○ In situations involving content creation, the learner will identify areas for
improvement and set goals for growth, and will seek out and reflect on feedback
for improvement using their journal.
● Attitudes
○ Learners will choose to find new opportunities for learning and self-improvement.
Learning Activities
● After introductions and attention activities and learning objectives, assess prior
knowledge of file formats, content creation, visual design principles, and digital
accessibility.
● Review necessary prerequisite knowledge by providing definitions and examples and
nonexamples. Allow learners to generate their own examples and nonexamples.
● Model the procedure for exploring and understanding the features of a digital creation
tool (like Canva).
● Provide practice and feedback for creating a document, flier, or brochure using a content
creation tool (like Canva) and provide opportunities for peer critique of artifacts with a
checklist assessing visual design principles and document accessibility.

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Summative Assessment
At the completion of units 1-3, learners will be assessed on a cumulative project in which
they create a brochure (or website) with multiple media types which effectively uses visual
design principles and accessibility features to communicate information about a chosen topic
area. Information included in the project must be relevant, credible, and free of bias and the final
artifact will include a bibliography with proper references, generated from a RMS.
Unit 4: Introduction to Communication and Collaboration
This unit builds upon ideas explored in the topic of digital content creation but focuses on
collaboration and communication. Learners will discuss the differences between group-work and
teamwork, synchronous and asynchronous work, and how to share and use content legally.
Additionally, learners will continue to develop a shared understanding of the importance of
digital accessibility as a core component of communication.
Terminal Learning Objective (Enhance Communication and Collaboration Skills)
● When learning and working on class assignments, the learner interacts, communicates,
and collaborates with others effectively in synchronous and asynchronous digital
environments, according to course rubric.
● When required, the learner can articulate best practices and guidelines for accessibility
and demonstrate common features of digital tools for communication and collaboration.
Enabling Objectives
● Declarative knowledge
○ Learners will describe the meaning of and give examples and nonexamples of
synchronous versus asynchronous communication, effective communication (1-1

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or 1 to many), collaboration (many to many, fewer than 10), accessibility, sharing
and using content legally, and interaction.
○ Learners can describe common features of several communication and
collaboration tools.
● Intellectual skills
○ Upon generating digital files, learners can organize and share digital files (and
folders) for ease and effectiveness for collaborations with peers and instructors,
according to course guidelines.
○ Given a task, learners can collaborate with others to present information in a
medium appropriate for the intended audience, according to a course rubric.
○ Given a task, learners will share and use digital content legally, according to US
laws.
● Cognitive Strategies
○ In situations where learners are communicating and/or collaborating with others,
they will reflect, monitor, evaluate, and self-regulate their behaviors, ask for and
use feedback to improve skills, and seek new knowledge and strategies to
improve skills, and record it in their journals.
● Attitudes
○ Learners will choose to treat others professionally and with respect.
Learning Activities
● After introductions and attention activities and learning objectives, assess prior
knowledge of synchronous and asynchronous work and how to share and use content
legally.

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● Complete small group, in-class collaborative activity about the difference between group
work and teamwork. Discuss results.
● Review necessary prerequisite knowledge by providing definitions and examples and
nonexamples. Provide opportunities for learners to generate their own examples and
nonexamples.
● Model the procedure for effectively naming and sharing files and folders with Google
Drive or other cloud-based file sharing services.
● Discuss and have students reflect upon the importance of sharing content legally.
● Provide practice and feedback for a jig-saw activity where groups of 3-4 collaborate on a
shared resource and then several groups review and assess the communication
effectiveness of the shared group resources.
Summative Assessment
After selecting a small team to work with, learners will collaborate synchronously and
asynchronously to create and share a small repository of resources about accessibility and
guidelines for legally sharing content.
Unit 5: Introduction to Safety and Cybersecurity
In this unit, learners will begin to explore some of the critical aspects surrounding the
topic of cybersecurity and personal device safety. Students will discuss the “how and why”
surrounding cybersecurity policies enforced by the university. At the conclusion of this unit
students will work collaboratively in small groups to create an infographic around one aspect of
computer safety or cybersecurity.

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Terminal Learning Objective (Practice Safety and Cybersecurity)
● When using computing devices, learners will implement safety measures to protect
information and digital assets by setting strong passwords, using two-factor
authentication, installing anti-virus software, and frequently updating software, according
to a course rubric.
Enabling Objectives
● Declarative knowledge
○ Learners will describe the meaning of attributes of a strong password and
password management and be able to give examples and nonexamples of good
passwords.
○ Learners will describe the meaning of cybersecurity threats including phishing,
malware, social engineering, ransomware, identity theft, and data breaches and be
able to give examples and nonexamples of these topics.
○ Learners will describe the meaning of authentication methods for devices and be
able to give examples of several authentication methods.
○ Learners will describe the importance of the CIA Triad in cybersecurity:
confidentiality (data is restricted from unauthorized access), integrity (ensuring
that data is accurate, reliable, complete, untampered with, and consistent through
its life cycle), and availability (data is accessible to authorized users when
needed).
● Intellectual skills
○ When using any computing devices connected to a network, the learner will
practice high levels of security awareness, following emerging trends. This

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includes identifying, understanding, and evaluating the likelihood of potential
threats; practicing security with browsing, downloading, emails, and regular
software updates; explaining incident response and be ready to take action to
mitigate impact of a cybersecurity incident; using encryption or secure
communication methods to protect sensitive information; and applying steps to
protect data and devices, including anti-virus software and software updates, all
according to a course rubric.
○ Learners will rely on principles from the CIA Triad model to help maintain
personal and organizational information security.
● Cognitive Strategies
○ In situations involving safety and cybersecurity, learners will monitor, watch, and
guide self-progress of knowledge, skills, and behavior and record in their journal.
● Attitudes
○ Learners will choose to be vigilant, responsible, and cautious when using any
computing devices connected to a network.
○ Learners will choose to practice ethical and responsible behavior.
Learning Activities
● After introductions and attention activities and learning objectives, assess prior
knowledge of personal device safety and cybersecurity practices.
● Review necessary prerequisite knowledge by providing definitions and examples and
nonexamples. Provide opportunities for learners to generate their own examples and
nonexamples.

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● Model the procedure for selecting a good password and using password management
tools.
● Provide practice and feedback for setting up and maintaining password management
tools.
● Provide opportunity to transfer knowledge and skills of safety and cybersecurity by
creating an infographic about one aspect of cybersecurity.
Summative Assessment
Learners will combine knowledge, skills, and attitudes from the previous units and work
collaboratively in small teams to create an infographic about one more basic aspect of personal
device safety or cybersecurity practices, following guidelines specified in course rubric.
Unit 6: Introduction to Data Literacy
In this unit, learners will start to explore the intricacies of data, and start to build the
concept of data as an imperfect representation of information. Learners will be introduced to the
concept that data is produced, rather than collected, and as such, is subject to both conscious and
unconscious bias. Learners will start to explore how computer algorithms can magnify biases in
data and learn how to interrogate data sets and how systems use and manipulate data in visible
and invisible ways.
Terminal Learning Objective (Demonstrate Competency in Information and Data
Literacy)
Given a data set (during class), the learner will be able to explain the reliability,
relevance, credibility, and biases per program guidelines.
Enabling Objectives
● Declarative knowledge

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○ Given a list of terms, learners will describe the meaning of and give examples and
nonexamples of the following, per the course materials
■ Concept of data literacy
■ Concept of data and biases
■ Concept of credibility
■ Concept of data types and variables (in programs and databases)
○ Learners can summarize the differences between information and data.
● Intellectual skills
○ Given information, learners can abstract the information in the form of data to be
stored in a computer, with skills measured according to a course rubric.
○ Given a source, learners can accurately classify it as data or information.
○ Given information or data, the learner can explain the reliability, relevance,
credibility, and biases present, according to a course rubric.
○ Given an existing data set, the learner can evaluate and explain biases in data sets,
according to a course rubric.
○ Learner can explain power dynamics that affect data and explain how technology
companies may manipulate data in visible and invisible ways, according to a
course rubric.
● Cognitive Strategies
○ In situations dealing with information or data, learners will monitor, watch, and
guide self-progress of finding, storing, managing, and organizing information and
record it in their journal.

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○ When performing research or data gathering, learners will evaluate effectiveness
of locating good information and data using their journal.
● Attitudes
○ Learners will choose to apply critical thinking when dealing with sources of
information or data.
Learning Activities
● After introductions and attention activities and learning objectives, assess prior
knowledge of data literacy, including biases and understanding of different types of data.
● Review necessary prerequisite knowledge by providing definitions and examples and
nonexamples. Provide opportunities for learners to generate their own examples and
nonexamples.
● Model the procedure to find and interrogate properties of a dataset
● Provide practice and feedback for explaining the reliability, relevance, credibility, and
biases present in a data set.
Summative Assessment
As part of a small team, learners will select a data set from an approved list, and explain their
assessment of the reliability, relevance, credibility, and biases in the data, per a course rubric.
Unit 7: Building Problem Solving with Data Literacy
In this unit, learners will work on building problem solving strategies and skills in
combination with exploring and interrogating data. Learners will experience the challenges
inherent in gathering meaningful data by designing a survey to collect information on a topic
relevant to their communities and explore how choices made when creating the survey
(including question wording, types of questions, and provided options) impact the data collected.

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In doing so, learners will be introduced not only to the concept of abstraction in problem solving,
but also be encouraged to develop a growth mindset and willingness to persist and fail when
faced with challenging problems.
Terminal Learning Objective (Constructing Knowledge and Using Problem Solving Skills
and Demonstrate Competency in Information and Data Literacy)
When given a task, learners will demonstrate persistence and willingness to fail when
approaching novel problems and use abstraction to iterate through possible solutions to a
problem, according to a course rubric.
Enabling Objectives
● Declarative knowledge
○ Given a list of terms, learners will describe the meaning of and give examples and
nonexamples of abstraction for problem solving per the course materials
■ Systematic and organized approach for information gathering
■ Abstract information in the form of data
■ Methods for storing, managing, and organizing data
■ Synthesizing information
■ Problem-solving can be both domain specific and interdisciplinary
■ Abstraction for problem solving
■ Presenting information and data in an accessible manner.
● Intellectual skills
○ Given a problem to be solved, learners will show competency in the following
skills measured by a course rubric:
■ Forming connections between sources of information

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■ Critically assess knowledge gaps and seek opportunities for obtaining and
integrating new knowledge construction
■ Synthesizing information
■ Applying creative thinking spiral as measured by a course rubric
■ Utilizing applicable problem-solving strategies for tasks
● Cognitive Strategies
○ When performing research or data gathering, learners will evaluate effectiveness
of locating good information and data using their journal.
○ In situations dealing with new knowledge acquisition and creative problem
solving, learners will experiment and fail while learning and record successes and
failures in their journal
● Attitudes
○ Learners will choose to apply critical thinking when dealing with sources of data.
○ Learners will choose to attribute success and failure to their own effort while
continuously building confidence in constructing knowledge and using problem
solving skills.
Learning Activities
● After introductions and attention activities and learning objectives, assess prior
knowledge of abstraction and problem-solving strategies.
● Review necessary prerequisite knowledge by providing definitions and examples and
nonexamples. Provide opportunities for learners to generate their own examples and
nonexamples.

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● Model the procedure for creating a systematic and organized approach for information
gathering in creating a survey, including demonstrations of how question choices affect
the types of data collected.
● Provide practice and feedback for creating a survey to gather information, synthesizing
information, and abstracting information into a data set.
● Model the procedure for storing, managing, and organizing data collected.
● Provide practice and feedback for storing, managing, and organizing data.
● Model the procedure for presenting information and data in an accessible format.
● Provide practice and feedback for presenting information and data in an accessible
format.
● Model the creative thinking spiral and problem-solving strategies for understanding and
working with a data set.
● Provide practice and feedback for using the creative thinking spiral and problem-solving
strategies to understand and work with data.
● Provide opportunity to transfer knowledge and skills of problem solving and data literacy
by creating, storing, and exploring information and data collected from a user group.
Summative Assessment
As part of a small team, learners will use abstraction and problem-solving techniques to
gather meaningful data by designing a survey to collect information on a topic relevant to their
communities and explore how choices made when creating the survey impact the data collected.
Learners will present information and data in an accessible format and explain their assessment
of the reliability, relevance, credibility, and biases in the data they collected, per a course rubric.

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Unit 8: Using AI (Content Creation, Communication, Problem Solving, and Cybersecurity)
In this unit, learners will explore the use and ethics of AI, specifically how to accurately
communicate about and with AI, and engage in discussions about the ethics of using and creating
artifacts with AI. Learners will apply and transfer knowledge and skills from the competencies
of content creation, communication, problem-solving, and cybersecurity and synthesize through
a dedicated exploration into the rapidly evolving proliferation of AI tools. Learners will evaluate
new and emerging tools, standards, and guidelines within this space, and use AI tools to create
content, according to a course rubric.
Terminal Learning Objective
When given a task to demonstrate a concept or idea, the learner will independently create and
publish digital content (using visual design principles), according to a course rubric
Enabling Objectives
● Declarative knowledge
○ Given a list of terms, learners will describe the meaning of and give examples and
nonexamples of the following, per the course materials:
■ Tasks solvable by computer programs
■ Artificial intelligence
■ Ethics of using and creating artifacts with AI
○ Learners can describe common features of several digital creation platforms and
tools for content creation
● Intellectual skills
○ Given a task, the learner can integrate text, images, videos, audio, and animations
into digital content, according to a course rubric

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○ Given specifications for creating digital content, the learner can successfully
apply design principles, according to a course rubric
● Cognitive Strategies
○ In situations involving content creation, the learner will identify areas for
improvement and set goals for growth, and will seek out and reflect on feedback
for improvement using their journal.
● Attitudes
○ Learners will choose to pay close attention to details within digital content
creation.
○ Learners will choose opportunities to build confidence in creating and publishing
digital content.
Learning Activities
● After introductions and attention activities and learning objectives, assess prior
knowledge of communicating about and with AI tools
● Review necessary prerequisite knowledge by providing definitions and examples and
nonexamples. Provide opportunities for learners to generate their own examples and
nonexamples.
● Discuss and have students reflect upon the ethics of using and creating artifacts with AI.
● Complete small group, in-class collaborative activity exploring and evaluating new and
emerging AI tools, standards, and guidelines.
● Provide opportunity to transfer knowledge and skills of exploring the uses and limitations
of generative artificial intelligence.

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Summative Assessment
Learners will use AI tools to independently create and publish digital content (using
visual design principles), according to course rubric.
Unit 9: Programming (As Content Creation)
In this unit, learners will explore computer programming as a form of content creation.
Students will explore fundamental concepts of programming, at various levels, according to prior
programming knowledge and experience. At the conclusion of this unit, students will
demonstrate knowledge by executing simple algorithms using a programming language.
Terminal Learning Objective
When given a programming task, the learner will develop a computer program to accomplish a
task, using an iterative design process, according to a course rubric.
Enabling Objectives
● Declarative knowledge
○ Given a list of terms, learners will describe the meaning of and give examples and
nonexamples of the following, per the course materials:
■ Programming instructions
● Nature of computer programs
● Conditionals, loops, functions
● Program input and output
● Flow-charts
● Algorithms
■ Program execution
■ Tasks solvable by computer programs

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■ Iterative design process
● Intellectual skills
○ Given specifications for a programming task, the learner can apply programming
concepts, including algorithm development, input and output, and execution order
of instructions to complete task, according to a course rubric
● Cognitive Strategies
○ In situations involving content creation, the learner will monitor, watch, and guide
self progress for content creation and record it in their journal.
○ In situations involving content creation, the learner will identify areas for
improvement and set goals for growth, and will seek out and reflect on feedback
for improvement using their journal.
● Attitudes
○ Learners will choose to pay close attention to details within digital content
creation.
○ Learners will choose opportunities to build confidence in creating and publishing
digital content.
Learning Activities
● After introductions and attention activities and learning objectives, assess prior
knowledge of programming instructions, program execution, and tasks solvable by
computer programs.
● Review necessary prerequisite knowledge by providing definitions and examples and
nonexamples. Provide opportunities for learners to generate their own examples and
nonexamples.

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● Model the procedure to use a simple programming language (such as Scratch, Snap, or
Strype (Python)) to solve problems.
● Provide practice and feedback for solving simple problems using a programming
language.
● Provide opportunity to transfer knowledge and skills of using programming as content
creation by solving a variety of coding exercises.
Summative Assessment
Students will complete various coding exercises to demonstrate algorithm development,
input and output, and execution order of instructions to complete tasks, according to a course
rubric.
Unit 10: Collaboration and Programming
In this unit, learners will continue learning various programming concepts, but will
leverage collaboration strategies. This unit will explicitly discuss how information is stored,
processed, and manipulated in a computer. Additionally, students will experience the benefits of
pair programming strategies. Learners will work together to continue creating content through
programming, demonstrating algorithm development, input and output, and execution order of
instructions to complete tasks.
Terminal Learning Objective
● When learning and working on class assignments, the learner interacts, communicates,
and collaborates with others effectively in synchronous and asynchronous digital
environments, according to course rubric.
● When given a programming task, the learner will develop a computer program to
accomplish a task, using an iterative design process, according to a course rubric.

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Enabling Objectives
● Declarative knowledge
○ Given a list of terms, learners will describe the meaning of and give examples and
nonexamples of the following, per the course materials:
■ Programming instructions
■ Program execution
■ Tasks solvable by computer programs
■ Iterative design process
■ Pair programming
● Intellectual skills
○ Given specifications for a programming task, the learner can apply programming
concepts, including algorithm development, input and output, and execution order
of instructions to complete task, according to a course rubric
○ Given a task, learners can collaborate with others on a given communication or
collaboration platform and tool to create (accessible) digital content
● Cognitive Strategies
○ In situations where learners are communicating and/or collaborating with others,
they will reflect, monitor, evaluate, and self-regulate their behaviors, ask for and
use feedback to improve skills, and seek new knowledge and strategies to
improve skills, and record it in their journals.
● Attitudes
○ Learners will choose to find new opportunities for learning and self-improvement.
○ Learners will choose to treat others professionally and with respect.

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○ Learners will demonstrate confidence in using collaboration and communication
tools and learning new skills within those tools.
Learning Activities
● After introductions and attention activities and learning objectives, assess prior
knowledge of programming instructions, program execution, and tasks solvable by
computer programs.
● Review necessary prerequisite knowledge by providing definitions and examples and
nonexamples. Provide opportunities for learners to generate their own examples and
nonexamples.
● Model the procedure to use pair programming for solving problems.
● Provide practice and feedback for pair programming activities.
● Provide opportunity to transfer knowledge and skills of using programming as content
creation by solving a variety of coding exercises with a collaborator.
Summative Assessment
Students will work in pairs to complete various coding exercises to demonstrate
algorithm development, input and output, and execution order of instructions to complete tasks,
according to a course rubric.
Unit 11: Programming, Data Science, and AI
In this unit, learners will explore data science concepts through programming and use of
AI tools. Learners will build on the concept of pair programming, but with AI as a partner (Chen
& Liang, 2024; Imai, 2022; Zhou & Li, 2023). Learners will practice problem solving for data
science by using programming concepts and the assistance of specific AI coding tools (Copilot,

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Code Whisperer, or CodeHelp) or through self-exploration of concepts in the book, Learn AIAssisted Python Programming With GitHub Copilot and ChatGPT (Porter & Zingaro, 2024). To
demonstrate their knowledge, students will work in small groups to use AI-assisted
programming to solve a data-science problem.
Terminal Learning Objective
● When learning and working on class assignments, the learner interacts, communicates,
and collaborates with others effectively in synchronous and asynchronous digital
environments, according to course rubric.
● When given a programming task, the learner will develop a computer program to
accomplish a task, using an iterative design process, according to a course rubric.
Enabling Objectives
● Declarative knowledge
○ Given a list of terms, learners will describe the meaning of and give examples and
nonexamples of the following, per the course materials:
■ Iterative design process
■ AI pair programming
● Intellectual skills
○ Given specifications for a programming task, the learner can apply programming
concepts, including algorithm development, input and output, and execution order
of instructions to complete task, according to a course rubric
○ Given a task, learners can collaborate with others on a given communication or
collaboration platform and tool to create (accessible) digital content
● Cognitive Strategies

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○ In situations involving content creation, the learner will identify areas for
improvement and set goals for growth and will seek out and reflect on feedback
for improvement using their journal.
● Attitudes
○ Learners will choose to find new opportunities for learning and self-improvement.
○ Learners will demonstrate confidence in using collaboration and communication
tools and learning new skills within those tools.
Learning Activities
● After introductions and attention activities and learning objectives, assess prior
knowledge of AI pair programming and iterative design process.
● Review necessary prerequisite knowledge by providing definitions and examples and
nonexamples. Provide opportunities for learners to generate their own examples and
nonexamples.
● Model the procedure for using AI for pair programming.
● Provide practice and feedback for using AI for assistance programming.
● Provide opportunity to transfer knowledge and skills of using programming as content
creation by solving a variety of coding exercises with human and AI collaborators.
Summative Assessment
In groups of 2-3, learners will use AI-assisted programming to solve a data-science
problem, according to a course rubric. Students will use abstraction and computational thinking
to solve novel problems in an interdisciplinary manner. They will show that they can work
individually and collaboratively to resolve conceptual problems and propose solutions to
challenging situations.

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Unit 12: Problem Solving in Cybersecurity
In this unit, learners will dive deeper into cybersecurity by exploring emerging
cybersecurity threats and tools for prevention and researching cybersecurity threats resulting
from AI. Learners will be encouraged to apply problem solving techniques while exploring
cybersecurity threats through a global and interdisciplinary lens. Additionally, learners will
consider both ethical issues and issues of cybersecurity responsibility for self and others.
Terminal Learning Objective
● When using computing devices, learners will implement safety measures to protect
information and digital assets, according to a course rubric.
● When given a task, learners will demonstrate persistence and willingness to fail when
approaching novel problems and use abstraction and computational thinking skills to
iterate through possible solutions to a problem, according to a course rubric.
Enabling Objectives
● Declarative knowledge
○ Given a list of terms, learners will describe the meaning of and give examples and
nonexamples of the following, per the course materials:
■ Cybersecurity threats including phishing, malware, social engineering,
ransomware, identity theft, and data breaches
■ Authentication methods for devices
■ Knowledge of NIST cycle of Identify, protect, detect, respond, recover
functions of cybersecurity
■ Measures to protect data and devices, including anti-virus software and
software updates

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○ Learner can summarize a variety of problem-solving strategies such as
brainstorming, critical thinking, decision-making, hypothesis testing, root cause
analysis, and systems thinking
● Intellectual skills
○ When using any computing devices connected to a network, the learner will
practice high levels of security awareness, following emerging trends.
○ Given a problem to be solved, learners will show competency in the following
skills measured by a course rubric:
■ Forming connections between sources of information
■ Critically assess knowledge gaps and seek opportunities for obtaining and
integrating new knowledge construction
■ Synthesizing information
■ Using failure as an opportunity to learn and iterate to explore new ideas
and innovations
■ Applying computational thinking as a process for solving problems
■ Applying creative thinking spiral (experiment, create, imagine, reflect,
share, experiment, create, imagine)
■ Utilizing applicable problem-solving strategies for tasks
● Cognitive Strategies
○ In situations involving safety and cybersecurity, learners will monitor, watch, and
guide self-progress of knowledge, skills, and behavior and record in their journal
○ In situations involving safety and cybersecurity, learners will assess and evaluate
risk awareness and tolerance, and record it in their journals.

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○ In situations dealing with new knowledge acquisition and creative problem
solving, learners will monitor, watch, and guide self-progress record it in their
journal
○ In situations dealing with new knowledge acquisition and creative problem
solving, learners will experiment and fail while learning and record successes and
failures in their journal.
● Attitudes
○ Learners will choose to be vigilant, responsible, and cautious when using any
computing devices connected to a network.
○ Learners will choose to practice ethical and responsible behavior.
○ Learners will choose to advocate for privacy rights and personal data protection.
○ Learners will seek opportunities to continue to develop confidence in applying
steps to protect data and devices, including frequent anti-virus software and
software updates.
○ Learners will choose to be curious, open-minded, persistent, adaptable, and
creative and approach knowledge acquisition and problem solving with a growth
mindset and willingness to be a lifelong learner.
○ Learners will choose to attribute success and failure to their own effort while
continuously building confidence in constructing knowledge and using problem
solving skills.
Learning Activities
● After introductions and attention activities and learning objectives, assess prior
knowledge of emerging cybersecurity threats and problem-solving strategies.

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● Review necessary prerequisite knowledge by providing definitions and examples and
nonexamples. Provide opportunities for learners to generate their own examples and
nonexamples.
● Model the procedure to research cybersecurity threats and critically assess knowledge
gaps and seek opportunities for obtaining and integrating new knowledge construction.
● Provide practice and feedback for researching cybersecurity threats and critically assess
knowledge haps and new knowledge construction.
● Model the procedure to apply creative thinking spiral (experiment, create, imagine,
reflect, share, experiment, create, imagine) for solving complex problems.
● Provide practice and feedback for applying creative thinking spiral and discuss the
connection to NIST Cybersecurity Framework.
● Provide an opportunity to transfer knowledge and skills of problem solving for
cybersecurity threats.
Summative Assessment
Learners will research an emerging cybersecurity threat and apply the creative thinking
spiral and NIST Cybersecurity Framework to suggest possible prevention strategies, according to
a course rubric. In the next unit, learners will use their research to create a public service
announcement to communicate their research efforts.
Unit 13: Creation, Collaboration, and Accessibility
In this unit, learners will communicate results of their research and problem-solving
involving cybersecurity threats by creating a public service announcement on an accessible web
page. This project will focus on accessibility and combine competencies of content creation and

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communication and collaboration. Learners will be assessed on creating an accessible and
inclusive web page, according to a course rubric.
Terminal Learning Objective
● When required, the learner can articulate best practices and guidelines for accessibility
and demonstrate common features of digital tools for communication and collaboration.
Enabling Objectives
● Declarative knowledge
○ Given a list of terms, learners will describe the meaning of and give examples and
nonexamples of the following, per the course materials:
■ Digital content and file formats for content categories
■ Accessibility guidelines for inclusivity
■ WCAG 2.1 standards for accessibility
● Intellectual skills
○ Given a task, learners can collaborate with others on a given communication or
collaboration platform and tool to create accessible digital content following
accessibility standards (WCAG 2.1)
○ Given a task, the learner can identify, select, and use the appropriate software
tool(s) for graphic design, video editing, web content, and programming tasks,
according to a course rubric
○ Given a task, the learner can integrate text, images, videos, audio, and animations
into digital content, according to a course rubric
○ Given specifications for creating digital content, the learner can successfully
apply design principles, according to a course rubric

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● Cognitive Strategies
○ In situations involving content creation, the learner will monitor, watch, and guide
self-progress for content creation and record it in their journal.
○ In situations where learners are communicating and/or collaborating with others,
they will reflect, monitor, evaluate, and self-regulate their behaviors, ask for and
use feedback to improve skills, and seek new knowledge and strategies to
improve skills, and record it in their journals.
● Attitudes
○ Learners will choose to find new opportunities for learning and self-improvement.
○ Learners will choose to treat others professionally and with respect.
○ Learners will demonstrate confidence in using collaboration and communication
tools and learning new skills within those tools.
Learning Activities
● After introductions and attention activities and learning objectives, assess prior
knowledge of accessibility guidelines and WCAG 2.1 standards.
● Review necessary prerequisite knowledge by providing definitions and examples and
nonexamples. Provide opportunities for learners to generate their own examples and
nonexamples.
● Model the procedure to use software tools for creating an accessible web page.
● Provide practice and feedback for creating an accessible web page.
● Provide opportunity to transfer knowledge and skills of accessibility and inclusivity in
content creation.

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Summative Assessment
Learners will create an accessible web page with a public service announcement
communicating their research from Unit 12, according to a course rubric.
Unit 14: Problem Solving in Practice
In this final unit, learners will work together in small groups to demonstrate their
problem-solving capabilities by diving into a problem of practice and create a presentation.
Students will be expected to demonstrate aspects of all digital fluency competencies, according
to a course rubric.
Terminal Learning Objective
Demonstration of all course learning goals:
● When using information and/or data, the learner will assess and, when required, explain
the reliability, relevance, credibility, and biases in the information and/or data.
● When learning or working, the learner interacts, communicates, and collaborates with
others effectively in synchronous and asynchronous digital environments and, when
required, can articulate best practices and guidelines for accessibility and demonstrate
common features of digital tools for communication and collaboration.
● When needing to demonstrate a concept or idea, the learner will independently create and
publish digital content (using visual design principles) or develop a computer program to
accomplish a task, using an iterative design process.
● When using computing devices, the learner will implement safety measures to protect
information and digital assets by setting strong passwords, using two-factor
authentication, installing anti-virus software, and frequently updating software.

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● When learning something new and/or solving a problem, the learner will use a systematic
and organized approach for gathering and synthesizing information. Learners will
demonstrate persistence and willingness to fail when approaching novel problems, and
use abstraction and computational thinking skills to iterate through possible solutions to a
problem.
Learning Activities
● Learners will be given the opportunity to reflect on their progress over the course of the
semester and discuss remaining knowledge gaps concerning any of the competencies.
● During an in-class writing activity, learners will be given a prompt to respond to
considering the importance of lifelong learning in maintaining digital fluency.
● Learners will share components of their lifelong learning reflection with the class and
draw connections between various learner reflections and knowledge, skills, and attitudes
discussed throughout the semester.
● Learners will select an approved topic for their final project presentation and select small
groups to work with, based on topic choice.
● Learners will have dedicated course time to work together on project presentation.
Summative Assessment
In groups of 3-5, learners will demonstrate their problem-solving capabilities by diving
into a problem of practice and create a presentation. Students will be expected to demonstrate
aspects of all digital fluency competencies, according to a course rubric. Presentations will be
delivered during the final exam period for the course.

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Appendix C: Lesson Activities, Design, and Materials
This appendix contains detailed descriptions of two units from this curriculum, Unit 6:
Introduction to Data Literacy and Unit 7: Building Problem Solving with Data Literacy. The
learner characteristic accommodations, notes for a facilitator, and instructional strategy overview
is presented. Then, for each sample unit, the learning objectives are stated, including the terminal
and enabling objectives. The summative assessment is described. The learning activities are
listed in a table format which contains the description of each activity, what the instructor does,
and what the instructor asks the learners to do. Finally, static versions of the learning materials
for each unit are included.
Learner Characteristic Accommodations
First year undergraduate students often need scaffolding to help them focus on longer
term projects. In these two units, as they learn specifics about working with data, students will
need to be reminded and supported as they participate in their first small-team project for the
course. Learners will be encouraged to apply metacognitive strategies to support collaborative
learning. To help support continued engagement with learning, the instructor should give
examples to demonstrate the practicality, usefulness, and real-life application of data literacy.
The lesson materials will be available on the LMS. Finally, principles of universal design for
learning will be applied to materials (in compliance with the Americans with Disabilities Act),
and to ensure all learners have equal learning opportunities.
Facilitator’s Notes
Due to the nature of scheduling at ZYX University, this course could potentially meet
one time a week for three hours and 20 minutes, or two times a week with each class session
meeting for one hour and 40 (or 50) minutes. The unit lecture slides will indicate where a

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session break should take place for a course that meets two times per week. Additionally, when
working with first year undergraduate students, the instructor should be aware of student
identity and potential challenges adjusting to university life. Many students will be
experiencing their first set of college midterms during this unit or the next one, and may need
support with time-management, especially as this unit requires students to work together
outside of class on a project. All lesson plans and materials will be provided on the LMS for
this course and learning activities can be found below.
Instructional Strategies
The instructional strategies for these units are designed with consideration of the
learner, the learning context, and the tasks. As these units serve as an introduction to encoding
information with data, which involves concepts that many learners will not have had prior
experience with, a supplantive strategy of instruction will be favored. A supplantive
instructional strategy will be more efficient, reducing learners’ anxiety and cognitive load
while maximizing potential for learning (Smith & Ragan, 2005; Sweller, 2011). As students
gain more familiarity working with data and move into the topics of Unit 7, the instructional
strategy will shift to a more generative approach, providing less overall scaffolding for the
learners (Smith & Ragan, 2005). During these units, learners will be practicing problem
solving with data and be expected to apply learning strategies and knowledge from previous
units to generate new knowledge, transfer knowledge from prior learning situations, and refine
strategies for learning and working with data (Smith & Ragan, 2005).
Unit 6: Introduction to Data Literacy
This section contains the lesson activities, design, and materials for Unit 6: Introduction
to Data Literacy, which is part of the second iteration through the spiral curriculum focusing on

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the five major core competencies for digital fluency. In this unit, lessons explore the intricacies
of data, building the understanding that data is an imperfect representation of real-world
information. This unit will span over one week of classroom instruction.
Learning Objectives
The terminal learning objective is that given a data set (during class), the learner will be
able to explain the reliability, relevance, credibility, and biases per program guidelines,
demonstrating that students are developing competency in information and data literacy. The
enabling learning objectives are:
● Declarative knowledge
○ Given a list of terms, learners will describe the meaning of and give examples and
nonexamples of the following, per the course materials
■ Concept of data literacy
■ Concept of data and biases
■ Concept of credibility
■ Concept of data types and variables (in programs and databases)
○ Learners can summarize the differences between information and data.
● Intellectual skills
○ Given information, learners can abstract the information in the form of data to be
stored in a computer, with skills measured according to a course rubric.
○ Given a source, learners can accurately classify it as data or information.
○ Given information or data, the learner can explain the reliability, relevance,
credibility, and biases present, according to a course rubric.
○ Given an existing data set, the learner can evaluate and explain biases in data sets,

144
according to a course rubric.
○ Learners can explain power dynamics that affect data and explain how technology
companies may manipulate data in visible and invisible ways, according to a
course rubric.
● Cognitive Strategies
○ In situations dealing with information or data, learners will monitor, watch, and
guide self progress of finding, storing, managing, and organizing information and
record it in their journal.
○ When performing research or data gathering, learners will evaluate effectiveness
of locating good information and data using their journal.
● Attitudes
○ Learners will choose to apply critical thinking when dealing with sources of
information or data.
Summative Assessment
The summative assessment for this unit allows students to work together as part of a
small team to explore data. Teams will select their data set from a provided list (or find their
own according to criteria given on the LMS), and explain their assessment of the reliability,
relevance, credibility, and biases in the data, per a course rubric. Students will start their initial
assessment during class time and will turn in a checkpoint draft of their team report through the
course LMS. The instructor and/or course learning assistants will provide feedback on the draft
report. Teams should incorporate the feedback on their draft during the continuation of this
assessment in Unit 7, after which the full summative assessment will be submitted on the
course LMS.

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Learning Activities Table
The learning activities table reflects the detailed outline of the synchronous class session
for Unit 6. The lesson includes an introduction and overview, opportunities to review prior
relevant knowledge, learning guidance, and opportunities for practice and feedback (Smith &
Ragan, 2005). Additionally, the table includes benefits and risks avoided of the unit, time
allotment for each task, big ideas, and strategies for connecting the material to the next unit.
Each activity indicates the expected amount of time for delivery. All course materials will be
housed on the LMS for this course. Table C1 shows the learning activities for the introduction to
data literacy unit.

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Table C1
Learning Activities for Unit Six: Introduction to Data Literacy
Instructional
sequence
Time Principle from
LD toolkit and
readings
Rationale Instructor action
(supplantive)
Learner action
(generative)
Gain attention 24 mins Capturing and
focusing the
learners’ attention
increases the
potential of
learning (Ambrose
et al., 2010; Mayer,
2011).
Learners need to be
interested and
engaged in the
lesson topic.
Provide each learner with
two index cards. Show
slide 2: gathering
information for a class
census. Say to learners:
jot down who you are,
information describing
yourself and your
characteristics on one of
the index cards.
Show slide 3 with a sample
filled out example and
say to learners: What
characteristics did you
list? Let’s have a few
volunteers share what
they wrote.
Show slide 4 with job
descriptions for each
class role. Say: form
teams of 4, with a
manager, recorder,
reflector, and
Ask learners to write about
themselves on one of the
index cards.
Ask for volunteers to share
a few characteristics with
the class.
Ask learners to form
groups and complete a
summary of team
information gathering.

147
Instructional
sequence
Time Principle from
LD toolkit and
readings
Rationale Instructor action
(supplantive)
Learner action
(generative)
spokesperson and spend
5 minutes completing
information gathering.
Show slide 5 with space for
team’s summaries. Say:
Team reporters, please
fill in up to 6 of the types
or categories that your
team reported. Once
complete, summarize
what has been recorded.
Show slide 6 with sample
images from US Census
surveys. Say: The US
Census is completed
every 10 years. Here are
some sample images
from the US Census
survey, what do you
notice here?
(Still Slide 6). Say: In this
unit we are going to
discuss information and
data, and how data is
always an incomplete
and inaccurate
Ask team reporters to fill
out information on a
shared google slide.
Ask learners to point out
things they notice, which
may include the binary
(male/female) option for
sex, or the more
complicated options for
race.
Ask learners to listen and
think about differences
between information and
data.

148
Instructional
sequence
Time Principle from
LD toolkit and
readings
Rationale Instructor action
(supplantive)
Learner action
(generative)
representation of
information. As we dive
into these topics, please
keep in mind this
exercise and think about
how the way we ask for
information will shape
the type of data that is
collected.
Learning
objectives
1 min Learning and
motivation will be
enhanced if learners
have clear, current
and challenging
goals (Kirschner &
Hendrick, 2020).
Focus attention on
what will be
accomplished.
Show slide 7. State the
overall learning objective
for this unit. Tell the
students that by the end
of this unit, they should
be able to articulate the
difference between
information and data,
and given a data set
(during class), the learner
will be able to explain
the reliability, relevance,
credibility, and biases
present.
Ask the learners to listen to
the objective and ask if
anyone has any
questions.
Reasons for
Learning
Benefits
3 mins Learning and
motivation are
enhanced if the
learner values the
There is utility
value to the task
since it relates to
an activity
Show slide 8. Describe the
benefits: informed
decision making,
effective communication,
Ask learners if they can
think of additional
examples from their own
experiences.

149
Instructional
sequence
Time Principle from
LD toolkit and
readings
Rationale Instructor action
(supplantive)
Learner action
(generative)
Risks Avoided
task (Ambrose et
al., 2010;
Anderman, 2020;
Mayer, 2011).
situated in
everyday life
(Pekrun, 2014).
bias awareness, ethical
considerations, improved
problem solving, and
maintaining integrity.
Show slide 9. Describe the
risks avoided:
misinterpretation, loss of
trust, legal or regulatory
issues, damaging
reputation (personal or
organizational),
ineffective resource
allocation, missed
opportunities, and ethical
lapses.
Overview: 6 mins The learners’ prior
knowledge can help
or hinder learning
(Ausubel, 1968).
Learning and
motivation will be
enhanced if learners
have clear, current
and challenging
goals (Kirschner &
Hendrick, 2020).
Advance organizers
support learners
in making
connections from
previous content
or experiences.
Reminding learners
of pre-existing
skills promotes
retention of new
material.
Show slide 10. Share the
lesson overview. Say:
We have made one loop
through the core
competencies of digital
fluency. By now, you
have started to build an
understanding of how to
assess the reliability,
relevance, credibility,
and bias of information
sources. You have a
Ask learners to listen as the
instructor shares the
agenda of the upcoming
lesson.

150
Instructional
sequence
Time Principle from
LD toolkit and
readings
Rationale Instructor action
(supplantive)
Learner action
(generative)
familiarity with
computer hardware and
how computers store
information and in the
form of 0’s and 1’s and
run applications.
Say: In this unit, we will
start to apply that to your
understanding of data.
We will discuss how data
and information are
related, but also explore
some key differences
between the two. We will
explore definitions of
data literacy. Through
this unit and the next, we
will start to explore the
representation of
information in data and
explore through a
critically conscious
computing lens how the
abstraction of
information in the form
of data can magnify
(intentionally or
unintentionally) biases.
Ask, anything else before
we get started?

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Instructional
sequence
Time Principle from
LD toolkit and
readings
Rationale Instructor action
(supplantive)
Learner action
(generative)
We will talk about types
of data and the
affordances allowed by
different data types while
exploring these topics in
a hands-on manner using
various software tools
(getting practice and
feedback using either
spreadsheets or (maybe)
a dedicated data
exploration tool like
Tableau). This
knowledge will help you
as you continue to build
digital fluency through
the main competencies.
Show slide 11 and have
students share examples
and non-examples of
terminology (activating
prior knowledge)
If needed, show slide 12
and remind students of
the discussion about
these topics from Unit 2.
Ask learners to provide
real-world examples of
reliability, relevance,
credibility, and bias of
information sources.
Ask learners to review
notes.

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Instructional
sequence
Time Principle from
LD toolkit and
readings
Rationale Instructor action
(supplantive)
Learner action
(generative)
Say: The reality that we
will be dealing with is a
bit more nuanced than
these definitions, but
they serve as a good
starting point for our
discussions. Please
review notes from Unit 2
if you don’t remember
assessing information
sources for reliability,
relevance, credibility,
and biases.
Assess
prerequisite
knowledge
(Declarative
knowledge,
concepts,
processes,
principles)
Enabling
objectives
assessment
17 mins The learners’ prior
knowledge can help
or hinder learning
(Kirschner &
Hendrick, 2020).
Learners need to
understand the
lecture and
demonstration.
Show slide 13 and direct
students to describe the
meaning of and share
examples and nonexamples of data, data
literacy, credibility, and
biases.
Assess declarative
knowledge. Say to
students: please write
down in your notes what
you currently feel is the
difference between
information and data.
Ask learners to describe the
meaning of and provide
examples of data, data
literacy, credibility, and
biases.
Ask learners to describe
their current level of
understanding of the
difference between
information and data.

153
Instructional
sequence
Time Principle from
LD toolkit and
readings
Rationale Instructor action
(supplantive)
Learner action
(generative)
Show slide 14, direct
students to discuss
concepts of data and data
literacy explored in the
videos assigned for
homework. Summarize
main points explored by
class on a whiteboard or
digital shared document.
Ask learners to recall
pertinent details about
data and data literacy
from the videos they
watched prior to class.
Short Break 6 mins Learning is enhanced
when the learners’
working memory
capacity is not
overloaded
(Ambrose et al.,
2010; Mayer,
2011).
Avoid cognitive
overload.
After break, show slide 16
and remind students of
where they can access
the summary notes from
class discussion of data
and data literacy.
Demonstrate
Procedures
(“how to”)
CTA
(Procedural
knowledge)
40 mins Modeling learning
improves student
achievement. and
motivation will be
enhanced if learners
have clear, current
and challenging
goals (Kirschner &
Hendrick, 2020).
Students will learn
better by
watching a model
demonstrate the
steps to
accomplish the
task (Bandura,
2012).
Show slide 17.
Demonstrate how to
create a survey using
Google Forms (for an
advanced option, could
consider demonstrating
Qualtrics).
Ask learners to follow
along with each step of
the demonstration of
creating an online survey
form.

154
Instructional
sequence
Time Principle from
LD toolkit and
readings
Rationale Instructor action
(supplantive)
Learner action
(generative)
Problem-solving
takes place in a
mental map or
problem space in
which learners
are moving from
a current state to
the goal state
(Kirschner &
Hendrick, 2020).
Discuss the question types
supported by the
software, as well as
response validation
options.
Show slide 18.
Demonstrate how to
review results in
spreadsheet or CSV
format. Discuss various
data types and how
different types are
supported in spreadsheet
software. Demonstrate
data validation and
simple data cleaning
mechanisms.
Ask probing questions of
learners about their
expectations around
question types and kinds
of answers they expect to
receive from participants
of the survey. Ask
learners to explain
benefits and risks of
using or not using
response validation.
After the demonstration
is complete, have
learners complete the
form with their data.
Ask learners to follow
along with the
demonstration and
encourage them to ask
questions.

155
Instructional
sequence
Time Principle from
LD toolkit and
readings
Rationale Instructor action
(supplantive)
Learner action
(generative)
Provide practice
and feedback
in authentic
conditions
90 mins Learning and
motivation are
enhanced when
learners have
positive
expectations for
success (Eccles &
Wigfield, 2020).
Learning is enhanced
when the learners’
working memory
capacity is not
overloaded
(Kirschner &
Hendrick, 2020).
Providing hands-on
practice with
scaffolding and
clear but simple
steps will
enhance selfefficacy and
decrease
cognitive load.
Students will
develop selfefficacy by
performing a
modeled behavior
(Schunk, 2020).
Show slide 21. Provide
learners with the
opportunity to create
their own survey for data
collection. Provide
students with a case
study scenario for data
collection. Say: form
teams of 4, with a
manager, recorder,
reflector, and
spokesperson and spend
15 minutes designing a
form to collect
information in the form
of data.
Show slide 22. Provide
feedback on data
collection surveys.
Show slide 23. Provide
learners with the
opportunity to revise
survey based on
feedback
Ask learners to apply data
collection strategies to a
case study.
Ask each group to share a
link to their data
collection survey. Ask
participants to help
critique surveys.
Ask learners to work with
their team to revise
surveys.

156
Instructional
sequence
Time Principle from
LD toolkit and
readings
Rationale Instructor action
(supplantive)
Learner action
(generative)
Show slide 24. Play video
called The Best Stats
You’ve Ever Seen by
Hans Rosling.
Show slide 25. Provide
students with a quick
overview of the US
census infographic and
visualization about race
and ask them to discuss
how racial information
has changed over time,
and how throughout all
that, the recorded data is
imperfect.
Ask learners to watch video
and notice the data
visualizations and data
disaggregation used in
video.
Ask learners to explore and
discuss the data set and
tie it to their reading
from Chapter 7 in
Critically Conscious
Computing.
Authentic
assessment
(Counted
above)
Learning and
motivation are
enhanced when
learners are given
the opportunity to
apply what they
have learned in
varying contexts
(Ambrose et al.,
Students need to
identify when
they are not
applying the
methods correctly
and then adjust
their method as a
form of selfregulation and
mastery goals.
Note: authentic assessment
comes as part of slide 23
when students are
refining surveys.
Examine student progress
at each of the steps
before proceeding to the
next.
Learners are practicing
assessment as they revise
their surveys as part of
slide 23.

157
Instructional
sequence
Time Principle from
LD toolkit and
readings
Rationale Instructor action
(supplantive)
Learner action
(generative)
2010; Mayer,
2011).
Provide praise and
encouragement.
Retention and
Transfer
2 mins Learning and
motivation are
enhanced when
learners are given
the opportunity to
apply what they
have learned in
varying contexts
(Mayer, 2011).
Ensure that learners
are reflecting and
finding meaning
in the material
being learned.
Show slide 26. Remind
students to record
reflections in their
journals.
Ask students to document
in their journal their
reflections about dealing
with data.
Advance
organizer for
the next unit
1 min Learning and
motivation are
enhanced if the
learner values the
task (Wigfield &
Eccles, 2000).
This helps learners
to position this
unit as a
preparation for
the next.
Show slide 27. Say: In the
next unit we will
continue to build data
literacy while working
on building greater
problem-solving
competency.
Ask the learners to
remember to complete
their out of class
readings so that they will
be ready to build more
knowledge and skills
next week in class.
Total Time 190
minutes

158
Lesson Materials
• Reflective Journal
• Read before class
1. Critically Conscious Computing Chapter 7, Encoding Information
https://criticallyconsciouscomputing.org/information
• Videos to view before class
1. Why everyone should be data literate by Jordan Morrow. TEDxBoise (12 minutes)
https://www.youtube.com/watch?v=8ovyQZ_Z8Xs
Key points from video:
○ Making data-informed decisions - data literacy in the fourth industrial
revolution - living in a digital world.
○ Refrigerator with digital touch screen and can play you-tube. Dishwasher,
showers, etc. – everything is being connected and produces data and
information. “Data as the new oil.”
○ Data literacy is the ability to read, word with, analyze, and argue with data.
(not data science - you need to be comfortable with data)
■ Read data: to look at something and comprehend it
■ Work with data - be comfortable with information that is presented to
us
■ Analyze data - move beyond observation and get to the insight - to
make a smarter decision. Get comfortable asking questions.
■ Argue with data - interrogate the information presented to you, ability
to put a position forward and back it up with information and data

159
○ To start - 2 C’s of data literacy: Be curious and ask questions of everything.
Creativity - our minds are the most powerful computers out there.
2. What is data literacy? From 365 Data Science Tutorials (approximately 9 minutes)
https://www.youtube.com/watch?v=NvaiQvpjGXk
Key points from video:
○ Data consumers need to be data literate:
■ Articulate a problem that can be solved using data.
■ Understand the data sources used.
■ Check the adequacy and fitness of data involved.
■ Interpret the results of an analysis and extract insights.
■ Make decisions based on the insights.
■ Explain the business value generated with a use case.
○ Communication and information seeking (asking the right questions).
Important questions:
■ How do we store data?
■ Which are the systems we use to do that?
■ Are the data complete and clean enough to support a decision?
■ What are the main characteristics of a data set?
■ What methodology is applied to analyze the data?
■ How reliable is the result of an analysis or forecast?
○ Data sources mentioned:
■ Consumers’ data (website clicks, app registrations, number of mobile
devices, physical store visits)

160
■ Patients’ data
■ Video data
■ Drivers’ data
○ Benefits of data literacy:
■ Improve customer understanding
■ Contribute to faster decision making
■ Enhance the accuracy of predictions
■ Help in process optimization
■ Reduce risks and costs
■ Boost productivity
3. Data Literacy and How Bias Gets in the Way of Decisions Within Organizations,
with Kevin Hanegan By Human Capital Innovations Podcast (25 min)
https://www.youtube.com/watch?v=1YvJn9_gNwI
Key points from video:
○ How to better leverage data to mitigate biases that we have
○ Data is not just numbers -Amazon reviews are also data. Data literacy is the
ability to read, work with, communicate, and challenge data. (Challenge =
critical thinking and common sense with data)
○ Data is objective - black and white. Data literacy is finding the story behind
the data. Finding the context, uncovering biases. Critical thinking with data to
make better decisions.
○ Some people don’t challenge data and associate the data as fact. Not being
malicious, but data can often be skewed and biased.

161
○ Correlation is not causation. Silly things that happen. Ice cream and shark
attacks. Eating hamburgers reduced risk of dying of cancer. Not knowing
what you don’t know. Ask better questions to understand data and make
decisions.
○ How brain works - understand why people do the things that they do - our
brain makes shortcuts - we try to make connections (seeing things once we
know about them). Different brain experiences can lead to different
connections – need to challenge assumptions and biases (implicit,
unconscious biases.) Surround yourself with others with different experiences.
Practice mindfulness and self-reflection to shrink biases (various types -
confirmation bias, motivated reasoning)
○ Diverse perspectives are needed to explore data (TEAMWORK!). Avoid
groupthink.
○ Follow scientific method - listen to both sides. Look for information to
disprove hypotheses.
○ Turning data to wisdom - data has a story. What is the question? What is the
decision? Ask the right question to frame the data.
○ You don’t have to do the analytics or statistical analysis to use data literacy to
keep biases in check.
4. (Optional) What tech companies know about your kids by Veronica Barassi. From
TEDxMileHigh, November 2019 (approximately 11 minutes)
https://www.ted.com/talks/veronica_barassi_what_tech_companies_know_about_you

162
r_kids
Key points from video:
○ Every day we agree to terms and conditions
○ Tracking data of children from the moment of conception and throughout
their lives
○ Turning data into profit - sharing of data from apps. Tracked by devices in
home, at school, at doctor offices, toys, etc. Individuals tracked and profiled
and sold to data brokers. Can we trust these technologies? We can’t rely on AI
and predictive analytics to objectively profile humans and make decisions
about individual lives - our data traces are not a mirror of who we are as
humans.
○ Technologies are ALWAYS biased. Rules/steps in algorithms are not
objective, they are biased algorithms, and biased databases - “dirty data”.
○ Data rights are human rights. Algorithmic discrimination and error - can affect
our children’s futures. Demand data justice.
5. (Optional) The birth of a word - Deb Roy. From TED-Ed: (20 minutes)
https://www.youtube.com/watch?v=eeYkGsWtUVY
Key points from video:
○ Imagine recording your life and discover patterns in life.
○ Home video (bird-eye view) of entire house. 3 years (8-10 hours each day),
90,000 hrs video, 140,000 hrs audio, 200 terabytes of data

163
○ Natural longitudinal data. Privacy provisions in place - team at MIT to look at
data. Looking at speech acquisition of son, transcribed over seven million
words that son encountered in his environment.
○ Time-lapse sound analysis of acquisition of the word “water.” Created a map
of every word learned (503 words, in chronological order) by second birthday.
○ Feedback loops in learning - scaffolding - speech and visual context of
learning language. (Ultimate memory machine - tracking movements in house
and then looking at interactions of when words are heard and how language is
learned – making wordscapes of words)
○ Language
connects to events which provide common ground for language can be
applied to other areas as well - example looking at TV signals and looking at
social media feeds and seeing the landscape of how people are engaging in
discussion about tv shows.
○ “As world becomes increasingly “instrumented” and we have capabilities to
collect and connect dots between what people are saying and the content
they’re saying in it, what is emerging is an ability to see new social structures
and dynamics that have previously not been seen.” Seeing behavior around
communication.
• Unit 6 slides (link)

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Unit 7: Building problem solving with data literacy
This unit focuses on two competencies: constructing knowledge and using problem
solving skills and demonstrating competency in information and data literacy. The terminal
learning objective is that given a task, learners will demonstrate persistence and willingness to
fail when approaching novel problems and use abstraction to iterate through possible solutions
to a problem, according to a course rubric. The enabling learning objectives are:
● Declarative knowledge
○ Given a list of terms, learners will describe the meaning of and give examples and
nonexamples of abstraction for problem solving per the course materials
■ Systematic and organized approach for information gathering
■ Abstract information in the form of data
■ Methods for storing, managing, and organizing data
■ Synthesizing information
■ Problem-solving can be both domain specific and interdisciplinary
■ Abstraction for problem solving
■ Presenting information and data in an accessible manner.
● Intellectual skills
○ Given a problem to be solved, learners will show competency in the following
skills measured by a course rubric:
■ Forming connections between sources of information
■ Critically assess knowledge gaps and seek opportunities for obtaining and
integrating new knowledge construction
■ Synthesizing information

193
■ Applying creative thinking spiral as measured by a course rubric
■ Utilizing applicable problem-solving strategies for tasks
● Cognitive Strategies
○ When performing research or data gathering, learners will evaluate effectiveness
of locating good information and data using their journal.
○ In situations dealing with new knowledge acquisition and creative problem
solving, learners will experiment and fail while learning and record successes and
failures in their journal
● Attitudes
○ Learners will choose to apply critical thinking when dealing with sources of data.
○ Learners will choose to attribute success and failure to their own effort while
continuously building confidence in constructing knowledge and using problem
solving skills.
Summative Assessment
The summative assessment for this unit allows students to continue to work with their
small teams from Unit 6. As part of this team, learners will use abstraction and problemsolving techniques to gather meaningful data by designing a survey to collect information on a
topic relevant to their communities and explore how choices made when creating the survey
impact the data collected. Additionally, learners will leverage one or more existing data sets to
practice synthesizing information and forming connections between sources of information.
Learners will present information and data in an accessible format and explain their assessment
of the reliability, relevance, credibility, and biases in the data they collected, per a course
rubric. Students will submit a pdf of their survey, as well as a detailed report of information

194
and data abstraction and data exploration results by the start of the next week on the course
LMS.
Learning Activities Table
The learning activities table reflects the detailed outline of the synchronous class session
for Unit 7. The lesson includes an introduction and overview, opportunities to review prior
relevant knowledge, learning guidance, and opportunities for practice and feedback (Smith &
Ragan, 2005). Additionally, the table includes benefits and risks avoided of the unit, time
allotment for each task, big ideas, and strategies for connecting the material to the next unit.
Each activity indicates the expected amount of time for delivery. All course materials will be
housed on the LMS for this course. Table C2 shows the learning activities for the introduction to
data literacy unit.

195
Table C2
Learning Activities for Unit Seven: Building Problem Solving with Data Literacy
Instructional
sequence
Time Principle from
LD toolkit and
readings
Rationale Instructor action
(supplantive)
Learner action
(generative)
Gain attention 5 mins Capturing and
focusing the
learners’ attention
increases the
potential of
learning (Ambrose
et al., 2010; Mayer,
2011).
Learners need to be
interested and
engaged in the
lesson topic.
Provide prompt to the
learners by asking them
to discuss differences
between data and big
data.
Ask the learners to provide
examples of data and big
data and try to highlight
differences that they
currently know about.
Learning
objectives
1 min Learning and
motivation will be
enhanced if learners
have clear, current
and challenging
goals (Kirschner &
Hendrick, 2020).
Focus attention on
what will be
accomplished.
State the overall learning
objective for this unit.
Tell the students that by
the end of this unit, they
should be able to
demonstrate persistence
and willingness to fail
when approaching novel
problems, and use
abstraction to iterate
through possible
solutions to a problem
Ask the learners to listen to
the objective and ask if
anyone has any
questions.

196
Instructional
sequence
Time Principle from
LD toolkit and
readings
Rationale Instructor action
(supplantive)
Learner action
(generative)
Reasons for
Learning
Benefits
Risks Avoided
3 mins Learning and
motivation are
enhanced if the
learner values the
task (Ambrose et
al., 2010;
Anderman, 2020;
Mayer, 2011).
There is utility
value to the task
since it relates to
an activity
situated in
everyday life
(Pekrun, 2014).
Show slide 4. Describe the
benefits: resilience to
navigate challenges,
opportunities for learning
and growth, innovation
through experimentation
and risk taking,
efficiency identifying
viable solutions, and
adaptability.
Show slide 5. Describe the
risks avoided: stagnation,
missing learning
opportunities, ineffective
problem-solving, risk
aversion, limited
adaptability, and
diminished innovation.
Ask learners if they can
think of additional
examples from their own
experiences.
Ask learners if they can
think of additional
examples from their own
experiences.
Overview 4 mins The learners’ prior
knowledge can help
or hinder learning
(Ausubel, 1968).
Learning and
motivation will be
enhanced if learners
have clear, current
Advance organizers
support learners
in making
connections from
previous content
or experiences.
Reminding learners
of pre-existing
Show slide 6. Share the
lesson overview. Say:
Now that we have started
to develop competency
in information and data
literacy by exploring the
differences between
information and data,
practicing the skill of
Ask learners to listen as
the instructor shares the
agenda of the upcoming
lesson.
Ask, anything else before
we get started?

197
Instructional
sequence
Time Principle from
LD toolkit and
readings
Rationale Instructor action
(supplantive)
Learner action
(generative)
and challenging
goals (Kirschner &
Hendrick, 2020).
skills promotes
retention of new
material.
using forms to collect
data, reviewing data in
CSV format, and
exploring data sets; we
are now going to start
focusing on building
problem-solving skills
using data analysis and
data-driven decision
making. As we explore
the skills of synthesizing
and abstracting
information, iterating
through possible
solutions, and general
problem solving; we will
also talk about important
attitudes for learning,
including demonstrating
persistence and
willingness to fail. These
knowledge, skills, and
attitudes will help
continue to build your
sense of digital fluency.
Show slide 7. Direct
students to share
Ask learners to provide
examples of differences
between information and

198
Instructional
sequence
Time Principle from
LD toolkit and
readings
Rationale Instructor action
(supplantive)
Learner action
(generative)
examples and nonexamples of terminology.
data, data collection, and
data exploration.
Assess
prerequisite
knowledge
(Declarative
knowledge,
concepts,
processes,
principles)
Enabling
objectives
assessment
36 mins The learners’ prior
knowledge can help
or hinder learning
(Kirschner &
Hendrick, 2020).
Learners need to
understand the
lecture and
demonstration.
Show slide 8. Say: In the
readings that you did for
homework, you came
across various ideas
about managing,
organizing, and
synthesizing information
and data for problem
solving. For each of the
following, let’s share a
quick example and nonexample: Systematic and
organized approach for
information gathering.
Abstract information in
the form of data.
Methods for storing,
managing, and
organizing data.
Synthesizing
information. Problemsolving can be both
domain specific and
interdisciplinary.
Abstraction for problem
solving. Presenting
Direct students to share
examples of when they
have or have not used
these problem solving
strategies.

199
Instructional
sequence
Time Principle from
LD toolkit and
readings
Rationale Instructor action
(supplantive)
Learner action
(generative)
information and data in
an accessible manner.
Assess declarative
knowledge, which will
likely require reviewing
and highlighting aspects
of assigned course
reading.
Show slide 9, direct
students to discuss
concepts of abstraction in
problem solving
explored in the readings
assigned for homework.
Summarize main points
explored by class on a
whiteboard or digital
shared document.
Show slide 10, direct
students to discuss
concepts of abstraction in
problem solving
explored in the videos
assigned for homework.
Summarize main points
explored by class on a
Ask learners to recall
pertinent details about
abstraction and problem
solving from the
readings they completed
prior to class.
Ask learners to recall
pertinent details about
abstraction and problem
solving from the videos
they watched prior to
class.

200
Instructional
sequence
Time Principle from
LD toolkit and
readings
Rationale Instructor action
(supplantive)
Learner action
(generative)
whiteboard or digital
shared document.
Short Break 6 mins Learning is enhanced
when the learners’
working memory
capacity is not
overloaded
(Ambrose et al.,
2010; Mayer,
2011).
Avoid cognitive
overload.
Learning
Guidance
Case Studies
40 mins Creating masteryorientation
enhances learning
and motivation
(Ambrose et al.,
2010; Mayer,
2011).
Make it safe to take
risks.
Show slide 13, Case
Studies on
Understanding How
Persistence and
Willingness to Fail Can
Lead to Success
(OpenAI, 2024). Present
overview of famous
failures in data analysis
or data-driven decisionmaking. Ask learners to
form POGIL teams of 4
to explore one of these
options, or another
failure of their choice) in
data analysis or dataAsk learners to choose a
case study from the
options presented or find
their own example of a
failure. In small teams,
learners should focus on
what happened and how
persistence and a
willingness to fail led to
eventual success. Each
team will present to the
class and can put quick
notes or a link to an
example in the next
slide.

201
Instructional
sequence
Time Principle from
LD toolkit and
readings
Rationale Instructor action
(supplantive)
Learner action
(generative)
driven decision-making.
While exploring the case,
teams should focus on
what happened and on
explaining how
persistence and a
willingness to fail led to
eventual success.
Show slide 14. Have each
team present their
findings.
Show slide 15. Facilitate a
discussion on the
importance of
perseverance and
learning from failures.
Each team will present
findings from their case
study with a focus on
what happened and how
persistence and a
willingness to fail led to
eventual success.
Engage students in a
reflective exercise where
they share personal
experiences of facing
challenges or failures
and how they overcame
them.
Short Break 5 mins Learning is enhanced
when the learners’
working memory
capacity is not
Avoid cognitive
overload.

202
Instructional
sequence
Time Principle from
LD toolkit and
readings
Rationale Instructor action
(supplantive)
Learner action
(generative)
overloaded
(Ambrose et al.,
2010; Mayer,
2011).
Demonstrate
Procedures
(“how to”)
CTA
(Procedural
knowledge)
30 mins Modeling learning
improves student
achievement. and
motivation will be
enhanced if learners
have clear, current
and challenging
goals (Kirschner &
Hendrick, 2020).
Students will learn
better by
watching a model
demonstrate the
steps to
accomplish the
task (Bandura,
2012).
Problem-solving
takes place in a
mental map or
problem space in
which learners
are moving from
a current state to
the goal state
(Kirschner &
Hendrick, 2020,
Mollick, 2024).
Show slide 17. Present a
dataset. Tell the students
the goal of what we want
to learn from the dataset.
Demonstrate how to use
abstraction to break
down the problem into
smaller, more
manageable tasks.
Show slide 18. Guide
students through an
iterative problem-solving
process, emphasizing the
importance of testing and
refining solutions
through multiple
iterations.
Ask learners to follow
along with the
demonstration. Consider
having students help
choose a dataset to use
for the example.
Tell students that they can
practice these steps to
help hone their data
literacy skills and
develop a deeper
understanding of how to
approach complex
problems in data-driven
environments.
Provide practice
and feedback
45 mins Learning and
motivation are
enhanced when
Providing hands-on
practice with
scaffolding and
Show slide 19. Provide
learners with the
opportunity to practice
Review your feedback
from Unit 6 and choose
an area of exploration to

203
Instructional
sequence
Time Principle from
LD toolkit and
readings
Rationale Instructor action
(supplantive)
Learner action
(generative)
in authentic
conditions
learners have
positive
expectations for
success.(Eccles &
Wigfield, 2020)
Learning is enhanced
when the learners’
working memory
capacity is not
overloaded.
(Kirschner &
Hendrick, 2020)
clear but simple
steps will
enhance selfefficacy and
decrease
cognitive load.
Students will
develop selfefficacy by
performing a
modeled
behavior.
(Schunk, 2020)
abstraction and problemsolving. Provide student
teams with data sets.
Say: form teams of 4,
with a manager, recorder,
reflector, and
spokesperson and apply
the concepts of
persistence, willingness
to fail, and abstraction to
tackle the assigned task.
As learners work together
in teams, provide
feedback.
combine with your data
collection from Unit 6.
Practice the knowledge
and skills from Unit 7 to
practice: persistence and
willingness to fail,
synthesizing information,
abstraction, iterative
problem-solving, data
visualization, and
statistical analysis using
the tools we explored in
this unit.
Authentic
assessment
12 mins Learning and
motivation are
enhanced when
learners are given
the opportunity to
apply what they
have learned in
varying contexts
(Ambrose et al.,
2010; Mayer,
2011).
Students need to
identify when
they are not
applying the
methods correctly
and then adjust
their method as a
form of selfregulation and
mastery goals.
Show slide 20. Ask teams
to provide an update on
their data synthesis and
exploration, discussing
any challenges,
difficulties, and failures
that occurred in the
process. Facilitate a
conversation that
provides feedback while
highlighting
opportunities where
Team spokesperson should
provide an update on
data exploration
progress. Team reflector
should provide an update
on challenges faced
during class activity.

204
Instructional
sequence
Time Principle from
LD toolkit and
readings
Rationale Instructor action
(supplantive)
Learner action
(generative)
failures may lead to
better successes.
Retention and
Transfer
2 mins Learning and
motivation are
enhanced when
learners are given
the opportunity to
apply what they
have learned in
varying contexts
(Mayer, 2011).
Ensure that learners
are reflecting and
finding meaning
in the material
being learned.
Show slide 21. Remind
students to record
reflections in their
journals.
Ask students to document
in their journal their
reflections about this
unit.
Advance
organizer for
the next unit
1 min Learning and
motivation are
enhanced if the
learner values the
task (Wigfield &
Eccles, 2000).
This helps learners
to position this
unit as a
preparation for
the next.
Show slide 22. Say: In the
next unit we will
continue to build digital
fluency but will shift the
focus to using AI for
content creation,
communication,
problem-solving, and
cybersecurity.
Ask the learners to
remember to complete
their out of class
readings so that they will
be ready to build more
knowledge and skills
next week in class.
Total Time 190
minutes

205
Lesson Materials
● Reflective Journal
● Read before class
1. University of Cambridge. (2024). Data Management Guide. Retrieved May 13, 2024,
from https://www.data.cam.ac.uk/data-management-guide
○ General information about research, file & data management. Web page
addresses: Systematic and organized approach for information gathering and
methods for storing, managing, and organizing data
○ Skim section “Creating your data”
○ Read section “Organising your data”
○ Skim section: “Looking after your data”
○ Skim section: “Electronic Research Notebooks”
2. Tableau. (2024). What Is Data Management? Importance & Challenges. Retrieved
May 13, 2024, from https://www.tableau.com/learn/articles/what-is-data-management
○ Terminology. Types of data management. Importance of data management.
3. Indeed Editorial Team. (2023, March 10). 6 Examples of Data Abstraction (With
Definition and Benefits). Indeed Career Guide. Retrieved May 13, 2024, from
https://www.indeed.com/career-advice/career-development/data-abstractionexamples
4. keenioblog. (2019, July 16). Accessibility Considerations in Data Visualization
Design. Keen. Retrieved May 13, 2024, from https://keen.io/blog/accessibility-indata-vis/

206
5. McIlwain, C. (2018). Interdisciplinary Competence: The Key to Exceptional
Performance. Defense AT&L. https://www.dau.edu/datl/b/interdisciplinarycompetence
6. Critically Conscious Computing Chapter 14: Abstraction
https://criticallyconsciouscomputing.org/abstractions
7. Hotz, N. (2024). Why Big Data Science & Data Analytics Projects Fail. Data Science
Process Alliance. https://www.datascience-pm.com/project-failures/
8. (Optional) Hatt, B. (2019, February 27). What does bad data look like? Medium.
Retrieved May 13, 2024, from https://medium.com/@bertil_hatt/what-does-bad-datalook-like-91dc2a7bcb7a
○ Highlights problems in data, including abstractions, inconsistent formats,
missing values, etc.
9. (Optional) Stedman, C. (2022, December). What Is Data Management and Why Is It
Important? Data Management. Retrieved May 13, 2024, from
https://www.techtarget.com/searchdatamanagement/definition/data-management
○ overview of importance of data management, key terminology in the process,
DBMS, data warehouses and data lakes, data integration, personnel roles,
history, evolution, and trends in data management (Includes embedded video)
10. (Optional) Borges, E. (2024, March 7). Information Gathering: Techniques and Tools
for Effective Research. Retrieved May 13, 2024, from
https://www.recordedfuture.com/threat-intelligence-101/intelligence-sourcescollection/information-gathering
● Videos to view before class

207
1. Abstraction - Computational Thinking. Robotics Academy. (2.5 minutes)
https://www.youtube.com/watch?v=jV-7Hy-PF2Q
Key points from video:
○ Abstraction is a problem-solving tool that helps simplify situation - remove
unimportant information and focus on what is truly important to the task at
hand.
○ Example: bus route - we need start point, end point, bus route, times, and
shape of route – finding the essential items in the task.
○ Find the KEY pieces of information to represent a class of similar things.
○ Every abstraction is built with a purpose in mind - making an easier to
understand version of a complex system, by focusing on key information
2. Find Problem, Solve Problem By Ariana Glantz - TEDxMemphis (5.5 minutes)
https://www.youtube.com/watch?v=LaYVqj1El1A
Key points from video:
○ Solution-minded Framework:
■ mindset -there is a solution for every problem; there is an opportunity
for success
■ structure - linear or organic flow, find a framework
■ questions - help clarify what you are solving for
■ practice - skill that you need to work on. implement a process. practice
■ patience - for yourself and everyone else

208
3. A level Computer Science: Problem solving and abstraction. Mr. Goff (6.5 minutes)
https://www.youtube.com/watch?v=wF3N2YEdKWI
Key points from video:
○ Specific versus general problems
○ Problem solving methods: exhaustive search or divide and conquer strategy
○ Abstraction - computational thinking - helping to develop understanding of
problem to be solved
■ Representational abstraction: removing unnecessary details from
problem
■ Abstraction by generalization or categorization (finding hierarchical
relationships)
■ Procedural abstraction: computational model - know the interface:
what are values needed (data type and order)
■ Functional abstraction: computation method is hidden
■ Data abstraction: don’t need to know how something is implemented
to use it
■ Problem abstraction: details removed until problem is represented in a
way that is possible to solve because it reduces to something that has
already been solved
■ Compositional abstraction: bring together a series or procedures or
building data abstractions
4. Computational Thinking: Abstraction and Pattern Generalization. Curriki (10
minutes) https://www.youtube.com/watch?v=RdzYOtxhuDc

209
○ Good high level overview of abstraction and pattern generalization, lots of
examples
5. (Optional) Problem Solve Like a Computer Programmer. Kyle Smyth (14.5 minutes)
TEDxRPLCentralLibrary https://www.youtube.com/watch?v=x77-gT8bWLo
● define the problem. understand the problem, break it down (line by line), to make
an algorithm (sample: making a diamond)
● finding the small problems that make up the big problem
● Unit 7 slides (link)

210

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212

213

214

215

216

217

218

219

220

221

222

223

224

225

226

227

228

229

230

231

232
Appendix D: Evaluation Administered Immediately Following the Program
1. My participation in course activities was encouraged by the instructor (L1)
a. Strongly disagree | Disagree | Neutral | Agree | Strongly agree
2. The course materials were easy to follow (L1)
a. Strongly disagree | Disagree | Neutral | Agree | Strongly agree
3. I would recommend this course to other ZYX students (L1, L2)
a. Definitely not | Probably Not | Probably yes | Definitely yes
4. How can this course be improved? (L1)
a. Open-ended
5. What topic(s) did you find most relevant to your studies? (L1, L2)
a. Open-ended

233
For questions 6 –15, please use the following rating scale, which is divided into three designated
intervals to indicate your knowledge rating before taking this course and now (after completing
this course). Entry/Novice (0 = low through 2 = high), Proficient/Skilled (2 = low through 4 =
high), and Mastery/Expert (4 = low through 6 = high).
0 - - - - - - - - - 1 - - - - - - - - - 2 - - - - - - - - - - 3 - - - - - - - - - 4 - - - - - - - - - 5 - - - - - - - - - 6
Entry or novice Proficient or skilled Mastery or expert
Developing awareness / building
knowledge
• Limited repertoire
• Limited experience
• Unaware of potential
problems
• Unaware of questions to ask
Applying knowledge routinely
• Basic repertoire
• Moderate amount of
experience
• Solves problems as they arise
• Aware of questions to ask and
able to access resources to
answer the questions
Using knowledge fluently and
effectively
• Advanced repertoire
• Extensive experience
• Anticipates problems before
they arise
• Poses questions to the field
• Sought out for input
Before the course Now (after the course)
0 1 2 3 4 5 6 6. Ability to explain the reliability,
relevance, credibility, and biases
in information and/or data (L2)
0 1 2 3 4 5 6
0 1 2 3 4 5 6 7. Ability to locate relevant and
credible information (L2)
0 1 2 3 4 5 6
0 1 2 3 4 5 6 8. Ability to articulate best practices
and guidelines for accessibility
and demonstrate common
features of digital tools for
communication and collaboration
(L2)
0 1 2 3 4 5 6
0 1 2 3 4 5 6 9. Ability to create and publish
digital content (using visual
design principles) (L2)
0 1 2 3 4 5 6
0 1 2 3 4 5 6 10. Ability to develop a computer
program to accomplish a task,
using an iterative design process
(L2)
0 1 2 3 4 5 6

234
0 1 2 3 4 5 6 11. Ability to protect information
and digital assets (L2)
0 1 2 3 4 5 6
0 1 2 3 4 5 6 12. Ability to use a systematic and
organized approach for gathering
and synthesizing information
(L2)
0 1 2 3 4 5 6
0 1 2 3 4 5 6 13. Ability to use abstraction and
computational thinking skills to
iterate through possible solutions
to a problem (L2)
0 1 2 3 4 5 6
0 1 2 3 4 5 6 14. I have confidence in my ability to
apply what I have learned in
future situations (L1)
0 1 2 3 4 5 6
0 1 2 3 4 5 6 15. I am committed to apply what I
have learned in future courses
(L1)
0 1 2 3 4 5 6

235
Appendix E: Evaluation Administered Two Semesters After the Course
For question 1-7, if the participant selects it depends, require that they elaborate with an
example. If they select rarely or never, require that they indicate their reasons from the following
list (checking all that apply):
● I do not have the necessary knowledge and skills.
● I do not have a clear picture of what is expected of me.
● I have other, higher priorities.
● I do not have the necessary resources to apply what I learned.
● I do not have the support to apply what I learned.
● The course did not give me the confidence to apply what I learned.
● Other (please explain):
1. I assess information and data for reliability, relevance, credibility, and biases. (L3)
a. Always | Often | Sometimes | Rarely | Never | It depends
2. I interact, communicate, and collaborate with others effectively in synchronous and
asynchronous digital environments. (L3)
a. Always | Often | Sometimes | Rarely | Never | It depends
3. I apply best practices and guidelines for accessibility. (L3)
a. Always | Often | Sometimes | Rarely | Never | It depends
4. I can independently create and publish digital content. (L3)
a. Always | Often | Sometimes | Rarely | Never | It depends
5. I implement safety measures to protect information and digital assets. (L3)
a. Always | Often | Sometimes | Rarely | Never | It depends

236
6. I use a systematic and organized approach for gathering and synthesizing information.
(L3)
a. Always | Often | Sometimes | Rarely | Never | It depends
7. I use abstraction and computational thinking skills to iterate through possible solutions to
a problem. (L3)
a. Always | Often | Sometimes | Rarely | Never | It depends
8. I have used what I have learned in this course in other classes. (L1)
a. Strongly disagree | Disagree | Neutral | Agree | Strongly agree
9. What information from this course has been most relevant to your other studies? (L1, L2)
a. Open-ended
10. What information should be added to this course to make it more relevant to your other
studies? (L1, L2)
a. Open-ended
11. Please provide an example of a positive outcome that you have experienced since
completing this course (L4)
a. Open-ended
12. This course has positively impacted my ability to succeed at ZYX University. (L4)
a. Strongly disagree | Disagree | Neutral | Agree | Strongly agree
13. I have seen an impact in the following areas as a result of applying what I learned in this
digital fluency course (check all that apply) (L4)
a. Increased quality of work
b. Improved productivity
c. Increased personal confidence

237
d. Better performance in other courses
e. Better organization
f. Increased willingness to experiment with new technology
g. Increased confidence in ability to learn new technology
h. Other (please explain):
14. Is there anything else you would like to share about the impact of this course on your
experience at ZYX University? (L3, L4)
a. Open-ended

Abstract (if available)

Abstract With the rapid pace of technological progress, all undergraduate students need to be digitally fluent and critical consumers of data and technology. New technology and AI innovations are entering our lives at an alarmingly fast pace. Institutes of higher education need to adapt and evolve by providing coursework addressing digital fluency for students. This curriculum centers five core competencies integral to digital fluency, while weaving in the concept of critically conscious computing and helping students to become lifelong learners in an increasingly technological world. Informed by research on learning and motivation and leveraging the European Union’s DigComp 2.2 framework as well as Ko’s (2024) research on critically conscious computing, this 15-week course uses a spiral-curriculum approach to provide at least two mastery opportunities for each competency. By the end of this course, students will demonstrate competence in information and data literacy, enhance communication and collaboration skills, demonstrate digital content creation, practice safety and cybersecurity skills, and develop problem solving skills. While developing these competencies, learners will practice critically conscious computing by considering social and ethical impacts of computing and technology to help build a more just and equitable future. Curriculum implementation details and an evaluation plan which measures student achievement of goals and outcomes is included. This curriculum can serve not only to provide knowledge to students, but as a catalyst and model for incorporating digital fluency competencies in curriculum efforts across disciplines.

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Asset Metadata

Creator Walther, Kendra Lynn (author)

Core Title Digital fluency and critically conscious computing: a curriculum for undergraduates

School Rossier School of Education

Degree Doctor of Education

Degree Program Educational Leadership

Degree Conferral Date 2024-08

Publication Date 06/10/2024

Defense Date 06/03/2024

Publisher Los Angeles, California (original), University of Southern California (original), University of Southern California. Libraries (digital)

Tag communication and collaboration,critically conscious computing,curriculum,digital content creation,digital fluency,information and data literacy,OAI-PMH Harvest,problem solving skills,safety and cybersecurity,technology

Format theses (aat)

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Yates, Kenneth (committee chair), Krishnamachari, Bhaskar (committee member), Seli, Helena (committee member)

Creator Email kendra@thewalthers.com,kwalther@usc.edu

Permanent Link (DOI) https://doi.org/10.25549/usctheses-oUC113992579

Unique identifier UC113992579

Identifier etd-WaltherKen-13073.pdf (filename)

Legacy Identifier etd-WaltherKen-13073

Document Type Dissertation

Format theses (aat)

Rights Walther, Kendra Lynn

Internet Media Type application/pdf

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Source 20240610-usctheses-batch-1166 (batch), University of Southern California (contributing entity), University of Southern California Dissertations and Theses (collection)

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Repository Location USC Digital Library, University of Southern California, University Park Campus MC 2810, 3434 South Grand Avenue, 2nd Floor, Los Angeles, California 90089-2810, USA

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