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Approaches to encouraging and supporting self-regulated learning in the college classroom

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Approaches to encouraging and supporting self-regulated learning in the college classroom

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Content Running head: APPROACHES TO SRL 1

Approaches to Encouraging and Supporting Self-Regulated Learning in the College Classroom

by

Mathew Williams

A Dissertation Presented to the
FACULTY OF THE USC ROSSIER SCHOOL OF EDUCATION
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF EDUCATION

August 2018

Copyright 2018 Mathew Williams
APPROACHES TO SRL 2
Dedication
I dedicate this dissertation to my incredible wife, Danielle, and our wonderful kids.
Danielle, I cannot thank you enough for the encouragement, support, and patience you have
shown me throughout this program. Your selflessness and capacity for love reflect a rare
combination of strength and kindness not often found in this world, and I feel privileged to share
this life with you. To my kids, you may soon forget all the long days I had to spend away and the
late nights you had to go to bed without me, but please know how grateful I am that I was able to
take this time to pursue my dreams. All I can promise in return, is that I will do everything I
possibly can to help you pursue yours.

APPROACHES TO SRL 3
Acknowledgements
This dissertation would not be possible without the support of countless family, friends,
and colleagues. I first want to thank my parents, who encouraged me from a young age to dream
big and never once suggested I settle for anything less. I also want to thank my many colleagues
and supervisors who have supported me over the years. Your guidance and advice has been
invaluable, as has your commitment to supporting lifelong learning. To my classmates at USC, I
want to thank you for all of the great conversation, debate, and support. This program would not
have been nearly as meaningful and impactful without being able to share in your experiences
and perspectives. Finally, I want to extend my sincere gratitude to my dissertation committee:
Dr. Patricia Tobey, Dr. Patrick Crispen, Dr. Wayne Combs, and Dr. Michael Escalante. I greatly
appreciate all of your guidance, support, and encouragement throughout this process.

APPROACHES TO SRL 4
Table of Contents
List of Tables 6
List of Figures 7
Abstract 8
CHAPTER ONE: OVERVIEW OF THE STUDY 9
Background of the Problem 10
Statement of the Problem 12
Purpose of the Study 13
Site and Context of the Study 14
Research Questions 15
Significance of the Study 15
Limitations and Delimitations 16
Definition of Terms 17
Organization of the Study 18
CHAPTER TWO: LITERATURE REVIEW 19
Nature of Self-Regulated Learning in College Students 19
Relationship Between Self-Regulated Learning and the Course Context 23
Instructor Support for Self-Regulated Learning 28
Theoretical Model of Self-Regulated Learning 32
Outcomes 33
Motivation 34
Cognition and Self-Regulatory Processes 34
Personal and Contextual Influences 36
Conceptual Framework for Study 38
Summary 41
CHAPTER THREE: METHODOLOGY 42
Research Design 42
Sample and Population 43
Instrumentation 44
Data Collection 46
Data Analysis 47
Credibility and Trustworthiness 50
Timeline 51
CHAPTER FOUR: FINDINGS 53
Summary of Cases 53
Faculty Perceptions of Self-Regulated Learning in Their Courses 56
Performance Orientation 56
Effort and Time Use 58
Metacognition and Metacognitive Knowledge 59
Faculty Approaches to Encouraging and Supporting SRL 61
Directly Suggesting and Teaching SRL-Related Strategies 61
Creating Conditions that Support and Encourage SRL 65
Faculty Perceptions of Effectiveness 75
Balance of Responsibility for Learning 76
Observing and Measuring SRL 77
APPROACHES TO SRL 5
Differential Impact 78
Promising Practices 80
Summary 84
CHAPTER FIVE: DISCUSSION 85
Discussion of Findings 85
Faculty Perceptions of Self-Regulated Learning in Their Courses 85
Faculty Approaches to Encouraging and Supporting SRL 87
Faculty Perceptions of Effectiveness 89
Implications for Practice 92
Recommendations for Research 94
Conclusions 95
References 97
Appendix A: Summary of SRL-Supporting Practices from Recent Empirical Research 104
Appendix B: Research Alignment Matrix 105
Appendix C: Guide for First Interview 106
Appendix D: Observation Protocol 108
Appendix E: Guide for Second Interview 110
Appendix F: Initial Codebook for Interviews, Observations, and Artifact Analysis 111
Appendix G: Final Codebook for Interviews, Observations, and Artifact Analysis 112
Appendix H: IRB Study Information Sheet 114

APPROACHES TO SRL 6
List of Tables
Table 1: Timeline of Events 52
Table 2: Summary of Participants 54
Table 3: Summary of Case Contexts 55
Table 4: Summary of Interviews and Observations 55
Table 5: Summary of Instructor Approaches and Strategies 75

APPROACHES TO SRL 7
List of Figures
Figure A: Conceptual Framework 39

APPROACHES TO SRL 8
Abstract
Variations in how college students monitor and control their own learning can contribute to
differences in important academic outcomes, including engagement and depth of understanding.
Theories of self-regulated learning (SRL) indicate that one area where higher education
practitioners may be able to promote more adaptive patterns of SRL is in the teaching practices
employed by faculty. This study provides an in-depth account of how faculty at a large public
research university approach this issue and how their teaching practices may encourage and
support self-regulated learning. Five faculty participated in the study, which consisted of two
interviews of each participant, course observations, and an analysis of related course documents.
Data was coded and analyzed to identify patterns, themes, and relationships in the perceptions
and teaching practices of the participants. Findings indicate that although participants recognized
specific differences in SRL among their students and have been incorporating several promising
practices, they are also encountering challenges with implementing and assessing these practices.
These findings point to a need to further explore and measure the effectiveness of existing
practices, while also developing new approaches to improving SRL, particularly in the areas of
motivation and regulation of motivation.
Keywords: self-regulated learning, motivation, cognition, teaching practices, instructional
strategies, higher education, faculty perspective
APPROACHES TO SRL 9
CHAPTER ONE: OVERVIEW OF THE STUDY
Students who effectively plan, monitor, control, and reflect on their learning often reach a
deeper level of understanding and achieve more academically than students who do not (Park,
Edmondson, & Lee, 2012; Pintrich & Zusho, 2007; Zusho, 2017). From an early age, however,
significant differences have been found in students’ engagement in these activities, both between
students and for the same student across different contexts. Some of these differences are
adaptive, leading to more effective regulation of learning, while others reveal challenges with
regulation that can influence immediate outcomes as well as development over time. This pattern
of variability can be found across all levels of education and has been the subject of significant
empirical research (Dent & Koenka, 2016; Dignath & Büttner, 2008; Wigfield, Klauda, &
Cambria, 2011).
This study explored the issue of variability in postsecondary students’ effective
regulation of their learning from the perspective of university faculty. Faculty can encounter this
variability as differences in student motivation, cognition, effort, and strategy use. Over the
period of a course or program of study, these differences have been shown to affect important
behavioral, affective, and cognitive outcomes (Park et al., 2012; Pintrich & Zusho, 2007; Zusho,
2017). This presents a challenge for institutions and their faculty: how to design learning
experiences that encourage self-regulation, and how to support the development of associated
knowledge and skills where they may be insufficient.
The aim of this study was to explore how a group of faculty at one public research
university approach this challenge in their undergraduate courses. This chapter provides an
overview of the study, beginning with a summary of what is currently known and unknown
about the problem. This is followed by a discussion of the purpose of the study, a description of
APPROACHES TO SRL 10
the site and context within which the study took place, and the research questions that guided the
study. The chapter concludes with important limitations, delimitations, and key definitions.
Background of the Problem
In practice, self-regulated learning (SRL) is sometimes conceptualized as engagement,
motivation, metacognition, study strategies, or general approaches to learning. Although related
and often included in theoretical models of self-regulated learning, these concepts alone do not
reflect the full picture. In current models, self-regulated learning is characterized as a dynamic
interaction between student motivation, cognition, and self-regulatory processes directed by
students in an effort to achieve a specific learning goal (Pintrich & Zusho, 2007; Winne &
Hadwin, 1998; Zimmerman, 2001; Zusho, 2017). These processes are often organized into
phases, including forethought/planning, monitoring/control, and reflection/attribution. They also
reflect specific domains, such as regulation of cognition, motivation/affect, behavior, and
context. Critically, most of these processes are not considered automated. Students actively
choose when and how intensely to engage in them. Rather than stable behaviors or generalized
abilities that persists across time and contexts, researchers have found that these processes
progress dynamically, unfolding differently across learning environments and academic tasks.
Students who regularly and effectively regulate their learning throughout an activity,
course, or program of study often exhibit greater engagement, reach a deeper level of
understanding, and experience greater academic achievement (Pintrich & Zusho, 2007; Zusho,
2017). Evidence suggests, however, that there are often significant differences in how frequently
and how effectively postsecondary students do so (Dye & Stanton, 2017; Park et al., 2012;
Sebesta & Bray Speth, 2017; Verrell & McCabe, 2015). This has been found to be the case for
students just entering college, as well as those further along in their studies. Recent research has
APPROACHES TO SRL 11
confirmed that some students may not seek out or develop new SRL strategies on their own,
even when faced with poor achievement. For example, even students who recognize a need to try
a different study strategy as a result of an unsatisfactory grade on an exam may not do so in order
to avoid the discomfort and anxiety associated with abandoning familiar strategies (Dye &
Stanton, 2017).
The existence of this variability in self-regulation of learning is well established and has
been the focus of significant efforts by researchers in the field of educational psychology to
understand how SRL develops and what influences it (Wigfield et al., 2011). Multiple factors
have been identified and confirmed through empirical research, including a given student’s prior
knowledge, beliefs about learning, motivation, and lifeload (Kahu, 2013; Pintrich & Zusho,
2007; Zusho, 2017). By the time students reach college, their engagement in self-regulated
learning has likely been shaped to a large degree by their experiences in primary and secondary
educational settings. However, a college student’s effective or ineffective regulation is not a
foregone conclusion. Most models of SRL, rooted in extensive empirical research, recognize the
influence that the features and characteristics of the current context can have on students’
regulation of learning (Pintrich & Zusho, 2007; Winne & Hadwin, 1998; Zimmerman, 2001;
Zusho, 2017). This includes more distal factors, such as discipline, curriculum, and institutional
support, as well as the more immediate nature of the academic task, instructional methods, and
the instructor’s behavior.
Understanding and distinguishing between these factors is crucial for higher education
practitioners, as the dynamic and multi-faceted nature of SRL suggests multiple types of
interventions may be necessary to support and encourage SRL in the greatest number of students.
At the postsecondary level, a conventional approach to this has been the creation of support
APPROACHES TO SRL 12
programs and curricula in the form of learning skills courses, supplemental instruction, and
tutoring (Wolters & Hoops, 2015). These typically supplement the traditional curriculum and can
be focused on general learning skills and strategies or those specific to a particular discipline.
Researchers have also made headway into identifying course structures, academic tasks,
instructional methods, and instructor behaviors that promote the use and development of SRL in
college students (Bol, Campbell, Perez, & Yen, 2016; Connell, Donovan, & Chambers, 2016;
Corkin, Horn, & Pattison, 2017; Sletten, 2017). These experimental studies suggest that there are
steps faculty can take in regular courses to help students develop SRL-related knowledge and
skills and increase the likelihood of students effectively regulating their learning.
Statement of the Problem
The influential role of the context in shaping self-regulated learning suggests that
individual factors associated with each course a student takes can impact how and to what extent
they regulate their learning (Pintrich & Zusho, 2007; Zusho, 2017). While administrators and
faculty may have limited ability to change some of these factors (e.g., attainment value and
intrinsic value), many others, such as course design and instructional methods, are often well
within their control. Experimental research on SRL offers insights into the teaching practices that
can be used in these areas to help support and encourage SRL (Bol et al., 2016; Connell et al.,
2016; Corkin et al., 2017; Sletten, 2017). However, it is less clear how faculty outside of
experimental settings are incorporating these practices into their regular courses and whether
they are also finding them to be effective (Hoops, Yu, Wang, & Hollyer, 2016; Hora, 2015;
Khaled, Gulikers, Biemans, & Mulder, 2016; Smith, Vinson, Smith, Lewin, & Stetzer, 2014).
Much of the research on teaching practices in naturalistic settings has been focused on
describing and quantifying how much time instructors spend lecturing compared to using more
APPROACHES TO SRL 13
active and collaborative techniques (Eagan et al., 2014; Hora, 2015; Smith et al., 2014). A key
finding is that over the past 25 years, faculty teaching undergraduate courses have been steadily
reducing the time they spend lecturing in class in favor of more student-centered instructional
strategies (Eagan et al., 2014). While this is generally considered a positive trend given the
significant body of evidence documenting the effectiveness of these approaches (Freeman et al.,
2014; Kuh, Kinzie, Schuh, & Whitt, 2010; Mayhew et al., 2016), the nature of how instructors
incorporate supports for self-regulated learning in these settings is less well known. Concepts
related to self-regulated learning may be acknowledged in these studies, but with the exception
of just a few (e.g., Hoops et al., 2016; Khaled et al., 2016), SRL-supporting practices have not
been the primary focus of inquiry.
Purpose of the Study
Incorporating supports for self-regulated learning in regular courses is a promising
approach to the problem of insufficient and ineffective patterns of self-regulated learning among
postsecondary students (Bol et al., 2016; Connell et al., 2016; Corkin et al., 2017; Sletten, 2017).
These supports may be implemented in the design and facilitation of the course with the intent of
increasing student knowledge of effective learning strategies and creating conditions that
encourage and support their use. Some of these practices have been identified and evaluated
through empirical research, while others are yet to be discovered and developed. The purpose of
this study was to explore how faculty in postsecondary settings are using these known and
potentially novel practices to encourage and support self-regulated learning in their
undergraduate courses. The following section provides further details about the site of the study
and the specific research questions that were addressed.

APPROACHES TO SRL 14
Site and Context of the Study
The site selected for this study, Riverview University (RVU, a pseudonym), is a public
research university located in the western United States. It currently enrolls 25,000
undergraduate and 5,500 graduate students across a wide-range of disciplines. As a public
research university, it is driven by a three-part mission of teaching, research, and public service.
The instructional staff consists of tenure-track and non-tenure track faculty, adjuncts, and
graduate teaching assistants. Course sizes can range from the many-hundreds to just a handful of
students, although a significant portion are above 30 students. These characteristics are likely
shared across many similar institutions, which may help increase the transferability of the
findings.
An important factor in selecting this institution is that in a recent institution-wide
strategic planning process, RVU made the broader adoption of research-based instructional
practices a top priority for the institution over the next several years. Existing data available at
RVU indicates that a portion of faculty are already using teaching practices that may be
considered research-based, including those associated with active learning and student-centered
pedagogies. However, while some of these practices may be related, little is known at an
institutional level about how faculty at RVU specifically experience and approach SRL among
students in their courses.
Given their dominant role in curriculum and instruction, faculty were the logical
participants to select for this study. It is worth noting, though, that achieving the goal of broader
adoption of research-based instructional practices also involves administrators, staff, and
students. The leadership provided by administrators at the institutional level and within academic
units, many of whom are faculty, help communicate the priority of this goal and establish how
APPROACHES TO SRL 15
progress will be measured. They also have some degree of control over resources and
organizational structures that can support the achievement of the goal. Staff, as well, contribute
to the goal by working with and supporting faculty and students on an ongoing basis. Of
particular note, staff and administrators in the area of educational and instructional development
frequently work with faculty and academic units to support efforts to improve teaching across the
institution.
Research Questions
The following research questions guided the study and reflect the broader problem of
practice and local goals of the study site:
1. How are a group of RVU faculty experiencing variability in self-regulated learning
among the undergraduate students that they teach?
2. What teaching practices are these faculty using that may encourage and support self-
regulated learning?
3. What are faculty perceptions of the effectiveness of these teaching practices?
To answer these questions, this study employed a qualitative case study design, including
interviews, classroom observations, and document analysis. It was guided by the model of self-
regulated learning put forward by Zusho (2017), which builds upon extensive work by Pintrich,
Zusho, and others (e.g., Pintrich, 2003, 2004; Pintrich & Zusho, 2007; Zusho, Pintrich, &
Coppola, 2003).
Significance of the Study
Given the importance of SRL in student success and the growing body of experimental
research that is identifying instructional practices that support it, there is a need to better
understand how these practices are being used in natural settings. Studying these settings in-
APPROACHES TO SRL 16
depth can also reveal valuable variations of these practices and even wholly distinct practices
that could be candidates for further evaluation. The findings of this study contribute to both of
these areas, providing an increased understanding of faculty perceptions and teaching practices at
the selected site, as well as adding to the broader literature on postsecondary instruction and self-
regulated learning.
Limitations and Delimitations
This study aimed to provide an in-depth account of the perceptions and teaching
practices of a small group of faculty. The methodological decisions reflect this purpose and the
nature of the research questions. Specifically, the qualitative approaches used in this study (i.e.,
interviews, observations, and artifact analysis) are ideally suited to address questions about
meaning and to document processes in detail (Maxwell, 2013; Merriam & Tisdell, 2016).
Although not immediately generalizable, these approaches enable the thick descriptions and in-
depth analysis needed to answer the research questions, while also providing the reader with
enough information to transfer these findings to similar contexts for further research and
evaluation. That being said, there are important limitations that should be acknowledged.
A key limitation inherent in the qualitative approach of the study is that it did not include
any direct measures of self-regulated learning. As the intent was to describe faculty perceptions
and existing teaching practices in naturalistic settings, this was determined to be an acceptable
limitation. However, it should be noted that the classification of teaching practices as supportive
of self-regulated learning was made based upon interpretations of the existing literature and
models of SRL, as well as the participants’ self-reports of effectiveness. Although effectiveness
was not assessed directly, the findings pave the way for future research that can build on the
practices discovered and documented in this study.
APPROACHES TO SRL 17
Another potential limitation that should be acknowledged is the small sample size and
study duration, which consisted of five faculty, at one institution, for one academic term. This
was an intentional decision based on time constraints and goals of the study. The intent was not
to evaluate all of the faculty at the institution or even a representative sample. Instead, care was
taken to identify faculty most likely to be using teaching practices supportive of SRL.
One important delimitation to note is that the study did not include the student
perspective, including any personal characteristics and more distal factors that could also
influence SRL. Given the complex nature of SRL and all of the potential factors, certain
boundaries and priorities had to be established to ensure the focus remained on answering the
research questions. Although these personal factors are critical to the model, this study was
specifically concerned with the contextual factors, namely the teaching practices and
instructional behaviors.
Definition of Terms
Active Learning: a broad collection of teaching practices and pedagogies that aim to increase
student engagement in their learning, from both a behavioral and a cognitive perspective
(Bonwell & Eison, 1991; Chickering & Gamson, 1987; Prince, 2004).
Self-Regulated Learning (SRL): a collection of related processes and strategies that students may
use to plan, monitor, control, and evaluate their cognition, motivation/affect, behavior, and
context in order to achieve a learning goal (Pintrich & Zusho, 2007).
Student-Centered Teaching Practices: approaches to teaching that emphasize and prioritize the
learning processes and experiences of students over the use of specific instructional methods
(Barr & Tagg, 1995; Felder & Brent, 1996; Weimer, 2013).

APPROACHES TO SRL 18
Organization of the Study
This study is organized into five chapters. This first chapter introduced the purpose of the
study, the context to be studied, and the methodology. Chapter two provides an analysis of the
current literature related to self-regulated learning in postsecondary settings. Chapter three
discusses the methodology that will be used to carry out the study. The findings are presented in
chapter four and then further discussed in chapter five.
APPROACHES TO SRL 19
CHAPTER TWO: LITERATURE REVIEW
The literature on self-regulated learning (SRL) is expansive and encompasses a broad
range of emphases, from general approaches to learning to real-time measures of regulation. This
chapter provides a review and analysis of recent empirical studies of self-regulated learning that
are most relevant to the purpose and context of the study. The literature is organized into three
themes: recent evidence describing the nature of self-regulated learning in college students; a
more specific examination of what is known empirically about the relationship between student
self-regulation and course contexts; and, recent attempts to describe and measure the use of
instructional strategies that support SRL. Following the recent empirical literature, the chapter
concludes with a discussion of the theoretical model of SRL (Pintrich & Zusho, 2007; Zusho,
2017) and conceptual framework that grounds the study.
Nature of Self-Regulated Learning in College Students
Several recent studies have attempted to describe, measure, and quantify the use of self-
regulated learning strategies by college students (Dye & Stanton, 2017; Park et al., 2012; Sebesta
& Bray Speth, 2017; Verrell & McCabe, 2015). The evidence suggests that student awareness
and use of SRL strategies in the college context is varied. This is a particularly critical finding, as
it has been shown that student use and development of SRL strategies can affect immediate
learning and developmental outcomes, as well as lifelong competencies.
Park and colleagues (2012) examined the development of SRL-related abilities and
psychological adjustment during the first year of college. Using a longitudinal design, they
assessed constructive thinking, emotion regulation, mastery, and adjustment in 175 first-year
students before the beginning of the year. Students completed the same assessment roughly ten
months later. At the completion of the study, the researchers discovered an overall lack of
APPROACHES TO SRL 20
growth in constructive thinking, emotional regulation, and mastery during the first year of
college. As this was an average, there were some who made gains, but also those who saw a
decline in self-regulation abilities. This change was found to predict students’ psychological
adjustment (i.e., depression, anxiety, and stress). Although this study only took place at one
institution and may have issues with selection bias, it does point toward a need to better
understand how SRL develops and changes during college. It also suggests possible links
between SRL development in college students and psychological adjustment.
Verrell and McCabe (2015) had similar findings in their survey of 677 undergraduate
students at Washington State University. They asked students from two lower-division biology
courses how prepared they felt for college, followed by more specific questions about their use
of SRL strategies. Their survey results highlight a discrepancy between how students feel about
their general level of preparation and their self-reported use of SRL strategies. Specifically, 70%
of respondents felt that their high schools prepared them well for college. Yet, when asked about
specific components of SRL, the majority of students felt poorly or only adequately prepared to
attend to detail, go beyond the minimum, use additional resources, manage time, and study to
learn deeply. They did, however, feel well prepared to complete all work, be ethical, take pride
in good work, be prepared for class, and attend class. As the study relies on student self-
assessment of their abilities, the authors suggest that some of these may be inflated and that
actual student ability is below that reported. This is congruent with the findings of Park et al.
2012, indicating that many students do not enter postsecondary education with a robust set of
SRL strategies. Verrell and McCabe go a step further in demonstrating that students may not be
aware of or acknowledge the role of these specific strategies in academic preparation.
APPROACHES TO SRL 21
These challenges also present themselves at the level of individual courses, as Sebesta
and Bray Speth (2017) discovered in their study of 414 students in an introductory biology
course at a large, private research institution. This course was taught using a flipped classroom
approach, utilizing textbook readings, instructor-produced videos, online quizzes, and
assignments outside of class. During class, students worked in persistent groups of three on
activities that required them to solve problems and apply concepts from the course. At two points
in the term, shortly after completing an exam, students were surveyed on their use of several
SRL strategies. Results from the surveys indicate that most students employed the following
strategies: seeking information, environmental structuring, reviewing textbook or videos, seeking
help from peers, and keeping records. The least used strategies included seeking assistance from
the instructor and seeking assistance from other resources, such as teaching assistants or tutors.
The only significant change in strategy use between the two surveys was reviewing exams. The
authors also analyzed use of SRL strategies in relation to achievement on the exams. They found
that students who improve their grade between the two exams more frequently used five
strategies: self-evaluation, goal setting and planning, seeking information, reviewing notes, and
reviewing exams. Although the study only examined one course and relied primarily on self-
report of strategy, it does provide evidence of the relationship between SRL and outcomes. It
also suggests that poor performance on an exam may not be sufficient to lead to a shift in SRL
strategy use.
A separate study carried out by Dye and Stanton (2017) helps shed some light on why
students may or may not change their use of SRL strategies. Utilizing a qualitative design that
included self-evaluation assignments and semi-structured interviews, the researchers examined
when, why, and how students in an upper division biology course evaluated their approaches to
APPROACHES TO SRL 22
learning and changed their use of SRL strategies. The authors purposefully sampled students
who had previously been identified as highly metacognitive. They found that most of the
students evaluated their approach to learning in response to an unsatisfactory grade, while very
few evaluated due to an internal indicator such as self-testing. This suggests that external
feedback may be a helpful step in prompting students to change their strategies. However, the
researchers further discovered that even when students recognized that the strategies they were
using were ineffective, some found it challenging to switch strategies, citing the discomfort
associated with change and the desire for familiarity. This is congruent with Sebesta and Bray
Speth's (2017) findings and suggests that for highly metacognitive students, the lack of strategy
change after an unsatisfactory grade may be related to affective factors. As this is a qualitative
study, direct generalization beyond the sample would not be appropriate. However, it does offer
areas for further investigation and a possible explanation for a gap between evaluation of
learning and regulation of cognitive strategies.
The literature discussed in this section provides three important insights into the nature of
SRL in college students: their knowledge and use of SRL strategies can vary significantly, use of
specific strategies is related to improved outcomes, and monitoring and evaluation may not lead
to control (Dye & Stanton, 2017; Park et al., 2012; Sebesta & Bray Speth, 2017; Verrell &
McCabe, 2015). Although most studies were limited by self-report and small sample sizes, the
consistency among the results does offer increased support for these findings. It is also clear that
the broad scope of SRL can pose a challenge when trying to study the model in its entirety, with
most researchers only examine a few aspects. While the present study will not directly measure
SRL strategies, the varied nature of SRL strategies used by college students demonstrates the
APPROACHES TO SRL 23
need to understand instructor awareness of these strategies, and how they are attempting to
support the use and development of them.
Relationship Between Self-Regulated Learning and the Course Context
Building on the previous section on the nature of SRL in the broad context of
postsecondary students, this section focuses more closely on the relationship between SRL and
specific components of college courses. There are several components of the course context that
may influence SRL and motivation: the nature of a given task, the reward and goal structure of
the course, and instructional methods and behaviors (Pintrich & Zusho, 2007; Zusho, 2017).
Recent studies have confirmed this relationship while providing a more nuanced understanding
of specific course designs and instructional methods (Bol et al., 2016; Connell et al., 2016;
Corkin et al., 2017; Sletten, 2017).
In an effort to better understand the effectiveness of student-centered pedagogies on
learning and attitudes about biology, Connell and colleagues (2016) compared two different
course designs for an introductory biology course: a course with moderate use of student-
centered pedagogies and a course with high use. The moderate design included two 30-minute
lectures per class period as the primary form of instruction, which integrated think-pair-share
activities, reflective pauses, and real-time writing. The extensive design included the same
elements, but used shorter just-in-time lectures based on pre-class assessments, two-minute
writes, cooperative learning, content summaries, group quizzes, and structured worksheets. One
of the intentions behind this course’s design was to include support for self-regulated learning,
which was operationalized as metacognition. Specifically, students were asked to create content
summaries at the beginning of a module and then revise them after completing the structured
worksheets, the goal being to prompt students to reflect on their change in understanding. In
APPROACHES TO SRL 24
analyzing the results from student test scores and changes in a pre and post assessment of content
knowledge, the researchers conclude that students in the extensive section learned significantly
more than the moderate section. Results from the authors’ multiple regression analysis revealed
that students in the extensive course scored significantly higher on a posttest that assessed
content knowledge. They found similar results for students’ attitudes about science and learning
science. Despite having similar profiles at the beginning of the course, students in the extensive
course showed a greater shift toward expert views of biology and learning science. Although it is
difficult to determine which aspects of the extensive section contributed most to these outcomes,
the experiment does provide credible evidence of the effectiveness of this combination of
student-centered pedagogies. It also supports the need for further research into self-regulation
constructs such as metacognition.
A more focused evaluation of SRL interventions was carried out by Bol and her
colleagues (2016) in community college developmental math courses. Their intervention
consisted of four components: students set weekly goals and established a plan for achieving
them; students assessed their study habits and time management; students planned their study
time for the week; and, students compared observations made during self-monitoring to goals.
Students were randomly assigned to the intervention course or a control course that did not
include these SRL activities. Results from the final exam indicate that students in the
intervention scored 0.23 SD above the mean. Students were also asked to complete the
metacognitive self-regulation and time/study environmental management scales from Motivated
Strategies for Learning Questionnaire (MSLQ). Student responses to this questionnaire indicate
significantly higher metacognitive self-regulation and time/study management among the
intervention group. One limitation of this study is that there were no pretests to compare these
APPROACHES TO SRL 25
findings against. However, the use of random assignment should have helped ensure comparable
starting samples. It should also be noted that students in developmental math courses in
community colleges might not be representative of the student population in the present study,
undergraduates at research universities.
Another SRL-based intervention for college students was developed and evaluated by
Steiner (2016) within the context of first-year seminar courses. She created an assignment that
students could apply to any course they were taking that would support students in regulating
their learning. The intervention consisted of planning, monitoring, and evaluating strategies that
students used in preparation for a test. Specifically, they had to plan their study time, interact
one-on-one with the instructor, use active reading strategies, use active note-taking, apply active
learning strategies (e.g., self-quizzing, concept mapping), and reflect on exam performance. The
researcher then examined student reflections for emerging themes using an open coding process.
Her descriptions of student responses highlight several important findings, including: students
most liked the study plan and instructor interaction, but had mixed feelings about the other
strategies; students self-reported increases in test grades and confidence in test-taking skills as a
result of the intervention; students reported permanent changes in their study and time-
management skills, as well as recognized the value of preparing for exams. Although these
findings cannot be generalized due to the qualitative nature of the study, the thick descriptions
and analysis provide insight into how students interpreted, used, and benefited from the SRL-
strategy intervention and how future interventions might be designed.
While the studies discussed so far have been mostly positive, Corkin et al. (2017) offered
a more varied picture of the effectiveness of course-based interventions. In a randomized
controlled trial involving 962 students enrolled in separate introductory biology courses, they
APPROACHES TO SRL 26
tested the effectiveness of an active learning intervention on classroom motivational climate,
student motivation, and learning. Similar to Connell et al. (2016), the intervention included a
variety of instructional methods, some of which were informed by principles from the SRL
literature. Specifically, it included: clicker questions to assess student understanding; think-pair-
share to discuss questions and solve problems; case studies; demonstrations; instructional videos;
advising sessions; and peer-led recitation sessions, which were optional unless students scored
below 70% on the first exam. The peer sessions included: team-based problem-solving; hands-on
use of modeling materials; and assistance with SRL skills, such as reading, note taking, concept
mapping, practice with problem-solving, recall, self-reflection, time management, and self-
motivation. Somewhat surprisingly given the findings of other studies involving similar
interventions, the researchers did not see a significant difference in average course grade in the
intervention course compared with the control course, which used more traditional instructional
methods. However, a more in-depth analysis did reveal a few small to moderate positive effects
on perceived instructor support and academic press, situational interest, and self-efficacy and
task value. Mediation analyses further revealed that although there was not a direct correlation
between the intervention and course grade, there was an indirect effect through the motivational
climate and motivational belief variables. Overall, students were more likely to view the
intervention course as supportive, holding higher expectations for learning, and situationally
interesting. Students in the intervention also experienced increases in confidence and personal
value. Unfortunately, it was not clear to what extent the SRL-based peer sessions contributed to
these findings, as the researchers did not track attendance, but as a whole, the intervention did
show promise.
APPROACHES TO SRL 27
Sletten (2017) took a somewhat different approach in examining student perception,
SRL, and achievement in a flipped introductory biology course. Rather than compare the flipped
model to a traditional course, she sought to understand the relationship between student
perceptions of the flipped classroom and self-regulated learning behaviors, as well as how these
two variables related to student achievement. Student perception was measured using a custom
survey that assessed preference of video, value of video, viewing frequency, learning
enhancement, and value of active learning. Student use of SRL strategies was measured by the
MSLQ. The findings indicate that perception predicted self-regulation of cognition (i.e., study
strategies and metacognition), motivation (i.e., self-talk and interest enhancement), and behavior
(i.e., effort and help-seeking), but not environmental restructuring or self-consequating.
However, the degree of SRL strategy use was not predictive of course grade. Sletten suggests
that the sample size, 76 students, and lack of granularity in course letter grades as the
achievement variable may have contributed to this finding. This may very well be the case, but it
could also be that the assessments of achievement were not sensitive to the effects of SRL
strategy use, or there was simply no effect. Importantly, though, the findings do show that
student use of SRL strategies can be influenced by perceptions of the course design and
instructional methods.
The literature in this section demonstrates that SRL can be influenced by the course
context and is amenable to intervention (Bol et al., 2016; Connell et al., 2016; Corkin et al.,
2017; Pintrich & Zusho, 2007; Sletten, 2017; Steiner, 2016; Zusho, 2017). Further, the studies
discussed provide insight into which interventions have been successful. However, the broad
nature of the course designs and instructional methods introduces challenges. While some
researchers clearly indicate that a particular practice or strategy is intended to directly influence
APPROACHES TO SRL 28
SRL, others are less explicit or focus more on outcomes. Further, practices are often grouped and
expanded under the broader labels of active learning (Corkin et al., 2017), student-centered
(Connell et al., 2016), or flipped (Sletten, 2017). While this reduction may serve a practical
purpose, it makes it difficult to determine the contributions of specific components of the course.
The next section examines how others have attempted to classify, describe, and measure these
instructional practices in naturalistic settings, both broadly and in specific reference to self-
regulated learning.
Instructor Support for Self-Regulated Learning
Recent studies that have examined instructional practices in naturalistic settings have
moved away from dichotomous categorizations of active versus traditional or student-centered
versus teacher-centered, toward more complex and nuanced descriptions of teaching (Hora,
2015; Smith et al., 2014). Despite the increased granularity, however, very few studies have
attempted to explore the specific use of SRL-supporting or SRL-promoting strategies by
postsecondary instructors in naturalistic settings (Hoops et al., 2016; Khaled et al., 2016). Both
types of studies are discussed in this section.
To better understand the instructional practices in use within STEM courses at the
University of Maine, Smith and colleagues (2014) surveyed faculty and conducted observations
of 51 courses across 13 different STEM departments. The survey instrument used was the
Teaching Practices Inventory (TPI), which asks instructors to assess their use of a range of
instructional practices. Courses were observed following the Classroom Observation Protocol for
Undergraduate STEM (COPUS), which documents the behaviors of instructors and students in
two-minute intervals using a series of fixed codes. In analyzing the frequency of all codes for
each class, the researchers suggest that it is best to characterize teaching practices in these
APPROACHES TO SRL 29
contexts as lying on a continuum between what would be considered traditional and highly
interactive. This continuum captures aggregate time spent presenting content compared to the
amount of time spent guiding students through discussion and activities. Most instructors landed
somewhere in the middle of this continuum, suggesting that dichotomous categories of teaching
do not adequately represent the full range of instructional practices or even those of the majority.
It is worth noting that among the instructors who spent most of their time guiding students, they
engaged in a variety of practices, including: facilitating small groups, posing questions,
answering questions, and interacting with students one-on-one. Students spent time working in
groups or individually on problem-solving activities, asking questions, answering questions, and
engaging in whole class discussion. Although this study does not address self-regulated learning
directly, the research previously discussed has linked some of these more active instructional
practices to increased student use of SRL strategies (Connell et al., 2016; Corkin et al., 2017;
Sletten, 2017). However, the lack of specificity makes it difficult to understand the extent to
which SRL was considered by the instructors.
Hora (2015) also identified a broad range of instructional practices in his study of 56
science and engineering faculty, but is able to provide greater specificity through the application
of the Teaching Dimensions Observation Protocol (TDOP) and the Differentiated Overt
Learning Activities (DOLA) framework (Chi & Wylie, 2014). Hora’s findings indicate that
although lecturing is used extensively among those observed, most lectured for less than 20
minutes at a time with some regularly integrated small group work and other activities. Also
important to note is that in many cases the lecture appeared to serve as preparation for other
learning activities rather than serve as the primary mode of instruction. This highlights the
importance of capturing and retaining as much detail as possible rather than try to simplify
APPROACHES TO SRL 30
observations of this type to just lecturing. Another important aspect of this study was the use of
the DOLA framework, which categorizes student activity in a course as active, constructive, or
interactive (Chi & Wylie, 2014). Hora used this framework to interpret TDOP codes as follows:
student responses to instructors and engagement in problem-solving was considered active;
students asking novel questions or engaging in creative activities was considered constructive;
and students interacting with peers on creative activities was considered interactive. The active
category was most represented in the observations, while constructive and interactive were
relatively rare. This finding is particularly important as it demonstrates that even those students
who may have been engaged in small group learning or independent activities, were not
spending a significant portion of their time being constructive or interactive. Although Hora’s
study gets closer to identifying instructor use of SRL-supporting and SRL-promoting strategies
in naturalistic settings, his intent was to cover a broad range of practices and was not explicitly
focused on these areas.
In contrast, Khaled et al. (2016) did focus on SRL, although with a much smaller sample
and more limited context than those carried out by Hora (2016) and Smith et al. (2014). Khaled
and her colleagues sought to describe the occurrences and quality of teacher and student
strategies for self-regulated learning in hands-on learning simulations in vocational education
settings. Informed by the literature and Zimmerman's (2001) model of self-regulated learning,
they developed a theoretical framework composed of several strategies that instructors might use
to stimulate SRL, as well as student strategies for SRL. Based on their observations, Khaled et al.
found considerable variation in both instructor and student use of SRL strategies. In particular,
instructors frequently used modeling and scaffolding techniques, but the use of attributional
feedback and evaluation was much less prevalent. Students, meanwhile, often proposed methods
APPROACHES TO SRL 31
for task performance and sought help when needed, but were less likely to set goals, ask for
feedback, and engage in self-monitoring. Although the relevance of these findings to the present
study is somewhat limited in light of the sample and context studied, it is valuable for from a
methodological standpoint and represents one approach to understanding the use of SRL
strategies in an educational context.
Hoops and colleagues (2016) carried out a similar study, but focused exclusively on
instructional practices, rather than trying to capture both instructor and student behaviors. Also
critical in terms of relevance to the present study, their site and participants consisted of an
instructor and students engaged in a pre-calculus course at a large public research university. The
goal of their study was to understand what instructional practices were being used in this setting
that may influence students’ SRL. To answer this question, they developed the Self-Regulated
Learning Observation Protocol (SRLOP) and used it to guide the observation of several sessions
across two sections of the course. The protocol consisted of several categories across the four
domains of self-regulation as defined by Pintrich (2004). For cognition, they specifically
identified metacognition, test-taking strategies, information processing strategies, and advance
organizers. For motivation and affect, they included value and interest. The behavior section
consisted of help-seeking and time management. Lastly, for context, they specified student
responsibility, task difficulty, instructor feedback, and rules and management. Their analysis of
the observation data reveals that, in terms of frequency, the practices and behavior of the
instructor primarily support self-regulation of cognition. Within cognition, metacognition was
emphasized the most, followed by test-taking strategies. Behavior and context were roughly
equivalent in their representation, with strategies related to help-seeking and student
responsibility most prominent. Very few instructional practices and behaviors were coded as
APPROACHES TO SRL 32
supporting student regulation of motivation. While these results are interesting and addressed
their research question, they are limited by the small sample: two sections of the same course
taught by the same instructor. As with Khaled (2016), however, there is considerable value and
relevance in the methodology.
The existing literature on the nature of teaching in postsecondary institutions is much
more expansive than what has been discussed here. However, the studies selected represent key
methodological approaches that help inform the present study. They also offer some insights into
the degree to which self-regulated learning has been characterized in naturalistic studies of
instructional practices in postsecondary settings. Hoops et al. (2016) and Khaled et al. (2016)
offer the most direct examination of SRL, while Smith et al. (2014) and Hora (2015) only
considered it indirectly. What is clear from both sets of studies is that to adequately represent the
complexity of teaching, both the type and qualities of the instructional approach need to be
captured. It is also evident that further research is needed in this area.
Theoretical Model of Self-Regulated Learning
The previous sections reviewed recent empirical research on the nature of self-regulated
learning among college students, the relationship between SRL and the course context, and the
extent to which instructors in higher education settings may support and promote SRL in their
courses. The phenomenon of self-regulated learning has been conceptualized in these studies and
the broader literature using several different theories and models that attempt to describe the
processes through which individuals reflect on and guide their learning (Pintrich & Zusho, 2007;
Winne & Hadwin, 1998; Zimmerman, 2001; Zusho, 2017). These underlying concepts of self-
regulation are similar across most models. The differences are primarily in the conceptualization
of specific processes and their relation to one another.
APPROACHES TO SRL 33
The current study is guided by an integrated model recently proposed by Zusho (2017),
which retains many elements of the earlier model of self-regulated learning in college students
presented by Pintrich and Zusho in 2007. Zusho’s more recent model builds on this foundational
work and integrates key findings and concepts from the research on learning patterns (Vermunt
& Vermetten, 2004) and student engagement (Kahu, 2013), as well as broadens the definitions
and scope of motivation (Wolters & Hussain, 2015; Wolters & Benzon, 2013). It is not intended
to model all of the processes involved in learning and it is not expected that all individuals will
self-regulate their learning in all contexts. Rather, it defines the ways in which individuals may
choose to direct and control their learning, which varies by person and context.
The model of self-regulated learning proposed by Pintrich and Zusho (2007) includes five
major components: outcomes, motivational processes, self-regulatory processes, personal
characteristics, and classroom context. Self-regulatory processes are further broken down into
four phases: planning, monitoring, controlling, and evaluating. Within each of these phases,
regulatory processes can act within four different domains: cognition, motivation/affect,
behavior, and context. Zusho's revised 2017 model retains most of this structure while
integrating elements from other lines of research on self-regulation, as will be expanded upon
below.
Outcomes
Zusho’s 2017 model includes a revision of the previous outcomes outlined in the Pintrich
and Zusho 2007 model. The latter included four outcomes of motivational and self-regulatory
processes: student choice, effort, persistence, and achievement. These are represented in the 2017
model through achievement and engagement, as measured by effort, choice, and persistence. In
addition, Zusho includes understanding and academic risk-taking as outcomes. One reason this
APPROACHES TO SRL 34
was done is to differentiate between cognitive outcomes (i.e., understanding and academic
achievement) and behavioral outcomes (i.e., academic-risk taking and engagement).
Motivation
In the 2007 model, Pintrich and Zusho distinguished between efficacy and control beliefs,
values and goals, and affect and motivation. These are largely retained in Zusho’s 2017 model,
but are reformulated as four motivational constructs: competence, meaningfulness, autonomy,
and belonging. As with the 2007 model, these processes are said to influence outcomes directly,
as well as indirectly through regulatory processes. In turn, motivational process can also be
influenced by regulatory processes, as detailed below.
Cognition and Self-Regulatory Processes
Interacting with motivation at the core of the model are cognition and regulation
strategies. Critical to this is the use of specific cognitive strategies, such as rehearsal, elaboration,
and organization. Regulatory processes intentionally directed by an individual can guide the use
of these cognitive strategies, as well as motivation, behavior, and context. Zusho’s 2017 model
does not describe specific processes, but instead refers to the 2007 model. As an understanding
of these processes is essential for addressing the research questions, each will be defined below,
organized by phase. As Pintrich and Zusho note, not all of these processes are used by every
person for every task. Those that are used may not follow the order below. Rather, they are used
dynamically and even simultaneously as a given task unfolds.
Planning. The planning phase includes several processes within the domains of
cognition, motivation/affect, behavior, and context (Pintrich & Zusho, 2007). Planning of
cognition involves setting goals, activating prior knowledge, and activating metacognitive
knowledge. Planning with respect to motivation/affect includes adopting a goal orientation,
APPROACHES TO SRL 35
making judgments about efficacy, making judgments about the difficulty of the task, activating
task value, and activating interest. Planning of behavior is articulated as planning time and effort,
and making plans to observe one’s behavior. Lastly, planning as it relates to context can involve
student perceptions of the task and context.
Monitoring. The next phase is monitoring. Monitoring of cognition involves an
awareness of cognition (i.e., metacognition) as well as the use of activities to help judge one’s
learning and understanding (Pintrich & Zusho, 2007). Similarly, an individual can be aware of
and monitor their motivation and affect, as well as aspects of their behavior (e.g., effort, use of
time, and need for help). Students can also monitor the context for changes in the tasks or
characteristics of the given context.
Control. The third phase is control, and like the others, involves processes across all four
domains (Pintrich & Zusho, 2007). Controlling cognition includes selecting and using specific
cognitive strategies. Likewise, controlling motivation and affect involves selecting and using
strategies that can help influence motivation and affect. Attempts to control behavior may take
the form of a change in effort or persistence. It could also involve a student seeking help. The
context, too, could also be subject to control, such as attempts to re-negotiate tasks, change the
structure of the context, or leave the context altogether. However, in traditional educational
settings, many aspects of the context are not likely to be under the direct control of the student.
Evaluation. The fourth phase of self-regulation is evaluation, which involves reflection,
reactions, and judgments across the four domains (Pintrich & Zusho, 2007). Evaluation of
cognition involves reflection on and judgments about learning and performance, including
making attributions about poor or good performance. Good self-regulators tend to attribute poor
performance to specific strategy or time use rather than general ability. This is related to
APPROACHES TO SRL 36
evaluation of motivation, which can take the form of affective reactions to a particular outcome
or attribution. Evaluation of behavior may take the form of reflection on and judgments about
use of time, effort, and other behaviors. Lastly, a student may evaluate the task they were
engaged in or the context within which they were engaged.
Personal and Contextual Influences
Pintrich and Zusho (2007) identified several personal and contextual factors that may
influence motivation and self-regulation. Zusho (2017) retained most of these. However, citing
the work of Kahu (2013), Zusho reframed what was previously a series of linear interactions
with a more ecological model in which motivation and cognition are embedded in personal and
contextual factors with varying levels of influence. These can be proximal or distal factors, a
feature also found in Kahu’s model. All of this takes place within a particular sociopolitical
climate.
Personal factors. The personal factors that Zusho (2017) identifies as distal include age,
ethnicity, personality, and lifeload, the latter of which is intended to capture the multiple
pressures that may be exerted on a person at a given time (Kahu, 2013). The more proximal
personal factors, according to Zusho, include prior knowledge and beliefs about learning. This is
a significant change from the Pintrich and Zusho (2007) model, which only accounted for age,
gender, and ethnicity. The revised model reflects Zusho’s attempts to update the model and
integrate other lines of research on self-regulation.
Contextual factors. Pintrich and Zusho (2007) recognized the critical role of the context
in shaping self-regulated learning and Zusho carries this forward into the 2017 model. The
academic discipline, curriculum, and institutional support are considered distal contextual factors
in this model. Proximal factors include the course structure, academic tasks, instructional
APPROACHES TO SRL 37
methods, and instructor behaviors. These proximal contextual factors, which are largely carried
over from the 2007 model, serve as the focus of the current study and are described in greater
detail below.
Academic task. The content and characteristics of the specific academic tasks that
students are asked to perform can influence SRL (Pintrich & Zusho, 2007; Zusho, 2017). For
example, the content of the task may be of more or less interest to a student. It can also vary in
level of difficulty. The structure of the task, such as whether it is open-ended or closed, could
also influence SRL and motivation. The characteristics help shape how much choice a student
has, the extent to which self-regulation is promoted and supported, and the extent to which a
student may be motivated to engage in self-regulatory processes.
Reward and goal structure. Related to the characteristics of a given task, the reward and
goal structure of the broader context (e.g., a single course) can also have a role in SRL (Pintrich
& Zusho, 2007). The reward structure of a given class is primarily concerned with how grades
are earned and distributed and can be individual, competitive, or cooperative in nature. This is
also true for the goal structures, which Pintrich and Zusho (2007) define as “how students are
organized to accomplish the tasks” (p. 796). They suggest that cooperative approaches can be
beneficial, but that students should still be required to produce something that is graded
independently.
Instructional methods and behaviors. In addition to the structures and characteristics of
the course and tasks, the specific instructional methods and behaviors of an instructor may
influence student motivation and learning (Pintrich & Zusho, 2007; Zusho, 2017). As Pintrich
and Zusho (2007) elaborate, however, it is not as straightforward as saying that small cooperative
groups are more motivating than lecture, as each can act on different components of motivation.
APPROACHES TO SRL 38
Small groups may offer more choice and autonomy, but a well-delivered lecture may trigger
situational interest. Conversely, both methods could negatively impact student motivation and
learning if poorly designed and facilitated. The authors suggest that rather than focus solely on
the type of instruction, the quality of the instructional methods and behaviors must also be
considered with respect to specific components of motivation.
As Zusho (2017) points out, these contextual factors do not operate in isolation. They
work in concert with personal factors to influence motivation and self-regulation. Motivation and
self-regulation also interact with each other while serving a mediating role between the person,
the context, and the outcomes discussed above. Zusho’s integrated model, and prior work by
Pintrich and Zusho (2007), provides a strong foundation for understanding self-regulation in
general college contexts and serves as the core component of the conceptual framework for the
current study, as described in the following section.
Conceptual Framework for Study
In qualitative research, a conceptual framework is often used to guide the design and
implementation of a study (Maxwell, 2013). It is created from a combination of existing theories
and research, as well as the personal experiences and expectations of the researcher. It contains
the fundamental concepts and relationships that help inform methodological decisions and
subsequent data gathering and analysis. The conceptual framework guiding this study, depicted
in Figure A, is rooted in the model of self-regulated learning developed by Pintrich and Zusho
(2007) and recently revised by Zusho (2017). Using both of these models provides the
combination of broad coverage of SRL concepts and the more detailed depiction of contextual
factors that are needed to hone in on teaching practices. These details are further enhanced by
APPROACHES TO SRL 39
findings from the recent empirical studies of SRL that were examined earlier in this chapter and
which have been summarized in Appendix A.

Figure A. Conceptual framework.
The major components of the conceptual framework include the following: the instructor
and assistants (e.g., teaching assistants, peer learning assistants, readers); the students; course
design and facilitation; student motivation, cognition, and self-regulation; and outcomes. A
critical feature of theoretical models of SRL (Pintrich & Zusho, 2007; Zusho, 2017) is the
mediating role that motivation and self-regulation have between the student, the context, and the
outcomes. This is depicted in the conceptual framework by directional arrows, and in particular,
APPROACHES TO SRL 40
the lack of a direct line between students, course design and facilitation, and the outcomes. The
directional arrows also indicate the recursive nature of SRL, whereby the outcomes impact both
the students and the instructor.
As this study is concerned with instructional practices that support the use and
development of SRL, the personal factors and the distal contextual factors from the theoretical
model are deemphasized. While it is important to acknowledge their role in SRL, trying to cover
all aspects of the SRL model is beyond the scope of this study. Rather, the goal is to achieve an
in-depth understanding of the course structures, academic tasks, instructional methods, and
instructor behaviors in use in naturalistic settings
As discussed previously in this chapter, the Pintrich and Zusho (2007) and Zusho (2017)
models lack specificity with respect to the instructional factors that may promote the use and
development of SRL in college students. They focus primarily on characteristics of the tasks and
instruction, such as level of difficulty, student choice, situational interest, and grading structures.
While this provides a good starting point, the empirical research discussed throughout this
chapter offers more concrete examples. A summary of these practices is provided in Appendix A
and also helps guide the study.
Another area where the models proposed by Pintrich and Zusho (2007) and Zusho (2017)
lack specificity is in accounting for regulation in peer learning settings. Given the increasing
prevalence of collaborative and cooperative learning activities in undergraduate courses (Eagan
et al., 2014), this is an important area to examine. Järvelä and Järvenoja (2011), for example,
found that motivation regulation can be socially constructed when students are working in
groups. In a later study, Järvelä, Järvenoja, Malmberg, and Hadwin (2013) were able to identify
different patterns of regulation during collaborative learning activities that were associated with
APPROACHES TO SRL 41
high performing and lower performing groups. A recent review of this area of research by
Schoor, Narciss, and Körndle (2015) suggests there may be multiple modes of regulation that
occur in peer learning settings, with important differences emerging between individual self-
regulation and socially share regulation of learning. For example, individual members of a group
may regulate toward their own goals, toward established group goals, or a combination of the
two. Although the current study is not focused on socially shared regulation, any interpretations
about SRL in peer learning settings should bear in mind the additional social factors that may be
involved, as highlighted in this recent line of research.
Summary
The recent empirical research on self-regulated learning explored in this chapter suggests
that SRL varies by student and context, that students may not develop more adaptive approaches
on their own, and that specific course-level interventions may help address this lack of growth.
This chapter also reveals limited empirical evidence of how teaching practices in more typical,
non-experimental settings may reflect support for SRL. The research reviewed in this chapter
and the theoretical models of SRL developed by Pintrich and Zusho (2007) and Zusho (2017)
suggest possible avenues and approaches to addressing this gap. This literature and the
conceptual framework derived from it guided the design and implementation of the study, as
discussed in detail in the following chapter.
APPROACHES TO SRL 42
CHAPTER THREE: METHODOLOGY
The purpose of this study was to explore how a group of faculty at a public research
university support and encourage self-regulated learning (SRL) in their undergraduate courses.
As described by theoretical models of SRL and empirical research, personal factors and
contextual factors can often contribute to this variability (Bol et al., 2016; Connell et al., 2016;
Corkin et al., 2017; Pintrich & Zusho, 2007; Sletten, 2017; Steiner, 2016; Zusho, 2017). This
study was most concerned with contextual factors, particularly those that are within the control
of faculty. This includes course design, instructional methods, and to a certain degree, instructor
behaviors. The following research questions and the conceptual framework discussed in previous
chapter guided the study:
1. How are a group of RVU faculty experiencing variability in self-regulated learning
among the undergraduate students that they teach?
2. What teaching practices are these faculty using that may encourage and support self-
regulated learning?
3. What are faculty perceptions of the effectiveness of these teaching practices?
This chapter provides an overview of the research design, sampling strategies, instrumentation,
data collection, and data analysis methods that were used in this study.
Research Design
This study followed a qualitative case study design. Qualitative research can help address
questions about process and meaning (Maxwell, 2013). This methodology is also helpful when
there is little existing information and rich descriptions of a particular phenomenon are needed.
This aligned well with the purpose and research questions of this study, which was focused on
documenting in detail the perceptions and teaching practices of a small group of faculty. Given
APPROACHES TO SRL 43
limited existing research on this topic, it was important to use a methodology that would not be
restricted to only assessing known practices, but that would allow for the discovery of new
practices or unique variations of a known practice. A quantitative survey design likely would not
have achieved this same depth or captured the emergent themes. An experimental design would
also have been inappropriate, as the goal of this study was not to test the effectiveness of these
practices. Rather, it was to document and understand what was happening in naturalistic settings
with minimal intervention. That being said, the findings from this study may help identify areas
for such efficacy research in the future.
Sample and Population
Merriam and Tisdell (2016) provide a helpful distinction between two tiers of sampling:
selecting a site to study and then selecting participants within that site. To effectively study the
research questions, it was important for the site to be accessible and for there to be a strong
likelihood of SRL-supporting practices being used. A large public research institution located in
the western United States, Riverview University (RVU), was selected based on these two factors.
I was able to gain access to the institution and, based on information available at the site, I was
able to determine that some degree of SRL-supporting practices were being used.
The second tier of sampling, selecting participants, was informed by the existing data at
the site, which included self-reported instructional practices of several faculty. The purpose of
this study was not to characterize or evaluate the teaching practices across the entire institution,
for which a typical or maximum variation sample would have been needed (Merriam & Tisdell,
2016). Instead, the goal was to understand how instructors who use SRL-supporting strategies
are doing so. This required a unique sample, purposively selected based on their use of
instructional practices. Although the existing data did not explicitly include references to SRL, it
APPROACHES TO SRL 44
did provide some insight into the instructors’ use of active and collaborative learning strategies,
as well as their overall approach to teaching. Based on these criteria, approximately 40 faculty
were contacted by email to inquire about their interest in participating in the study, with the goal
of obtaining four to six participants. As part of this email, participants were provided with the
study information sheet found in Appendix H, explaining the nature of the study, what they
would be asked to do if they participated, and what they could expect regarding confidentiality.
At the conclusion of the recruitment period, five participants had been selected, as detailed in the
next chapter.
Instrumentation
To fully address the research questions and ensure the findings were well triangulated,
three qualitative methods were used for this study: interviews, observations, and artifact analysis
(Maxwell, 2013; Merriam & Tisdell, 2016). Two interview guides were created, one for
interviews to be held at the beginning of the study term, and the other for interviews held at the
end. Both sets of interviews followed a semi-structured approach that provided a moderate
degree of structure through the use of pre-established questions, but also allowed for deviations
and a more natural conversation. This approach enabled emergent concepts that were not fully
captured in the interview guide to be discussed and explored (Patton, 2002).
Both interview guides were informed by the conceptual framework presented in the
previous chapter, which was based on the theoretical models of SRL proposed by Zusho (2017)
and Pintrich and Zusho (2007). In particular, the distinction between four different domains of
SRL (i.e., cognition, motivation, behavior, and context) was helpful in dividing the broader
concept of SRL into smaller components that could more easily be discussed and with which the
participants were more familiar. Incorporating these concepts, the first interview guide focused
APPROACHES TO SRL 45
on participants’ previous experiences with the courses they were teaching that term, including
their perceptions of students’ self-regulated learning and how the participants developed,
implemented, and revised their instructional strategies. The second interview guide, used toward
the end of the term, also incorporated these SRL domains, focusing specifically on the
experiences and perceptions of the participants during the study term. The questions centered on
the participant's judgments about how SRL unfolded during the course and how their
instructional approaches may have contributed. A copy of the interview guide for the first
interview can be found in Appendix C and the second in Appendix E. The research alignment
matrix in Appendix B indicates which interview questions were intended to help answer the three
research questions.
The conceptual framework and theoretical models of SRL (Pintrich & Zusho, 2007;
Zusho, 2017) also informed the class observations. These took place between the two interviews
and were used to gain a first-hand account of the teaching practices used by the participants. The
observation protocol, provided in Appendix D, contained a note-taking section with areas to
write the current time, descriptions of what was taking place, and observer comments. Following
the note-taking section was a summary of practices identified in the literature and theoretical
models that may support and encourage SRL. These served as a reference to help guide my focus
while I took field notes on the instructional methods and behaviors I observed. Similar to the
interviews, this approach provided a degree of structure without confining me to only a pre-
determined set of codes (Bogdan & Biklen, 2007; Merriam & Tisdell, 2016). This was critical to
the overall research design, as the intent of the study was not only to determine whether a
particular practice identified in the literature was present, but also to capture how it was
implemented and to potentially identify novel or related practices.
APPROACHES TO SRL 46
Data Collection
Data was collected utilizing the interview guides and observation protocols discussed in
the previous section. Both rounds of interviews were held in the offices of the participants, with
each lasting about 30 to 60 minutes. Following the semi-structured approach, I asked the
participants a series of questions from the interview guides, following up with probing questions
when appropriate. In the second round, specifically, these follow up questions were used to
inquire further about practices that I observed in the classroom and responses from the first
interview that needed further clarification or elaboration. As expected, in both rounds of
interviews, the conversations drifted from the questions at times and some questions were
addressed in the context of the participants’ responses to the others. All of the interviews were
recorded for later analysis using a standalone voice recorder. I also took field notes to document
items to follow up on and to capture my own thoughts, reactions, and reflections during the
interview.
The class observations were scheduled in consultation with the instructor, with the goal
of identifying class sessions that utilized instructional methods and activities that were more
closely related to self-regulated learning. Two class observations were completed for each
participant, with the exception of one instructor, who taught a three-hour class once a week. The
other observations ranged from 50 minutes to 80 minutes. Following the observation protocol
described in the previous section, I took continuous field notes on the participant’s teaching
practices and behaviors, including his/her speech and actions. As the observations were not
recorded, I also wrote down relevant quotes to the degree that it was possible. My observations
were guided by the focus areas listed in the observation protocol, as well as the broader
conceptual framework of the study. Observations of the students and environment were included
APPROACHES TO SRL 47
when relevant to the instructional practices being documented, such as students asking and
answering questions. However, the purpose of this study was not to measure or assess SRL
among students directly, but to describe and analyze instructional practices. Thus, the
observation of the instructor was prioritized above everything else. As with the interviews, I
captured my thoughts, reactions, and reflections in my field notes as observer comments while
conducting the observations. As well as contributing to the overall analysis, these field notes and
comments helped identify case-specific questions and broader themes that I followed up on
during the second interviews.
In addition to the interviews and observations, I requested the course syllabus from each
participant and retained copies of any documents and activities distributed during the class
sessions I observed. The syllabi, in particular, were important supplements to the data gathered
through interviews and observations. As will be discussed in the next chapter, they helped
confirm and clarify data captured during the interviews and observations while also offering
novel information not found using the other two methods.
Across the three methods, data was captured electronically (e.g., audio recordings and
electronic documents) and physically (e.g., handwritten notes and copies of documents). Physical
data and recording devices were kept in a secure location during and after the study period.
Electronic data was secured under password-protected accounts and de-identified whenever
possible. Pseudonyms for the institution and all participants have been used in place of real
names.
Data Analysis
As is a common practice in qualitative research, I began lightly analyzing the data during
the data collection period (Bogdan & Biklen, 2007; Merriam & Tisdell, 2016). Although I did
APPROACHES TO SRL 48
not modify the research design or instruments during this time, as sometimes occurs in
qualitative research, I did incorporate emergent concepts into some of the probing questions I
asked participants during the second interviews. For example, for each participant, there were
certain teaching practices and behaviors that I noted in the observations or activities or grading
policies detailed in the syllabus about which I wanted to gain their perspective. For the most part,
these were brought up directly by the participants in response to the questions in the interview
guide, but on a few occasions, I asked about them directly in the follow-up questions.
Following the second round of interviews, which concluded the data collection period, I
moved forward with the full analysis. My overall approach was informed by the constant
comparative method, which involves a involves a series of iterative processes in which data is
coded, grouped, and analyzed for themes (Corbin & Strauss, 2008; Merriam & Tisdell, 2016). To
help track the sources and codes during the analysis process, I used QSR International's NVivo
11 qualitative data analysis software. Although this software features a broad range of tools, I
limited my use to only applying codes to the sources and running queries on selected codes to
recall specific excerpts from the sources.
To begin the coding process, I first added all of my sources to NVivo. This consisted of
transcriptions from the interviews, field notes from the interviews, field notes from the
observations, and the course documents. I also populated NVivo with an initial set of a priori
codes developed from the conceptual framework, literature, and theoretical models of SRL
(Pintrich & Zusho, 2007; Zusho, 2017). A copy of these initial codes is provided in Appendix F.
Before starting the more granular coding process, however, I read through all of the sources and
segmented the data into three large chunks that reflected the different research questions:
instructor perceptions of students and SRL; instructional strategies; and, instructor perceptions of
APPROACHES TO SRL 49
implementation and effectiveness. I also developed a brief summary of each case that contained
relevant context that would be important for my analysis, such as how many times a participant
taught the course and how much control they had over the curriculum. With this information in
hand, I then worked with one of these segments at a time across all cases, which helped make the
coding process more manageable.
For each segment, I began coding the data in NVivo with the previously mentioned a
priori codes. Following an open-coding approach, I also developed new, emergent codes and
revised the a priori codes as I went through the coding process. These changes are reflected in
the final codebook found in Appendix G. This was a valuable approach as the a priori codes were
insufficient to capture the nuance and range of concepts in the data. During the coding process, I
also made several separate jottings, noting the broader themes and concepts that seemed to be
emerging from the data (Miles, Huberman, & Saldana, 2014).
After the initial coding process, which was focused primarily on summarizing the data
using concrete, descriptive codes, I employed several of the analytic tools recommended by
Corbin and Strauss (2008) to further analyze the data within and across each case. These tools
offered different approaches to probing, comparing, contrasting, and grouping data that helped
clarify concepts and draw out patterns, themes, and relationships. Using these approaches,
particularly the constant comparison strategy, I began grouping codes into broader categories.
For example, an occurrence of one participant using controversy to generate interest and the
occurrence of another participant stating the value of a particular topic would both be grouped
under the motivation category. Similarly, a participant expressing uncertainty about how much
help to give to students and another participant discussing students’ need for structure would be
grouped under a category of responsibility for learning.
APPROACHES TO SRL 50
This iterative process of comparing, grouping, and sometimes splitting up codes and
pieces of data continued for several rounds as I developed themes and then validated them
against the data. NVivo aided this process by making it possible to quickly display all of the data
associated with one code or a specific combination of codes. Throughout this process, I also
regularly consulted my conceptual framework, the theoretical models of SRL, and the empirical
literature to compare my findings with existing conceptualizations of SRL. This was critical as
my research questions center on the relationships between instructional factors and student
regulation of their learning. Although the intent of this study was not to confirm this relationship
empirically, I needed to maintain that conceptual lens as I interpreted the data. The conceptual
framework was also helpful in highlighting areas that were absent from the data that I may not
have otherwise considered significant.
After establishing the broader themes and categories, I incorporated them into a series of
assertions, statements that synthesize several analytic findings, that addressed the research
questions (Miles et al., 2014). I refined these assertions by once again going through the data
and, in particular, assessing the significance of any negative examples that did not support the
assertions. I also examined different sources for the same participant (e.g., interviews,
observations, and documents) for agreement and supporting evidence within each case, an
advantage of the triangulated research design. The results of this analysis are presented in the
following chapter.
Credibility and Trustworthiness
During the data collection and analysis process, I took several steps to ensure credibility
and trustworthiness. An important component of this is being aware of researcher reflexivity
(Maxwell, 2013; Merriam & Tisdell, 2016). In qualitative research, the researcher plays an active
APPROACHES TO SRL 51
role in interpreting the data and thus, any biases the researcher has may influence this process.
These biases cannot be completely eliminated, but can be managed by ensuring that they are
acknowledged in both data collection and analysis. I did this through the use of observer
comments in my field notes and reflective memos.
The use of multiple data gathering methods—interviews, observations, and artifact
analysis—also helped maintain credibility and trustworthiness by enabling me to triangulate my
findings (Maxwell, 2013; Merriam & Tisdell, 2016). In many cases, I was able to confirm and
better understand the teaching practices that participants discussed in the interviews by observing
them directly in the classroom or reading the details contained in the course documents.
Conversely, the observations and documents helped me probe deeper during the interviews into
practices that participants did not initially discuss. Consistent coding across all of these data
sources and the use of recording devices contributed to this as well.
Credibility and trustworthiness can also be ensured by protecting and providing visibility
into the chain of data collection and analysis (Maxwell, 2013; Merriam & Tisdell, 2016). This
audit trail makes it possible to trace all of the themes and assertions presented in of the study
back to the original data. This will be demonstrated through the use of thick descriptions in the
written findings contained in the next chapter.
Timeline
Data collection for this study took place between January 2018 and April 2018, as
reflected in Table 1. This table also summarizes the events that took place prior to and after the
data collection period.

APPROACHES TO SRL 52
Table 1
Timeline of Events
Month and Year Events
August 2017 Study approved by dissertation committee
September 2017 Study approved by USC IRB
December 2017 IRB reliance agreement between USC and RVU approved
Recruitment of study participants began
January 2018 Recruitment of study participants completed
Data collection began
April 2018 Data collection completed
June 2018 Analysis and preparation of findings completed

APPROACHES TO SRL 53
CHAPTER FOUR: FINDINGS
The purpose of this study was to explore how a group of faculty at Riverview University
(RVU) support and encourage self-regulated learning (SRL) in their undergraduate courses.
Specifically, the study addresses three research questions:
1. How are a group of RVU faculty experiencing variability in self-regulated learning
among the undergraduate students that they teach?
2. What teaching practices are these faculty using that may encourage and support self-
regulated learning?
3. What are faculty perceptions of the effectiveness of these teaching practices?
The chapter presents the findings of the study for each research question. Thick descriptions,
including verbatim quotes and portions of my field notes, are used to ensure that the voices of the
participants are well represented and to provide visibility into the evidence I used to develop and
support my assertions.
Summary of Cases
The cases explored in this study consisted of five faculty at Riverview University (RVU)
and their respective courses. As detailed in Table 2, the faculty that participated in the study are
primarily from STEM disciplines and are tenured or tenure-track professors and lecturers with
multiple years of teaching experience. All participants indicated they had some degree of
familiarity with the literature on postsecondary teaching, including active learning and
discipline-based educational research (DBER). One participant, Alice, indicated she had
participated in professional development opportunities related to these topics, which briefly
touched on self-regulated learning. Others were somewhat familiar with SRL conceptually, but
did not make reference to specific models. Instead, they tended to focus on specific components
APPROACHES TO SRL 54
and related concepts, such as motivation, understanding, engagement, learning skills, study
strategies, and time-on-task.
Table 2
Summary of Participants
Name (Pseudonym) Discipline Appointment Type
Alice Social Sciences Tenured Professor
Jane Biological Sciences Tenured Lecturer
Kate Physical Sciences Tenured Professor
Parker Physical Sciences Tenured Lecturer
Reed Biological Sciences Tenure-Track Lecturer

Further details about the participants’ backgrounds have been omitted to help protect
their anonymity. However, relevant information about the courses selected for the study are
provided in Table 3. The courses ranged in size from approximately 25 students to 350 students,
with most having over 100 students. As noted in the table, some of the instructors designed their
courses and had considerable control over them, while others were constrained by needing to
cover specific topics to make sure the courses aligned with a course sequence or adequately
addressed important prerequisites. All participants had at least three years of experience teaching
their courses, with most having experience well beyond that. This additional context was helpful
in interpreting the participants’ perceptions of self-regulated learning, implementation of specific
practices, and the effectiveness of those practices.
As detailed in Table 4, all participants completed both interviews, which ranged from 28
minutes to 60 minutes. A total of 424 minutes were transcribed and analyzed. Representative
quotes from these transcriptions are provided throughout this chapter. The class observations
ranged from 50 minutes to 170 minutes, resulting in a total of 630 minutes of observations. I
APPROACHES TO SRL 55
took handwritten field notes during the observations, but did not record audio or video. These
were later typed up and added to NVivo along with the interview transcriptions and course
documents that were collected.
Table 3
Summary of Case Contexts
Participant
Class Size
(Rounded)
Course
Level Control over Course
Experience
with Course
Alice 25 Lower
Division
Shares common topics with other sections
of course, but participant has control over
instructional methods and assignments
10+ years
Jane 300 Upper
Division
Developed course and has ongoing control
over instructional methods and
assignments
10+ years
Kate 325 Lower
Division
Course is part of a sequence and must
cover specific topics; participant has
control over instructional methods and
assignments
3+ years
Parker 350 Lower
Division
Course is a prerequisite for others and
must cover specific topics; participant has
control over instructional methods and
assignments
10+ years
Reed 125 Upper
Division
Developed course and has ongoing control
over instructional methods and
assignments
5+ years

Table 4
Summary of Interviews and Observations
Interviews Observations
Participant First Second Total First Second Total
Alice 54 min. 60 min. 114 min. 170 min. -- 170 min.
Jane 37 min. 60 min. 97 min. 50 min. 50 min. 100 min.
Kate 43 min. 42 min. 85 min. 80 min. 80 min. 160 min.
Parker 40 min. 28 min. 68 min. 50 min. 50 min. 100 min.
Reed 32 min. 28 min. 60 min. 50 min. 50 min. 100 min.
Total 424 min. 630 min.
APPROACHES TO SRL 56
Faculty Perceptions of Self-Regulated Learning in Their Courses
The first research question asks: How are a group of RVU faculty experiencing
variability in self-regulated learning among the undergraduate students that they teach? Based on
previous research, it was expected that faculty would encounter variability across the different
domains of SRL (Dye & Stanton, 2017; Park et al., 2012; Sebesta & Bray Speth, 2017; Verrell &
McCabe, 2015). Through the use of interviews, the intent of this component of the study was to
confirm whether or not participants encountered this variability and to understand how they
experienced it and interpreted it.
As expected, all participants expressed encountering variability in student self-regulated
learning in their courses. As the interview questions deconstructed the broader concept of SRL
into the different domains (i.e., cognition, motivation, behavior, and context), participants
responses focused on one or more of these areas. Three themes emerged that reflect these
domains: challenges with performance orientation, differences in effort and time use, and
differences in metacognition and metacognitive knowledge.
Performance Orientation
Participants expressed a range of motivation in their students, but emphasized particular
challenges with students’ preoccupation with grades. Alice, a tenured professor from the social
sciences, captured this sentiment well in the second interview, stating that:
I face a couple things, like one is confronting that their motivation, at least initially… is
just to get an A and figure out what it takes to get an A. My hope is over time they
become motivated to learn something, and they do, but that initial motivation is almost
across the board grade-driven.
APPROACHES TO SRL 57
Jane, who teaches upper division courses in biological sciences, expressed a similar challenge,
further elaborating that part of the grade focus appears to be an expectation among her students
that their grade will reflect the time and effort they put into the particular assignment:
I'm getting here at the end of the quarter. I'm getting the same sort of thing coming out, is,
you know, students that obviously have not listened to certain things, they're saying: well
my assignment one…well, you know, I really worked really hard on that, can you change
the grade? It's never I did a really good job. It's always I really worked hard on it.
While Alice and Jane’s comments are focused more on general motivation than regulation of
motivation, they expressed an interest in moving students toward a motivation to learn, rather
than just to obtain a grade. They also highlighted variability in motivation, with students some
students shifting motivation during the course.
Reed, who was also teaching an upper division course in biological sciences, expressed
encountering variability in motivation as well, but offered a somewhat different perspective:
I think the vast majority are highly motivated and they put in a lot of effort. I get that
feeling from their performance in class. I see, usually, the really high clicker responses.
Then there's the days when they’re not so high and I think, oh, well, it's week five, there's
also two other exams this week. So, you can get the feel for when they're getting busy,
but…from talking to them too… many of the students are going to medical school, PA
school. I get asked for a ton of reference letters at the end. So, I mean, they're there for a
reason, because no one has to take this class. It’s an optional class, but they’re either
highly motivated to learn about the human body or they need it as a prerequisite to get to
a career that is a highly competitive career. So…they have to have some level of
motivation to get there. But again, I can see that because they're doing their work. They're
APPROACHES TO SRL 58
asking good questions. They're doing great with the clickers. In lab, my TAs tell me they
have, you know, great questions, they're always working hard, and they're there the whole
time.
There are a few things worth noting here. First, as Reed points out, some students appear to be
motivated to learn the subject while others see it as necessary to their career. Second, there
appears to be some variability across most students during the quarter, suggesting that contextual
factors may be involved, such as upcoming exams. Third, Reed seems to indicate that both
sources of motivation are contributing to productive effort.
Effort and Time Use
As noted within the context of motivation, another area where participants noticed
variability in their students is in their overall effort and strategic use of time. One component of
this seems to be student expectations at the beginning of a course based on their previous
experiences. Reed mentioned a particularly illustrative example of this in the first interview:
I think a lot of it comes down to time management, you know, are you willing to put the
time in? Are you able to regulate what's going on every day to prepare adequately for the
class? …I had a student this quarter on our discussion board said, you know, I'm
assuming this class is like other ones here where all I need to do is download the lecture
slides. So, when are you going to post them so I can look at them?
For Kate, who teaches a range of courses in physical sciences, the differences in effort and time
seem to be particularly challenging around strategic use of time. As she discussed in the first
interview, despite incentives in the form of grade points, she still struggles with getting some
students to engage in important aspects of the course:
APPROACHES TO SRL 59
You know, I give…20% credit for doing the homework, class participation, and clickers
and stuff. That's, you know, the exams is 55% of grade and all these other things
that…you would think, if you just put in the work, is easy to do—45% of the grade. But,
a lot of students just don't do it.
Both Kate and Reed indicate that some students may not be directing their time and effort in
adaptive ways, a key component of self-regulated learning (Pintrich & Zusho, 2007; Zusho,
2017).
Jane also encountered challenges with student effort that seemed to persist across the
term and extended beyond just time use. As she described in the first interview, some of her
students push back and try shifting responsibility:
I've taught for so long, but I'm feeling…this cohort coming in, where…they're not
holding themselves accountable more and more than I've seen before. It's…my fault that I
didn't do this. It's never I forgot to hand this in. It's my fault that I didn't remind them 12
times and, you know, I have plenty of reminders on those things. So, I’m feeling this kind
of push going back, because I want them to mature, but yet, I don't want them to fail. I'm
feeling…like I'm actually handholding more than I've ever done before
Particularly noteworthy here is that Jane indicates that the problem appears to be more prevalent
than in the past. She also expresses some unease about how much handholding has been needed,
a tension that will be explored further later in this chapter.
Metacognition and Metacognitive Knowledge
The third area where participants indicated that they are seeing differences in student
SRL is metacognition and metacognitive knowledge. Some students appear to have a range of
APPROACHES TO SRL 60
strategies and are able to adapt to different contexts. Alice captured this sentiment well in the
first interview:
Some of it is, they have different levels of preparedness and they are self-learners and
they'll go figure it out. And it's kind of irrelevant what I do. I mean, I could be a good
teacher or bad teacher, I could engage them, I could bore them, but they're going to go
master it and learn it, because that's how they already come to me. And I have no
illusions that those folks really, you know, whether I'm doing content transmission,
whether I'm facilitating a learning environment, all those things we talked about, these
folks are so ambidextrous in terms of their learning.
At another point in the interview, however, Alice suggested that other students may be using
counterproductive strategies such as “rotely reading and underlining” and that students “come in
not knowing how to learn.”
Parker, who was teaching a lower division sequence in physical sciences, also
commented on this variability. During the first interview, he talked about his experiences with
the approaches students might take during the course:
A lot of students coming in, what they've learned in high school is just to memorize and
you know they're…given study notes and they just study what's in the notes or they’re
given sample tests…so it's more driven that way. What we have to make clear is
chemistry is very conceptual and it's not about memorizing and reproducing stuff, but it's
about applying it and solving problems. And the emphasis is, from their perspective, it's
giving a problem and coming up with a creative answer on their own.
Similar to Alice, Parker also commented that his “experience has been that these [students] are
actually extraordinary that…every year the pool of students we’re getting is improving.” What
APPROACHES TO SRL 61
Parker and Alice appear to be saying is that although the students entering the institution are very
capable, there are segments of that population that may not have the metacognitive knowledge
that they need or may not be effectively applying the knowledge that they do have.
Faculty Approaches to Encouraging and Supporting SRL
The second research question asks: What teaching practices are these faculty using that
may encourage and support self-regulated learning? Having described how the participants are
encountering variability in SRL, this section examines and provides evidence of the instructional
strategies they are using that may be related to SRL. Importantly, this section is not an
exhaustive report of every teaching practice discussed in the interviews, observed in the
classroom, and found in the course documents. Rather, these are the most representative of those
practices that relate in some way to self-regulated learning.
The approaches that participants took can be loosely grouped into two categories.
Included in the first category are those approaches that directly related to self-regulation
processes, such as explicit instruction and opportunities to practice with specific processes,
skills, and strategies. The second category encompasses the broader teaching practices that may
create conditions to support and encourage SRL, such as statements made in class, how grades
are given, the overall structure of the course, and the nature of specific activities and
assignments. It is important to note that the boundaries around these two categories are not
entirely distinct and reflect my interpretation of the data and theoretical models of SRL.
Directly Suggesting and Teaching SRL-Related Strategies
All participants attempted in some way to influence self-regulated learning by suggesting
or sometimes directly teaching a strategy related to SRL. Some of these could be considered
strategy hints or suggestions, as they were not something students were required to do. Although
APPROACHES TO SRL 62
less frequent, there were also occurrences of some participants teaching a related skill or strategy
and requiring students to practice them.
Strategy hints and suggestions. Participants provided hints and suggestions around
several strategies. During my observations of Alice and Parker, I noted that they both made
statements about using quizzes as opportunities for students to assess their own learning and
make changes accordingly. Alice called them “a good litmus test” while Parker suggested to
students that if they did not do well on the midterm exam, it was an indication that they may
have to make some changes and that they should use weekly quizzes to determine if their
strategies are working. Reed also emphasized self-assessment, but beyond the required course
quizzes, he recommended to students to use flashcards and practice exams.
Parker and Reed, as well as Kate, also gave students suggestions for how to read their
textbooks. In the second interview with Kate, who was teaching a lower division physical
science course, she mentioned the following:
If they do read it, they read it…I tell them…like a newspaper, you know, just scanning,
that they're not actually understanding what it's saying to them. So, it's not enough just to
look at the problem, you have to really understand, okay, how did they go from line one
to line two to line three? What is the intermediate steps? But I always tell them, if you did
it, if you did it for the example problems, you have what you need to do your homework.
There's nothing extra that you need.
Parker, who was also teaching a lower division course, suggested to his students that they should
use the textbook as a reference book rather than try to read through all “1500 to 200” pages cover
to cover, adding that they should follow his guidance and lectures for how to study. Reed, who
APPROACHES TO SRL 63
was teaching an upper division biology course, took a somewhat different approach and provides
some of this direction in the form of a reading guide:
What I wanted them to do and what I hope they did, and what I can see them doing to
learn is…to, you know, really [become]…self-regulated learners. So, they're going to be
doing the work on their own at home before class, practicing in class, and then working
more afterwards. And so, how they did that? You know, I provide the reading guides for
them to help them structure their…reading experience so they can answer questions as
they go. I can be transparent with them. So, they know what I want them to be able to
pull out of the reading.
Reed also suggested to his students that they markup areas of confusion while reading so that
they can come back to them later and reassess their understanding, particularly when studying
for an exam. While in some ways these practices can be interpreted as the instructor helping to
regulate student cognition and behavior, exposure to these practices might help students develop
strategies that can be transferred to other courses and contexts.
Strategy instruction and practice. On several occasions, participants went beyond
strategy suggestions to explicitly teaching strategies and requiring students to practice them.
Reed, for example, stated that in his freshman courses he requires students to complete a self-
reflection form containing questions about study habits and devotes a “whole class period to
study skills and time management and how college is different from high school.” He also has
students practice with specific study strategies, such as labeling a diagram from memory,
suggesting to them that it is “a model of what I think of as good studying practice.” In reflecting
on these during the second interview, Reed had the following to say:
APPROACHES TO SRL 64
I think, as a lot of things in life, is you don’t really want to do it unless you own it. And
someone can tell you this is a good thing to do, but…then you gotta try it yourself. Then
go, oh actually this is a good thing…So yeah, I just kind of lay it out there and say hey
guys, here's what we know works. Here's all these resources. I'm going to assign some of
them to you, because I want you to do them and be prepared. But there's a bunch more
that, if you choose, hopefully will help you.
Worth noting here is that students were required to practice some of the strategies at least once,
but afterward, were able to choose to continue or discontinue use of the strategy.
Jane also required students to practice with SRL-related strategies in her upper division
biological sciences course. This description from my field notes for the second observation
captures one of these occurrences, including a reference to Chickering and Gamson's ( 1987)
principles for undergraduate education:
The instructor is reviewing the seven principles of undergraduate education with the class
that she went over at the beginning of the term. She goes through the principles first and
reflects out loud about how she contributed to these. She then puts up a slide listing the
course goals and asks students to reflect in small groups on how much progress they have
made on these goals. One student from each group is asked to go to the front of the class
and write in their group’s responses so that the rest of the class can see. After students list
areas where they made the most progress, the instructor asks them to think of strategies
that go with them. She asks “what did you have to personally do” to be able to evaluate
other people more critically (one of the goals students felt they made progress on)? The
instructor continues going through the list in this way, asking students for strategies that
helped them accomplish the course goals. The instructor states that during the next class
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session she will ask about areas where they made the least progress, why they think that
is, and what they can change.
In this brief in-class activity, Jane modeled a self-reflective process and then asked students to
participate in a reflection on their learning. By making this an in-class activity, she and the
teaching assistants were able to coach students through the process and provide feedback.
Creating Conditions that Support and Encourage SRL
Beyond directly targeting self-regulated learning through suggesting and teaching
specific strategies, several of the teaching practices, instructional decisions, and instructor
behaviors of the participants can be interpreted as creating conditions that support and encourage
SRL. These approaches include clear learning goals, grading policies, statements about interest
and value, a positive classroom environment, frequent practice and assessment, and peer
learning. This section provides examples of these approaches that were identified in the
interviews, observations, and course documents.
Learning goals and emphasis. All participants included course-level learning outcomes
in their syllabus as well as sections about expectations for performance and participation. I also
observed the instructors using lesson-level objectives or topics to frame the beginning of a new
lesson. Jane’s approach to this was particularly interesting. At the beginning of the lesson, she
presented students with learning outcomes organized by Bloom’s Taxonomy (Bloom, Engelhart,
Furst, Hill, & Krathwohl, 1956). When I asked her about this in the second interview, this is
what she had to say:
A lot of times, you know, I'm saying okay we're working on higher cognitives and… the
way I introduced it at the very beginning of class is…you've done very well…but think
back, you've probably done well because of some of these lower Bloom’s. And that's all
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right, because you need those lower Bloom’s. But, when do you have practice to do these
others? So, I said, well, you'll see how many times I'm thinking that these need to be
used. And so, I think that it's more of, maybe it's in the back of their mind.
As an essential component of self-regulated learning is goal setting, providing and explaining
learning outcomes may help support students in this process (Pintrich & Zusho, 2007).
Explaining lower order and higher order outcomes goes a step further in providing students with
suggestions about appropriate cognitive strategies.
In addition to learning outcomes, another way that participants appeared to be guiding
students’ focus and prompting goal setting was emphasizing concepts during class. For example,
while observing Alice, I noted that she used phrases such as “I want to impress upon you…” or
“You should be thinking: why is that?” Kate also highlighted important concepts with statements
like “Write that down in your notebooks” and “Make sure you’ve now written our second rule”
when discussing rules for resistors. These statements may give students cues about what is
important, potentially influencing their goal setting and leading them to direct more time and
effort in these areas.
Grading policies. In the theoretical models of SRL (Pintrich & Zusho, 2007; Zusho,
2017), the reward structures of a course have been identified as a potential factor in student
regulation. Several of the grading policies used by the participants seem to hold promise for
supporting SRL. Most of the participants, for example, used a straight scale and did not curve
grades, an approach that may reduce competition between students. Another approach used by
multiple participants was awarding grade points for participation. Kate, who used this approach
in her lower division social sciences course, described her grading scheme in the first interview:
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I have 5% of the grade in the class is called class participation points. It means they have
to open their mouth and ask a question or answer a question maybe that I gave in lecture
or in discussion section and they get a point. So, they have to open their mouth five times.
I tell them this is one of the most important things in the class….I want to teach them
how to ask a question about something they don't know, not to hide the fact that they're
confused about something, but to acknowledge that fact and ask the question that…gets
the right answer, gets them going on the right track.
Awarding points for participating in class may help support SRL by increasing the value of the
processes that are being rewarded, which in Kate’s case, requires students to formulate a
question about something they do not know or answer a question posed by another student
(Pintrich & Zusho, 2007; Zusho, 2017). Both of these require some degree of attention and
reflection on current understanding.
Another grading approach mentioned by Kate, as well as Parker, is allowing students
multiple attempts to get a correct answer on homework problems. A critical part of this, as
Parker mentioned, is that the online homework system he uses generates new values for
problems each time a question appears in an effort to reduce the likelihood of students gaming
the system. This is how he described his homework policy in the first interview:
What we ask is that they should score 75% or more for each unit. If they score 75% it
counts as 100%. So, I encourage them, like the first time they do a unit, they'll get 20%,
that's fine because it's mastery, you know. And I say the first time you do the homework
you guys can work as a group and do the homework. But remember, in the end, you're
accountable. So, you have to go back. The first time you can try it out, practice, you’re
going to get a totally different question and then, you know, in the end, that's what's
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important. They can also do the homework after the due date. So, if they miss a
homework, they get half the credit.
Providing students with multiple opportunities to practice, and incentivizing their doing so, may
support multiple aspects of SRL, including metacognition and increased effort (Pintrich &
Zusho, 2007; Zusho, 2017).
Interest and value. Beyond making certain activities require through grading policies, a
common approach to increasing motivation used by all participants was trying to generate
interest and demonstrate value. Alice for example, would try to make concepts personal for
students, as she described in her first interview:
So, I think some of it’s what I'm able to do. I can make the material interesting,
provocative. I can make them turn their head and…especially when I had the STEM
students, if I say now remember we're talking about a jail, not a prison, there is a
distinction, they don't care about that. But if I say imagine yourself in a 9 by 22 foot box,
not knowing when you get out, what do you think that would do to your thought
processes? Their heads will turn. So, some of it’s me, some of it’s them, and some of it is
kind of the synergy between us.
I observed this in her class as well. At one point she showed an image of a police uniform and
asked students to write down what they felt when they saw the image. Both of these examples
show that within the same subject-matter there may be specific techniques that increase interest.
Parker and Kate, who both taught lower division physical sciences courses, also
attempted to increase interest and value, focusing more specifically on the academic goals of
students. Parker, for example, noted in his first interview that he tries to “find connections to
what they're doing in class in other classes as well as kind of bring in sort of an interdisciplinary
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perspective.” I observed this during one of his classes in which he described how the current
topic related to other disciplines that his students were pursuing. Kate took the same approach, as
she described in the first interview:
We'll talk about fluid flow next class. And so, I talk about how the blood in your body
circulates and we say if we give someone an injection of dye for a CAT scan that actually
goes all the way through their body, fills every capillary in less than a minute. And
they're all impressed about that. So, you know, that must mean the flow rate is really
high. So, and then we derive the flow rate.
Related to academic goals, I observed both Reed and Jane provide examples to their students of
how their disciplines are still growing and changing. For example, during an activity on power
analysis, Jane demonstrated that it is still not widely used in the field, suggesting that now that
her students know about it, it may be one way they can help improve science. These statements
and those used by the other participants may not directly target self-regulation, but may influence
it indirectly through student motivation.
Positive environment. Another approach closely aligned with motivation is developing a
positive learning environment. Many of the participants used positive and encouraging
statements to help accomplish this. Alice, for instance, tried to reassure students before the
midterm that they would do well if they had been doing the readings and coming to class. Reed
made a similar comment during one of my observations. When starting a new lesson on the
nervous system, he stated that students often have challenges with that topic, but that his role was
to set them up for success. This was reflective of a statement he made during the first interview:
I just try to be as positive as possible, first of all. You know, just be the cheerleader for
them in a way… like, I know it's tough guys, I know you’re working hard, it's going to
APPROACHES TO SRL 70
pay off, just keep going, you know. I try to share my enthusiasm for anatomy, which can
be dry at times, but, you know, say it's really a lot of fun and logical if you think about it
and kind of go through it at least one time. And, I get that feedback from the students too.
These statements may help to create a more supportive environment where students feel that the
instructor is a partner or ally in their learning.
Another example of how participants might have accomplished this is by soliciting and
responding to student feedback. Alice mentioned doing so in her second interview:
So, it was helpful for them to say the slides are too much and it was helpful for me to say
don't treat them as a kind of thing you have to master. Think of them as kind of a prompt
to double-check your notes, to think what was the main topic?
Reed shared a similar process for gathering and addressing student feedback in his upper division
biological science course:
So, I do the midterm evaluation. Then we spend five minutes in the next class actually
going over that feedback. So, here's what you guys like, here’s what you didn't, here’s
what you want me to improve. Now, I don't get so much of…the kind of logistical things,
but I do get comments like, you know, we do too much talking…too much active
learning, but then I address that. Well, you're better off for it, you know. Or, we don't
cover everything because we did too much active learning and I say, well, we can't cover
everything and even if I did talk through 50 minutes straight, maybe we could, but you
wouldn't learn anything…So I have my rebuttals to those and those are kind of common,
but I don’t make them do the stuff.
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In both of these examples, the instructor did not make sweeping changes to their courses based
on the feedback, but it did give them an opportunity to address student areas of concern. Doing
so may encourage, to a limited degree, student attempts to regulate the context.
One particularly noteworthy example of allowing students to regulate their context came
up in the second interview with Jane. She described an activity in which students could pick their
learning environment for one class session:
What I did is instead of coming to class, you had to meet somewhere…outside of class,
anywhere outside of class, and you had to fill in this worksheet…And the first question
is, and they had to turn this in, and the first thing they had to do is take a picture of all
their feet and tell me where they were. And that, you know, I thought maybe it's
completely different and maybe by being in a group setting outside of the lecture hall,
they could actually focus and they weren't distracted by the learning environment of the
lecture hall, which is, in all honesty, not the best place.
In this example, students were given a structured task they had to complete, the worksheet, but
had to seek out an environment in which to do so.
Frequent practice and assessment. A fifth approach that may support and encourage
SRL that was common across all participants was frequent practice and assessment. Reed’s
response in his first interview stands out as a particularly representative description of this
approach:
I'm going to structure the class to kind of make them do it. I’m going to require three pre-
class assignments a week, one for each day of class, two online review assignments a
week. I'm going to have six total exams in anatomy to keep you working. I'm going to ask
a ton of questions during lecture. I'm going to provide all these extra opportunities for
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you to get extra help and extra question and answer opportunities. So, I’ll force you
through the grades to do…graded assignments…But, then again, it's just kind of creating
this atmosphere where you gotta do the work. I can't do it for you. I can’t lecture through
everything. Even if I could, you probably would not do well.
In addition to the interview, I observed this approach during one of his classes. He asked students
a question related to a common misconception. Students, submitting their answers with
classroom response devices, mostly got the question wrong. At this point, Reed revealed the
answer and asked students to work together to fix the false statements.
Kate and Jane also made regular use of in-class questions and student response devices.
In one class, I observed Kate asking students to make predictions about what would happen in a
demonstration she was about to conduct. Jane used in class questions to ask students about prior
knowledge. She also used the opportunity to ask students about approaches they use when
learning something new. This frequent practice and assessment, both in and out of class,
provides regular feedback to students about their current understanding of a concept. While self-
regulated learning is focused on how the student is directing their learning, this additional
structure may help support and encourage those efforts.
Peer interaction. The last approach found in the data that may support and encourage
SRL is activities that involve peer interaction. Some of these activities focused on making sense
of a particular issue or concept. Alice was one instructor to use peer interaction in this way,
which I described in my field notes during the observation of her course:
The instructor is starting a group discussion activity. She described the findings from a
study and then asked students how the findings could be explained. What factors are
involved? Why are there racial differences? She asked the groups to elect a scribe to take
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notes and discuss for 7-8 minutes. During this time, peer learning assistants were located
at the tables and helped facilitate the discussion as needed. After the discussion period,
the groups reported out to the entire class.
I observed a similar example of this approach in Jane’s course in which she asked students to
discuss the implications of researchers not using power analysis when analyzing their data.
Given the larger size of the class, she asked her teaching assistants to help monitor groups and
facilitate sharing out.
While some group activities required students to formulate a response to questions about
meaning, others focused on practice with a particular process. Jane used this approach to have
students work together to deconstruct and evaluate a figure legend. Parker, in his first interview,
talked about how he used them in discussion sections:
Where I get them more engaged is the discussions. The discussions are very structured.
So, I give them worksheets and every week, the material that we cover the preceding
week is structured so that they carry these out these group activities. And so, what I tell
the students is you don't want the discussion to be a second lecture. You've already had a
lecture. So, what we learn and practice in class now is…where they have to be
accountable in the discussion. And it's more cognitively demanding. Now I may do, you
know, bits and pieces and then they have to put the whole thing together in discussion
where…TAs walk around, they can work as groups….We encourage them to work as
groups. And so, it's very structured. So, they do have to carry out activities, they have to
give their answers at the end, and be accountable for it and stuff like that. So that's where
that sort of the active engagement part takes place. And so, attendance in discussion is
mandatory
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These activities encourage students to evaluate their understanding in relation to their peers. This
is aided to some extent by the requirement in many of these activities that students submit their
own work.
A final group of peer learning activities focused on sharing strategies, inside and outside
of the classroom. Kate, for example, created an online discussion forum after a midterm and
asked students who did well to “post what you think worked the best for you and so that
everybody can, you know, pull their ideas and see what might work best for them.” In another
example of this approach, Reed described an activity in which students from a previous class
shared strategies and advice:
So, I started doing this a couple years ago and, I don't know if it works or not, but, on the
last day of class…I pass around a note card and I'll say write advice to a future student in
the class… and then they would list whatever advice they want. Some are silly, like, you
know, it's okay to cry or run and hide, but some are really nice, you know, like…they
often talk a lot about time management…stay on track, don't procrastinate, don't fall
behind, ask questions, go to office hours, you know, typical stuff…On the second day of
[the new class], I bring the stack with me, as I just did this on Wednesday, and I read
some off and I'll read some of the silly ones, but I read the serious ones too.
This activity has the potential to impact both groups of students. It encourages the students
writing the cards to reflect on their learning and effective strategies, while students on the
receiving end of the cards get what will hopefully be interpreted as credible advice. These
approaches are summarized in Table 5, along with all of the others presented and discussed in
this section.

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Table 5
Summary of Instructor Approaches and Strategies
Category Approach Examples
Directly Suggesting
and Teaching SRL-
Related Strategies
Strategy hints and
suggestions
Recommendations about using quizzes for
reflection, how to read the textbook, and how
to take notes
Strategy instruction
and practice
Self-reflection worksheets, labeling a blank
diagram from memory, and in-class
discussion about time management
Creating Conditions
that Support and
Encourage SRL
Learning goals and
emphasis
Discussing lesson-level outcomes and
emphasizing important information
Grading policies Using a straight grading scale, awarding
participation points, providing multiple
attempts on homework
Interest and value Making personal connections and connecting
concepts to academic interests and goals
Positive
environment
Using encouraging statements in class,
responding to student feedback, and allowing
students some control over context
Frequent assessment
and practice
High-structure course designs, pre-class
assignments, questions and activities during
class
Peer learning Small group activities focused on making
sense of concepts, practicing with processes,
and sharing strategies

Faculty Perceptions of Effectiveness
The findings related to the first two research questions have established how faculty
experience variability in self-regulated learning among their students and the approaches they are
taking that may support and encourage SRL. The findings in this section address the third
research question: What are faculty perceptions of the effectiveness of these teaching practices?
The second interview guide and a few of the items from the first interview were designed to
answer this question. When responding to these questions, participants commented on several
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areas, including the balance of responsibility for learning, observing and measuring SRL,
differential impact of strategies, and promising practices.
Balance of Responsibility for Learning
Several participants expressed uncertainty about how much hand-holding to provide in
their courses. For example, how much should be required of students through the use of grade
points compared to how much students should be expected to do on their own initiative. Jane
summed this up best in her first interview when she said “the whole point is you know I'm not
here to have them fail, but I'm also not here to have them fail when they leave.” She also had this
to say about using extra credit to encourage more participation in her upper division biological
sciences course:
So, I'm going to try that. I’m mostly leery of extra credit, because to me, it's not time-on-
task and so it goes against my own principles of you should be really organizing yourself
and thinking what's the most appropriate and most important things you're doing. And
giving extra credit for low amounts of points is not a time-on-task scenario. It's actually
breaking my rules, but I'm going to try it.
Reed, who also taught an upper division biological science course, offered a different perspective
on using a high structure design with multiple required and optional activities:
I have never taught it low structure, traditional, didactic, but I can't imagine them doing
well. I mean, just because the quantity of stuff…if there’s no assignments, you’re
probably going to let things go. And if all you do is attend lecture and take notes, you're
not gonna, it's not gonna sink in. So, I can't imagine this class without the daily pre-class,
without the weekly reviews, because it's just too much stuff.
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These examples illustrate the tension between when to prompt or cue, when to tell explicitly, and
when to require specific activities. Effective self-regulators may not need these additional
supports, but given the variability in SRL, this is an understandable concern.
Observing and Measuring SRL
Another area where some participants expressed uncertainty was in being able to observe
and measure self-regulated learning. Alice noted in the first interview that it is difficult to know
what students are doing outside of the class and that although students might seem more engaged
in class, without doing a pre and post assessment, it is difficult to know if that is contributing to
higher cognitive outcomes. She followed up on this thought in the second interview, stating:
Where's the research? And how do we know? I think we know that students enjoy some
things more than others. I think we know some things make the time pass more or less
painful, but I don't know. I'm not convinced that we know what really is creating these
skills or this retention.
Reed and Jane expressed similar concerns about being able to assess the impact of their teaching
practices on SRL, noting that they were limited to mostly anecdotal evidence. One on one
interactions with students seemed to be one area where instructors could get feedback. Jane
commented on this in the second interview when I asked her about her experience with making
regular reference to Blooms Taxonomy (Bloom et al., 1956) in her classes:
I think it would be next impossible to actually study that, but I think it does sink into
them a little bit, because I've had students out in office hours come to me…and we'll talk
about some question and one students says well yeah, that we had to evaluate that…but
again, those are the ones coming office hours.
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Read also discussed the value and limitations of one on one interaction during his interview,
stating:
I'll recommend X, Y, or Z and then a few weeks where they'll say, Oh, I tried this and
now the second time I did much better. And, I’ll say great job, you know. So, so I get
anecdotes of that, but I have never measured it or actively sought to.
These examples suggest that although the participants are able to find some evidence that their
approaches are working for some students, they do not have sufficient data to feel comfortable
saying that they are effective overall. As they indicated in the interviews, this is because they
have not been able to carry out the rigorous experiments that would be required or they are
unsure of how to operationalize and measure SRL.
Differential Impact
When participants did comment on the effectiveness of a particular strategy, they
frequently mentioned that the impact seemed to vary across students and was particularly limited
by students’ incoming motivation. Parker, who was teaching a lower division sequence in
physical sciences, captured this sentiment well in his second interview:
If you look at the demographics of the students, you know there is a top quartile. These
[students], regardless of what you do, they will do well. You can have a lousy teacher,
you can have, you know, lousy instruction, you can have lousy…activities. These
[students], they are the ones who are highly motivated, will do whatever it takes. And so,
regardless these [students] do well. There is a bottom quartile. These are the students that
regardless of what you do, it may not be…having impact because they just, they're not
motivated and I can't figure out…then there's the middle group and that's where I see the
impact of, you know, all these guided activities….And so, and it's a delicate balance.
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Reed also commented on this idea of a group of students that are especially difficult to reach,
even at the upper division level:
We get that feeling for the motivation and the effort that they're putting in there, but then
there's a…subset that just, they don’t cut it for whatever reason. Sometimes it's a high
course load, you know, way too much going on, family stuff…So I think, as a group,
again, I would characterize their effort and motivation as very high, but again, not
everyone does that.
These examples illustrate the challenges that participants face in trying to support and encourage
SRL in all of their students.
Jane and Alice commented on this differential impact as well. In the second interview, for
example, Jane discussed the challenge of knowing ahead of time how well something will work:
I, you know, sometimes I feel like I'm just like throwing things up in the air…and maybe
something will hit somebody…Sometimes I feel like it's random…and that's diversity of
learning
Similarly, when asked about the factors that might contribute to students being successful, Alice
suggested that it can vary for a number of reasons:
They have different levels of preparedness. It's a different priority for some versus others.
They’ll do more work. There's too many moving parts for them to sit themselves out. So,
I don't know, that's a good question. Why are some successful and why some aren't? I'm
sure it’s them, me, and us.
In these examples, the participants appear to distinguish between students who may be motivated
and need help with skills and strategies, and other students who are not well motivated or have
significant external responsibilities. They also expressed variability in effectiveness across
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different instructional strategies. This is highly reflective of the dynamic and multidirectional
nature of SRL (Pintrich & Zusho, 2007; Zusho, 2017).
Promising Practices
With the caveats that the impact was likely not uniform across all students and that SRL
had not been precisely measured, participants did identify a few promising practices. These
include some of the motivation supports discussed in earlier in this chapter, as well as exposure
to and practice with specific strategies.
Motivation supports. Participants attempted to increase student motivation in several
ways. The approaches that they indicate were successful include making personal connections,
giving students control, providing multiple opportunities to attempt homework problems, and
awarding grade points for participation. A representative example of each of these is provided
below.
Regarding the first approach, making personal connections, Alice had the following to
say during her second interview:
So, sometimes, for some of the students, the more provoked they get, I can see their
motivation shifting a little, you know. Like maybe they're outraged over justice. Maybe
they disagree with my interpretation and they want to make sure I understand it in
alternative ways. There's lots they do that tell me their motivation is shifting. One student
told me…about halfway through the quarter: this is great. She said: I just read the
newspaper differently now. I said, well, thank you for reading a newspaper. So yeah, the
motivations, my hope is that they shift and that it's away from what I call grades, grade-
grubbing, instrumentality and more towards kind of the more higher-end goals for
learning.
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Regarding student choice, the example of Jane allowing her students to change their learning
environment for one class session seemed to have an impact on cognitive outcomes, as she noted
in the second interview:
After that, I had the highest scores for negative and positive controls that I've ever had.
And the TAs are going through right now in their assignment…and they said…they're
seeing really high scores on this. So that's going into the curriculum, because that
worked. And so, again, you know, I try different things. They don't work, I throw them
out. I try something else, I put it back in.
Parker compared his approach of allowing students to attempt homework problems multiple
times with colleagues who do not, noting that it seemed to encourage a mastery approach:
So, what we find is on the average, each homework unit that I assign, my students do it at
least four to five times…Other faculty in our department don't like that mastery part of it.
They just like to assign one homework. And so, the other side of it is you can assign
homework and usually the whole class gets the same homework and and it's a one shot
deal. But, the way that the [online homework system] is constructed is it's mastery
learning. So, they can do it multiple times.
Several instructors included some form of student participation, including Kate. She indicated in
her second interview that these seemed to be worthwhile, noting that “before we did this, we got
no questions...nobody coming to the tutoring center.”
In these examples, participants note specific outcomes, such as greater engagement and
increased exam scores. However, the underlying relationships with self-regulated learning are
still unclear. This challenge will be further discussed in the next chapter.
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Exposure to and practice with strategies. The other category of promising approaches
to supporting and encouraging self-regulated learning involves exposure to and practice with
specific strategies. Reed noted this in his second interview:
We also provide ample practice opportunities, whether they're assigned like [the online
homework system], before class assignments, weekly review quizzes, etc., or unassigned.
So, I promote…flashcards, I promote practice quizzing yourself and doing practice
exams, things like that. And I see students doing those things in office hours. They’re
showing me their reading guides and things. So, I know they're doing them to some
extent.
He also commented on this in the first interview, noting that he has heard of at least some
students asking for this structure in other courses:
It’s anecdotal, yeah, that, at least in this class, that I've seen students say, you know, I
thought it was like this, but then I learned it didn't work, so I've adapted my study
strategies to help me with that. I have seen…students go on to other classes and heard
back that they've asked those instructors for reading guides and things, like they want this
more structured framework to help them read the book...So, in that case, I've seen them
carry, or at least ask, for certain instructional strategies in the next class, which has been
kind of fun to hear back on. And then I hope that the strategies they develop here, they
carry forward in other courses…with regard the time management and study skills, but I
don't have any evidence for that.
Jane also noted some positive impacts related to recommending strategies and having student
practice them, but still felt there were limitations:
APPROACHES TO SRL 83
My instructional approach and the activities…what I'm trying to do is teach them a little
spacing. For some students, they embrace that. But I really don't feel that the majority of
students are embracing it…Time-on-task is the other…I would say spacing and then this
concept of time-on-task, you know, choose a hierarchy of what's important to you and
make sure that it's going…For some students it’s a wake up call and they'll do time-on-
task or you could see that some of them thought that was an important aspect and they
hadn't thought about that prior.
While the participants indicate that these practices do show promise in some areas and for some
students, these examples highlight the self-regulated learning involves more than just knowledge
of effective strategies.
One other important consideration in this category is the role peer interaction can play.
Several participants noted this, with Jane’s comments in the second interview offering several
insights:
I feel that group can make huge differences in their motivation and their effort. And if
they get in a good group, and I have a couple of students that were dissatisfied with the
group they were in and were having problems and came and talked to me individually.
And I said, well, why don't you move over into this group or do that and it changed a lot
of what they do. But, how do I shift them into another group? How do I move students
into the groups, because they have, you know, how do they connect with each other? ….
But now if they're in a…group that gives them problems, it just continues to give them
problems.
Jane’s comments here and those of the other participants indicate that while peer interaction and
collaborative learning may be beneficial, some of those benefits are dependent on the overall
APPROACHES TO SRL 84
quality of a group. Individual students might learn more or less and behave differently depending
on who they are grouped with. This potential interaction between self-regulated learning and
socially regulated learning echoes the findings of Järvelä et al. (2013).
Summary
This chapter presented the results of the data collection and analysis, grouped
thematically with respect to the research questions. For the first research question, which asked
about faculty experiences with SRL, the data reveals that participants encounter differences in
performance orientation, effort and time use, and metacognition and metacognitive knowledge.
The second research question asked about approaches participants took that could be interpreted
as supporting and encouraging self-regulated learning. Here the results were grouped into two
broad categories that distinguished between approaches that directly relate to SRL and those that
might create conditions that are supportive of SRL. For the last research question, which asked
about faculty perceptions of the effectiveness of these approaches, four themes emerged from the
data, including: personal responsibility for learning, measure SRL, differential impact, and a
collection of promising practices. The next chapter provides further discussion of the meaning,
significance, and implications of these findings.

APPROACHES TO SRL 85
CHAPTER FIVE: DISCUSSION
This study explored the approaches that a group of faculty at Riverview University use to
encourage and support self-regulated learning (SRL) in their undergraduate courses. The
following research questions guided the study:
1. How are a group of RVU faculty experiencing variability in self-regulated learning
among the undergraduate students that they teach?
2. What teaching practices are these faculty using that may encourage and support self-
regulated learning?
3. What are faculty perceptions of the effectiveness of these teaching practices?
Five faculty participated in the study, which consisted of two interviews, class observations, and
analysis of course documents. The previous chapter detailed the findings that emerged from this
data collection and subsequent analysis. This chapter provides a discussion of the meaning,
significance, and implications of these findings.
Discussion of Findings
Faculty Perceptions of Self-Regulated Learning in Their Courses
The first research question asked: How are a group of RVU faculty experiencing
variability in self-regulated learning among the undergraduate students that they teach? Broadly
speaking, participants expressed encountering significant variability in self-regulated learning
among their students. This is in alignment with what has been suggested by the theoretical
models of SRL (Pintrich & Zusho, 2007; Zusho, 2017) and what has been found in recent
empirical research on SRL in college students (Dye & Stanton, 2017; Park et al., 2012; Sebesta
& Bray Speth, 2017; Verrell & McCabe, 2015). What this study adds is a more nuanced
depiction of SRL from the perspective of the course instructors. In particular, the study found
APPROACHES TO SRL 86
three areas where variability in SRL was most significant for the instructors: performance
orientation, effort and time use, and metacognitive knowledge.
Participants expressed concern about their students’ preoccupation with grades, with
some noting that it seemed to be an increasing trend. Also encompassed within this issue were
experiences some instructors had with students expecting that their grade should reflect the time
and effort they put into an assignment rather than reflect their understanding and mastery of the
subject-matter. In the theoretical models of SRL (Pintrich & Zusho, 2007; Zusho, 2017),
motivation is conceptualized in two ways: general motivation and regulation of motivation.
These findings suggest challenges with both. Students are beginning the course with a
performance orientation and in many cases do not appear to be regulating their motivation
toward a mastery approach. As discussed in the next section, this appears to be one reason the
participants specifically targeted motivation in their instructional approaches.
Closely related to motivation, the instructors also expressed encountering significant
variability in student effort and use of time. More than just overall effort and time, they
specifically noted differences in strategic use of time. This reflects the behavioral domain of SRL
(Pintrich & Zusho, 2007; Zusho, 2017), which describes the processes students may use to plan,
monitor, control, and reflect on their effort and use of time. As revealed by the instructors’
experiences, some students are able to manage their time well and direct it toward productive
activities, while others may invest the same amount of time, but direct it toward less productive
activities.
The third area where the study participants indicated significant differences in students
was in their metacognition and metacognitive knowledge. Although the instructors did not
always use the same terminology, their responses during interviews differentiated between
APPROACHES TO SRL 87
different processes in the theoretical model of SRL (Pintrich & Zusho, 2007; Zusho, 2017),
specifically: knowing general cognitive strategies, knowing metacognitive strategies, and
effectively applying both. Students, for example, might not be aware of certain strategies that
could help them learn more deeply on their own, as Verrell and McCabe (2015) found in their
study. Or, as Dye and Stanton (2017) discovered, even students who recognize a need to try a
different strategy may not do so. The instructors in this study encountered both of these
scenarios, as well as students’ lack of awareness about what strategies are best suited to
particular tasks.
These findings demonstrate that the participants encountered variability in multiple
domains of self-regulated learning. The variability that they noted aligns well with existing
research while providing a detailed account of how faculty are experiencing this variability in
their courses. In addition to answering this specific research question, these findings help provide
context for the other two research questions.
Faculty Approaches to Encouraging and Supporting SRL
The second research question asked: What teaching practices are these faculty using that
may encourage and support self-regulated learning? In general, the participants made significant
use of what would be considered active learning or student-centered teaching practices. Rather
than report on all of these practices, my findings focus on those that appeared to be most directed
toward self-regulated learning. To make this distinction, I considered four sources of
information: practices in which participants explicitly stated they were targeting some aspect of
SRL, my conceptual framework, the theoretical models of SRL (Pintrich & Zusho, 2007; Zusho,
2017), and the recent literature on instructional practices associated with SRL that was discussed
in Chapter 2 and summarized in Appendix A. I then further divided the instructional approaches
APPROACHES TO SRL 88
into two broad categories, approaches that involved recommending and teaching SRL-related
strategies, and approaches that might create conditions supportive of SRL.
Within that first category, some of the approaches the study participants took involved
suggesting specific strategies to students, such as using quizzes to assess their knowledge and
adapt their study strategies. Some of these suggestions were made in a brief, casual manner,
while at other times the instructors were more direct. Going a step further, many of the
participants explicitly taught specific strategies and required students to practice with them, such
as labeling a diagram from memory. While both approaches provide exposure to strategies, the
results of Connell and colleagues' study (2016) of student strategy use suggest that the latter
approach, requiring students to practice, may be more effective. Even with encouragement from
an instructor, it is likely that a portion of the students will not try a new strategy on their own.
It is also important to note that the majority of the strategies the study participants
focused on could be considered cognitive and in some cases behavioral, such as time
management tips. Out of all the strategies the participants discussed in the interviews and those
that I observed directly in the classroom, very few focused on regulation of motivation. For
example, instructors did not appear to provide suggestions or practice with positive self-talk or
interest enhancement, processes recognized by Pintrich and Zusho (2007) as helpful in regulating
motivation. Interestingly, Hoops and her colleagues (2016) also found regulation of motivation
to be underrepresented in their study of SRL supporting teaching practices. That is not to say that
instructors ignored motivation. Instead, among the participants in my study, most of their
approaches that involved motivation were focused directly on general motivation factors rather
than regulation of motivation. These approaches, and several others related to the cognitive and
behavioral domains, were grouped into the second category.
APPROACHES TO SRL 89
The second category of instructional approaches consisted of teaching practices that did
not appear to target a self-regulatory process directly, but that might support student attempts to
self-regulate. As detailed in the previous chapter, these approaches were grouped into six sub-
categories: learning goals and emphasis, grading policies, interest and value, positive
environment, frequent practice and assessment, and peer learning. In implementing these
practices, the participants appeared to have similar goals in mind: increasing student effort and
time on task, guiding their attention and cognition, and encouraging students to reflect on their
learning. Within these approaches, the underlying factors that might influence SRL seem to vary.
For example, instructors using statements in the class intended to increase interest and value
might support SRL by influencing motivation. Frequent practice and assessment, on the other
hand, require students to take an action.
In their models of SRL, Zusho (2017) and Pintrich and Zusho (2017) made the distinction
between academic tasks, reward structures, instructional methods, and instructional behaviors.
Those distinctions are present in the two categories of instructional approaches discussed here.
However, what emerged from the data were also distinct differences in the degree to which a
particular approach specifically targeted self-regulation.
Faculty Perceptions of Effectiveness
The third research question asked: What are faculty perceptions of the effectiveness of
these teaching practices? When participants were asked questions that related to effectiveness,
they commented on a number of different areas beyond just outcomes, including challenges and
uncertainty around implementation. The most significant of these generally fell into one of four
themes: balance of responsibility for learning, observing and measuring SRL, differential impact,
and promising practices.
APPROACHES TO SRL 90
Several of the instructors noted the need for providing students with multiple supports for
their learning. This emerged in the interviews as expressions of uncertainty and sometimes
frustration at what they considered to be an increasing amount of handholding. The question
these instructors seem to be grappling with is: what is an appropriate balance of responsibility for
learning? Providing high levels of support during one class might improve outcomes, but if
students do not also develop as self-regulating learners during that process, they may struggle in
less supportive and structured environments. Some instructors felt they had reached a good
balance, while others seemed less certain.
Another area multiple instructors commented on when asked about effectiveness was
their ability to truly know if a particular practice was effective in improving self-regulated
learning. This seemed to involve both a question of measurement of SRL and the feasibility of
associating SRL with specific instructional practices. While some instructors did note using
surveys, assessment data, in-class questions, and anecdotes from one on one interactions with
students as a loose benchmark, none had rigorously assessed self-regulated learning. Some
instructors also noted that the type of controlled experiments that would be needed to isolate the
specific effects of an instructional strategy would be challenging to implement. As reflected in
the broader literature, this is a challenge shared by many researchers and practitioners, even
among those that specifically examined course factors related to SRL (Bol et al., 2016; Connell
et al., 2016; Corkin et al., 2017; Sletten, 2017; Steiner, 2016).
In cases where the instructors were willing to offer a cautious judgment about
effectiveness, most were in agreement that any impacts varied across students. In particular,
instructors seemed to feel that they could make a positive impact on students who were already
somewhat motivated, even if only by grades, but who lacked knowledge of effective strategies.
APPROACHES TO SRL 91
However, they seemed challenged by certain groups of students who were not motivated to
engage in the course. Conversely, they recognized that there was also a group of students who
would likely do well and learn no matter what instructional strategies they used.
Although instructors indicated that there did not appear to be one particular strategy that
worked across the board, they did identify a few practices that they considered promising for a
majority of students. Some of these practices focused on providing motivational supports, such
as attempts to make course topics more personal or to allow students multiple opportunities to
get credit for homework problems. Other approaches that instructors considered promising
involved exposure to and practice with an SRL-related strategy, such as a guided reflection
activity.
Limitations
There are a few important limitations to acknowledge with respect to these findings.
First, I did not attend every class session taught by the instructors, nor did I attend associated
discussion sections and labs. It is possible that there were other instructional approaches that I
missed as a result, although some of these were covered during the interviews and document
analysis.
Another important limitation is that I did not directly measure self-regulated learning or
attempt to access the student perspective. As the purpose of the study and the focus of the
research questions was faculty practices and perceptions, this is an appropriate limitation.
However, it does mean that I am unable to independently assess the few claims that participants
made about effectiveness. Similarly, as a qualitative case study, the findings reported here should
not be generalized to other contexts or to other faculty at RVU. However, as discussed in the
APPROACHES TO SRL 92
next section, readers may be able to transfer many of these findings to their site for further
development and evaluation.
Implications for Practice
This study provides valuable insight into a problem of practice shared by many
postsecondary institutions: how to help students develop the knowledge and skills they need to
effectively regulate their learning, and how to create conditions across the institution that support
and encourage that self-regulation. The findings describe in detail the experiences, perceptions,
and practices of a group of faculty who are already implementing research-based instructional
strategies, many of which related directly to self-regulated learning. While the local context of
the study stands to gain the most from these findings, there are important implications for the
broader field of higher education as well.
One of the immediate implications of this study is the need to further develop and
evaluate the practices and strategies that show promise for encouraging and supporting SRL. The
participants highlighted a few of these practices directly and I identified others through my
analysis. Although the theoretical models of SRL imply that they should be effective, the
opinions expressed by the participants, as well as the mixed results of recent empirical research
in this area (Corkin et al., 2017; Sletten, 2017), suggest more rigorous examination is necessary.
There is significant opportunity here for higher education practitioners, including the participants
of the study, to pursue this research and advance the development of these practices.
The findings of this study reveal one area in particular that is in need of further
development: instructional strategies that directly support regulation of motivation. The
participants used several strategies to attempt to increase or shift general motivation, but much of
this focused on actions taken by the instructor, such as awarding participation points and making
APPROACHES TO SRL 93
statements related to value and interest. Students may also benefit from coaching and support in
how to regulate their own motivation, such as using positive self-talk and interest enhancement
(Pintrich & Zusho, 2007). This may be one way to help address the tensions between
handholding students and equipping them with skills needed to regulate their own learning.
Further, those institutions and individuals who may have found effective ways to support
regulation could benefit the broader community by sharing their approach and the evidence.
Another important implication of this study is the need to consider how the broader
context of students’ lives relate to self-regulated learning at the course-level, a concept Zusho
(2017) brought into her revised model of SRL as “lifeload” based on work by Kahu (2013). As
many participants noted, faculty do not often have visibility into what students are doing outside
of class, particularly family and employment obligations they might have. As a result, it may
appear at the course-level that students are not regulating their time and effort appropriately,
when, in the broader scope of their lives, students may actually be very strategic in prioritizing
and allocating their time based on competing demands. As some of the study participants noted,
this concept of lifeload may be particularly relevant for low-income students.
Self-regulated learning also needs to be considered from the broader context of the
institution. Although the participants in this study were found to be implementing several
strategies with the potential to support and encourage SRL, they were purposively sampled to
help ensure that was the case. If institutions intend to make this a more widespread practice, it
will require leaders of those institutions to make it a priority, provide appropriate resources, and
encourage a culture that recognizes and values these practices. Part of this will involve
addressing the uncertainty and tensions brought up by the participants. However, there is also an
opportunity to look beyond course-level interventions to program-wide and even institution-wide
APPROACHES TO SRL 94
strategies that take a more developmental approach to cultivating self-regulated learners
throughout their time at the institution.
Another important consideration at the institutional level, and within the broader context
of higher education, is how student success is defined. Although overall academic achievement
is one of the stated outcomes of the model of self-regulated learning, three others are just as
critical to consider: engagement, risk-taking, and understanding. Typical institutional metrics,
such as graduation rates and GPA, may not adequately reflect these outcomes and to the extent
that these incongruities exist, institutions and their faculty may continue to experience challenges
with self-regulated learning. While completing a program with a good GPA is important, this
study suggests that student perceptions and expectations around grades were inconsistent with
those held by the instructors. Some students seemed to value grades above learning for mastery
and expected grades to correlate with effort and time spent rather than understanding. This
preoccupation with grades is partly the responsibility of students, but institutions also need to
examine how grades are being communicated and awarded if they want students to regulate their
learning toward more meaningful outcomes.
Recommendations for Research
Both the findings and limitations of this study point to several important areas for future
research. The findings shed light on the instructional approaches that faculty are using that may
support self-regulated learning. However, as a qualitative case study, the intent was only to
ascertain faculty perceptions of effectiveness, not to assess it directly. Future studies should
further explore the promising practices found here to more fully assess their effectiveness.
Randomized controlled trials would be helpful in reducing the influence of other variables, but
APPROACHES TO SRL 95
quasi-experimental studies with appropriate statistical analyses could also produce valuable
insights.
It would also be important for some of these studies to take a longitudinal approach. One
of the important questions raised in this study, as noted by the participants, is how some of these
instructional approaches might improve SRL in subsequent courses. This developmental
perspective might be missed if only cross-sectional designs are used. Of particular interest might
be to explore a scaffolding approach in which practice with specific cognitive and behavioral
strategies are initially encouraged with grade points and other motivational supports, which are
slowly replaced with strategies that support self-regulation of motivation.
Additional qualitative studies are also recommended. This study reveals several tensions
around self-regulated learning, such as responsibility for learning and distinction between effort
and mastery. These topics would benefit from an in-depth follow up to gain the student
perspective and those of other faculty, particularly those who may be using more traditional
teaching practices that were not explored in this study.
Conclusions
Findings across the three research questions paint a detailed picture of how a group of
faculty experience variability in self-regulated learning in their undergraduate courses, how they
approach this challenge through their teaching practices, and their perceptions of the
effectiveness of these practices. Having been carried out in a naturalistic setting, these findings
reflect current, real-world conditions in the area of postsecondary teaching. Of particular note,
the instructors who participated in the study are regularly implementing research-based
instructional strategies, many of which are often bundled under the broad categories of active
and collaborative learning. Given growing enthusiasm around these practices, it is important to
APPROACHES TO SRL 96
examine them more closely within the context of self-regulated learning. This study reveals
important questions and challenges that even experienced faculty and administrators may be
facing, such as what is an appropriate amount of support to provide and how can we prepare
students to be more effective regulators of their own learning beyond their current courses and
programs of study? This study offers some suggestions, but there is much more work to be done.
APPROACHES TO SRL 97
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APPROACHES TO SRL 104
Appendix A
Summary of SRL-Supporting Practices from Recent Empirical Research

Academic Tasks and Course Structure Reference
Tasks that directly target SRL phases and domains, such as
requiring students to: set goals and create plans; activate prior
knowledge; monitor understanding, effort, and time use;
modify strategies and approaches when ineffective; seek help;
and/or evaluate effectiveness of strategies and approaches in
achieving goals, understanding, and performance.
Bol et al., 2016; Connell et
al., 2016; Corkin et al., 2017;
Sebesta & Bray Speth, 2017;
Steiner, 2016
Scaffolding course assignments and providing explicit
guidance
Hoops et al., 2016; Khaled et
al., 2016
Including open-ended tasks that provide opportunity for
student choice and autonomy
Hoops et al., 2016; Khaled et
al., 2016
Using reward structures that promote cooperation, individual
responsibility, and mastery
Hoops et al., 2016
Tasks that require students to practice with and develop
specific strategies, such as: active reading, active note-taking,
problem-solving, concept-mapping, self-quizzing
Bol et al., 2016; Corkin et
al., 2017; Steiner, 2016
Instructional Methods and Instructor Behavior Reference
Modeling SRL strategies Hoops et al., 2016; Khaled et
al., 2016
Providing guidance and cues during instruction by making
specific reference to: metacognition; test-taking strategies,
information processing, help-seeking, and time-management
Hoops et al., 2016; Khaled et
al., 2016
Attempting to trigger interest and demonstrate value Hoops et al., 2016
Providing attributional feedback Khaled et al., 2016
Encourage students to try new strategies Dye & Stanton, 2017
Using small groups and peer interactions that require students
to monitor their understanding, discuss learning strategies,
adjust their personal strategies, and evaluate effectiveness
Connell et al., 2016; Corkin
et al., 2017; Sebesta & Bray
Speth, 2017

APPROACHES TO SRL 105
Appendix B
Research Alignment Matrix

Research Question Conceptual Framework Data Instruments
How are a group of RVU
faculty experiencing
variability in self-
regulated learning among
the undergraduate
students that they teach?
Self-Regulated Learning
(Pintrich & Zusho, 2007;
Zusho, 2017)
First Interview, Questions: 4-15
Artifact Analysis

What teaching practices
are these faculty using
that may encourage and
support self-regulated
learning?
Self-Regulated Learning
(Pintrich & Zusho, 2007;
Zusho, 2017)
First Interview, Questions: 9-12
Observations
Artifact Analysis
What are faculty
perceptions of the
effectiveness of these
teaching practices?
Self-Regulated Learning
(Pintrich & Zusho, 2007;
Zusho, 2017)
First Interviews, Questions: 4-15
Second Interview, All Questions
Basic/Demographic First Interview, Questions: 1-3

APPROACHES TO SRL 106
Appendix C
Guide for First Interview

Basic/Demographic Questions

1. How long have you been teaching at RVU?
a. Have you taught anywhere else?
b. If so, where?

2. What courses do you typically teach?

3. How long have you been teaching [course identified for study]?

Course Design

Great, thank you. For the next set of questions, it would be helpful to focus specifically on that
course, although you’re welcome to bring in other examples if you think they’re important.

4. Tell me about your approach to designing this course.
a. How did you start?
b. What did you find challenging?
c. What did you most enjoy?

Experiences with Students

5. What are your expectations of students who take this course?

6. Thinking about the previous times you’ve taught this course, how would you say students
met or did not meet these expectations?

7. For those students who did well, what factors do you think most contributed to their
success?

8. For those students who didn’t do so well, what factors do you think most contributed to
the poor outcome?

Instructional Strategies to Support/Promote SRL Use/Development

9. Have you found that particular strategies are helpful in getting and keeping students on
the right track?
a. Are there specific things you do while teaching to help guide students’ focus or
thought process?
b. How often do you prompt them to reflect on their thinking and understanding of a
given topic?
c. Are there particular activities or strategies you use to guide this refection?
d. Do you find that they’re able to adjust their approach to learning based on this?
APPROACHES TO SRL 107

10. What strategies have you tried to help increase student motivation?
a. Do you find that students are receptive to this?
b. In what ways have you observed them try to motivate themselves or each other?

11. How would you characterize the amount of time and effort students put into the course?
a. Have you found that there are things you can do to help students put in the
required time and effort?

12. How often do you encounter students trying to change the parameters for a particular
activity or negotiate changes to the course?
a. Are there areas of the course where you’re more flexible or let students define
certain aspects of an assignment? (e.g., writing their own rubric)

13. Thinking about students at the end of your course compared to the beginning, how would
you characterize their growth as self-sufficient learners?
a. If they improved, what do you think contributes to this?
b. If not, what do you think could help?

14. If a student came to your office who was struggling in your course, what advice would
you give that student?

15. If you were handing this course off to a colleague who was teaching it for the first time,
what advice would you give that person?

APPROACHES TO SRL 108
Appendix D
Observation Protocol

Participant:
Observation Number:
Additional Instructional Staff:
Date:
Location:

Classroom Layout

Field Notes

Time Notes Observer Comments

APPROACHES TO SRL 109
Focus of Observations

Category Definition Examples
SRL-
Supporting
Practices
Practices that provide an
opportunity for students to
engage in SRL, but do not
directly encourage it
- Pausing briefly during lectures
- Providing opportunities for student choice
- Providing time for planning and reflection
SRL-
Promoting
Practices
Practices that appear to
encourage student use of
SRL strategies

- Activating interest
- Activating prior knowledge
- Modeling SRL processes
- Using cues and questioning to guide
students through SRL processes
- Providing explicit instruction in SRL
strategies
- Using student activities that require students
to engage in SRL processes
- Structuring group work to include
opportunities for peer modeling
Developmental
Supports for
SRL

Practices that appear to
accommodate different SRL
abilities and develop student
SRL skills over time
- Assessing student SRL ability at different
points in the term
- Providing regular feedback on SRL skills
and strategies
- Requiring students to try new strategies they
may be hesitant to try on their own
- Requiring students to reflect the
effectiveness of strategy use
- Progressively removing scaffolds
Non-
Supportive
Practices

Practices that may not
support SRL or appear to
actively discourage SRL
- Fosters an overly competitive environment
- Emphasizes grades/performance
- Significant use of highly scripted or close-
ended activities
Student
Response

How students respond to
SRL supporting and
promoting practices
- Student interaction with instructor and peers
- Degree of engagement in activity/lecture
- Resistance to activities

APPROACHES TO SRL 110
Appendix E
Guide for Second Interview

1. How would you characterize the approaches students used to learn the concepts in this
course?
a. How do you feel your instructional approach and activities influenced their
approach to learning?
b. What other factors might played a role?

2. How would you characterize student effort and motivation in this course?
a. How do you feel your instructional approach and activities influenced their
motivation?
b. What other factors might have played a role?

3. What changes, if any, did you make during the course in response to student feedback?
a. What about changes you made in response to your own observations of student
behavior and understanding?

4. What shifts, if any, did you notices in students motivation and approaches to learning at
this point in the course compared to the beginning?
a. What variations did you notice between students?
b. How do you feel your instructional approach and activities influenced these
shifts?
c. What other factors might have played a role?

5. What changes, if any, are you considering for the next time you teach this course?

APPROACHES TO SRL 111
Appendix F
Initial Codebook for Interviews, Observations, and Artifact Analysis

SRLDomain: Cognition
SRLDomain: Motivation/Affect
SRLDomain: Behavior
SRLDomain: Context
SRLPhase: Planning
SRLPhase: Monitoring
SRLPhase: Controling
SRLPhase: Evaluation
Context: InstructionalMethod
Context: ActivityDesign
Context: RewardStructure
Context: InstructorBehavior
SpecificPractices: Modeling
SpecificPractices: Scaffolding
SpecificPractices: Cues/Guidance
SpecificPractices: AttributionalFeedback
SpecificPractices: TeachingAssistant
SpecificPractices: PeerModeling
OvertnessOfInstructorStrategy: ExplicitSRL
OvertnessOfInstructorStrategy: ImplicitSRL
NatureOfTask: HighStructure
NatureOfTask : LowStructure
NatureOfTask : Open-ended
NatureOfTask : Close-ended
GradeConditions: IndividualGrades
GradeConditions: CompetetiveGrades
GradeConditions: CooperativeGrades
Outcome: Understanding
Outcome: Engagement
Outcome: Achievement
Outcome: Risk-taking
TargetOfInstructorSRLStrategy: CurrentContext
TargetOfInstructorSRLStrategy: Developmental
TargetOfInstructorSRLStrategy: ViaMotivation
TargetOfInstructorSRLStrategy: ViaOutcomes
TargetOfInstructorSRLStrategy: ViaKnowledge/Skills

APPROACHES TO SRL 112
Appendix G
Final Codebook for Interviews, Observations, and Artifact Analysis

InstructorPerceptionsOfSRL

PerceptionOfLearning PerceptionOfSelf-Regulation
PerceptionOfMotivation

InstructorPerceptionOfImplementation

Classroom InstitutionalPriorities
ContactOutsideOfClass InstructionalResources
ContentCoverage LargeClassSizes
DepartmentalConstraints MultipleMovingParts
DifficultToAssess PreventOwnBias
GradeWeighting ReducingAcademicDishonesty
HandHolding TimePressures
HardToEnforce UseOwnTimeProductively
HowToGroupStudents

InstructorPerceptionOfOutcomes

AbilityToWorkInGroups GrowthInCompetencies
AdaptStrategies HelpSeeking
BetterStudentExperience ImpactOnSubsequentCourses
BuyIn MixedOutcomes
ConceptualChallenges Motivation
DefiningSuccess NewPerspectives
DifferentialImpact PeerRelationships
EngagementInClass PredictorsOfSuccess
EngagementOutOfClass RelianceOnExternalHelp
ExamScores StudentPushback
GradeFocus StudentsDoingTheWork
GroupLottery

InstructorPerceptionOfStudents

StudentsAbilityCapacity StudentsKnowledgeOfStrategiesSkills
StudentsAcademicHonesty StudentsLanguage
StudentsCharacteristicsDemographicsChanging StudentsMixedSpectrum
StudentsEffort StudentsMotivatedByGrade
StudentsEngagementInClass StudentsMotivatedToLearn
StudentsExpectGradeForEffort StudentsMotivationAffect
StudentsExperiencesInHighSchool StudentsPreparedness
StudentsExternalResponsibilities StudentsResponsibility
StudentsHigherOrderThinking StudentsStrategicTimeUse
APPROACHES TO SRL 113
InstructorStrategies

AdaptInstructionToStudentCharacteristics OneOnOne
AddressMisconceptions OpportunitiesToReflect
AskDifferentStudents OutOfClassCommunication
AskFeedback ReadingGuide
AskOpinion ReduceCompetition
AskPriorKnowledge RequireGroupsToReportOut
AskRecallQuestions StatementAcademicHonesty
AskStrategyUse StatementGettingHelp
CaseStudy StatementImportance
ChallengingAssumptions StatementInstructorExpectations
ChangeBasedOnFeedback StatementLearningObjectives
ChangeEnvironment StatementMotivation
ClickerQuestion StatementPersonalExperience
CompellingFactsData StatementPositiveSupport
ConnectionsToDisciplinesClasses StatementRealWorldConnections
Controversies StatementsAboutNatureOfLearning
Demonstration StatementsRecommendedStrategies
DesignGrades SupplementalInstruction
DesignHighStructure SyllabusHelpResources
DesignIndividualAccountability SyllabusParticipationGuidelinesRecommendations
DesignMultipleOpportunities SyllabusTechnologyUse
DesignOpenEnded TaskPracticeSRL
DesignPeerLearning TaskPreLectureAssignment
DesignScaffolding TaskReflectOnLearning
Game TaskSelfAssessment
InClassAssessmentActivity Teaching Assistant
IndividualPractice TeachStrategy
LearningAssistant ThoughtExperiments
MakePrediction TryNewThings
ModelProcess WitholdAnswers
ModelSRL

APPROACHES TO SRL 114
Appendix H
IRB Study Information Sheet

University of Southern California
Rossier School of Education
3470 Trousdale Parkway
Los Angeles, CA 90089

INFORMATION/FACTS SHEET FOR EXEMPT NON-MEDICAL RESEARCH

APPROACHES TO ENCOURAGING AND SUPPORTING SELF-REGULATED
LEARNING IN THE COLLEGE CLASSROOM

You are invited to participate in a research study. Research studies include only people who
voluntarily choose to take part. This document explains information about this study. You should
ask questions about anything that is unclear to you.

PURPOSE OF THE STUDY
This study aims to understand how the teaching practices that you use may encourage and support
self-regulated learning. Self-regulated learning refers to a collection of related processes and
strategies that students may use to plan, monitor, control, and evaluate their learning in an effort
to achieve a specific goal.

PARTICIPANT INVOLVEMENT
If you agree to take part in this study, you will be asked to participate in two 30-45 minute audio-
recorded interviews, permit the researcher to observe two to three class sessions, and provide the
researcher with copies of the course syllabus and instructional materials used during the observed
class sessions. You do not have to answer any questions you don’t want to; if you do not want to
be recorded during the interviews, only handwritten notes will be taken. The observations will not
be audio or video recorded by the researcher.

Your participation in this study is voluntary and you may withdraw at any time. Your employment
is not contingent upon participating in the study.

PAYMENT/COMPENSATION FOR PARTICIPATION

You will receive a $25 gift card for your participation. You do not have to answer all of the
interview questions in order to receive the card. It will be given to you by the researcher at the end
of the data collection period (1 academic term).

CONFIDENTIALITY

Any identifiable information obtained in connection with this study will remain confidential. Your
interview responses will be coded with false names (pseudonyms) and maintained separately. The
audio files will be destroyed once they have been transcribed. You may request a copy of this
transcription. Field notes taken during class observations may include descriptions of student
APPROACHES TO SRL 115
activity. However, students will not be identified by name in these field notes or in any subsequent
analysis. The documents requested for analysis will be limited to those used to support instruction,
such as the course syllabus, activity instructions, and worksheets. They will not be used if they
contain any identifiable student information. Field notes, transcripts, and documents obtained
during the study will be stored by the researcher indefinitely under a password protected account.
However, the code key linking pseudonyms with participant identities, will be destroyed upon
completion of the research.

The members of the research team and the University of Southern California’s Human Subjects
Protection Program (HSPP) may access the data. The HSPP reviews and monitors research studies
to protect the rights and welfare of research subjects.

When the results of the research are published or discussed in conferences, no identifiable
information will be used.

INVESTIGATOR CONTACT INFORMATION

Mathew Williams
Principal Investigator

Dr. Patricia Tobey
Faculty Advisor

IRB CONTACT INFORMATION
University Park Institutional Review Board (UPIRB)
3720 South Flower Street #301
Los Angeles, CA 90089-0702
(213) 821-5272
upirb@usc.edu

STUDY ID: UP-17-00647

Abstract (if available)

Abstract Variations in how college students monitor and control their own learning can contribute to differences in important academic outcomes, including engagement and depth of understanding. Theories of self-regulated learning (SRL) indicate that one area where higher education practitioners may be able to promote more adaptive patterns of SRL is in the teaching practices employed by faculty. This study provides an in-depth account of how faculty at a large public research university approach this issue and how their teaching practices may encourage and support self-regulated learning. Five faculty participated in the study, which consisted of two interviews of each participant, course observations, and an analysis of related course documents. Data was coded and analyzed to identify patterns, themes, and relationships in the perceptions and teaching practices of the participants. Findings indicate that although participants recognized specific differences in SRL among their students and have been incorporating several promising practices, they are also encountering challenges with implementing and assessing these practices. These findings point to a need to further explore and measure the effectiveness of existing practices, while also developing new approaches to improving SRL, particularly in the areas of motivation and regulation of motivation.

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Asset Metadata

Creator Williams, Mathew (author)

Core Title Approaches to encouraging and supporting self-regulated learning in the college classroom

School Rossier School of Education

Degree Doctor of Education

Degree Program Education (Leadership)

Publication Date 07/27/2018

Defense Date 06/18/2018

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

Tag cognition,faculty perspective,Higher education,instructional strategies,Motivation,OAI-PMH Harvest,self-regulated learning,teaching practices

Format application/pdf (imt)

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Tobey, Patricia (committee chair), Combs, Wayne (committee member), Crispen, Patrick (committee member), Escalante, Michael (committee member)

Creator Email mathewlw@gmail.com,mathewwi@usc.edu

Permanent Link (DOI) https://doi.org/10.25549/usctheses-c89-35325

Unique identifier UC11669767

Identifier etd-WilliamsMa-6537.pdf (filename),usctheses-c89-35325 (legacy record id)

Legacy Identifier etd-WilliamsMa-6537.pdf

Dmrecord 35325

Document Type Dissertation

Format application/pdf (imt)

Rights Williams, Mathew

Type texts

Source University of Southern California (contributing entity), University of Southern California Dissertations and Theses (collection)

Access Conditions The author retains rights to his/her dissertation, thesis or other graduate work according to U.S. copyright law. Electronic access is being provided by the USC Libraries in agreement with the a...

Repository Name University of Southern California Digital Library

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