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PowerPoint design based on cognitive load theory and cognitive theory of multimedia learning for introduction to statistics
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Running head: POWERPOINT DESIGN FOR STATS i
POWERPOINT DESIGN BASED ON COGNITIVE LOAD THEORY AND
COGNITIVE THEORY OF MULTIMEDIA LEARNING FOR INTRODUCTION
TO STATISTICS
by
Ilder Andres Betancourt Lopez
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 of
DOCTOR OF EDUCATION
May 2014
Copyright 2014 Ilder Andres Betancourt Lopez
POWERPOINT DESIGN FOR STATS ii
POWERPOINT DESIGN FOR STATS iii
Abstract
Statistics is a complicated subject to teach because it involves interpretational,
mathematical, and logical components. Given the importance of introduction to
statistics for many non-technical students and the propensity of PowerPoint as an
instructional tool, there is a need to determine whether the application of cognitive
load theory and cognitive theory of multimedia learning provide effective principles
for manipulating PowerPoint lessons for greater learning potential. This study
evaluated the split-attention and redundancy principles in a PowerPoint lesson on z-
scores and their potential to decrease mental effort and increase learning. Through an
experimental approach, participants were recruited from an introduction to statistics
for the behavioral science courses at a community college and were randomly
assigned to one of three conditions (control PowerPoint, split-attention PowerPoint,
and redundancy PowerPoint). After watching the recorded PowerPoint lecture,
participants self-reported mental effort and answered retention and transfer test
questions to measure learning. Analyses of variance with post-hoc Tukey HSD tests
were conducted. Findings suggest that manipulating the PowerPoint with the
principles decreases mental effort and increases learning, especially for transfer.
POWERPOINT DESIGN FOR STATS iv
ACKNOWLEDGMENTS
I wish to thank my dissertation chair, Dr. Dennis Hocevar, for his expertise and
guidance through this process. I also thank Dr. Patricia Tobey and Dr. Robert Keim
for working with me and providing encouragement.
I am grateful to the students from Glendale Community College. This research
would not have been possible without their participation. I am also grateful to the
Psychology Department at GCC for their support.
The culmination of my graduate degree is dedicated to my parents, Alejandro
and Ana Betancourt, who came to this country with only a dream and incredible work
ethic. I thank them for providing me this legacy. I also dedicate this work to my two
daughters, Jael and Isabela.
Finally, I would like to thank my beautiful wife, Chris, for her patience,
understanding, encouragement, and love.
POWERPOINT DESIGN FOR STATS v
TABLE OF CONTENTS
Abstract ................................................................................................................ iii
Acknowledgments ............................................................................................... iv
List of Tables ...................................................................................................... vii
List of Figures ..................................................................................................... vii
CHAPTER 1. POWERPOINT DESIGN FOR STATISTICS AND THE SPLIT-
ATTENTION AND REDUNDANCY PRINCIPLES ..........................................1
Background of the Problem ...................................................................................1
Statement of the Problem ......................................................................................4
Purpose of the Study ..............................................................................................5
Research Questions ...............................................................................................6
Hypotheses ............................................................................................................6
Significance of the Problem ..................................................................................7
Methodology ..........................................................................................................8
Assumptions ..........................................................................................................8
Limitations .............................................................................................................8
Delimitations .........................................................................................................9
Organization of the Study ......................................................................................9
CHAPTER 2. REVIEW OF THE LITERATURE .............................................11
Literature Review ................................................................................................11
Background on Working Memory ...............................................................11
Cognitive Load Theory ................................................................................13
Cognitive Theory of Multimedia Learning ..................................................16
Split-Attention Principle (CLT) ..................................................................18
Redundancy Principle ..................................................................................21
Studies on PowerPoint and CLT and CTML Principles ..............................23
Learning Measurements ...............................................................................25
Limitations on CLT and CTML Studies ......................................................26
CLT and CTML Studies on Statistics ..........................................................28
POWERPOINT DESIGN FOR STATS vi
CHAPTER 3. RESEARCH METHODOLOGY ................................................33
Research Questions .............................................................................................33
Research Design ..................................................................................................34
Population and Sample .................................................................................36
Instructional Material ...................................................................................37
Instrumentation .............................................................................................39
Data Collection .............................................................................................40
Validity and Reliability ................................................................................41
Data Analysis ...............................................................................................43
CHAPTER 4. FINDINGS ..................................................................................45
Demographics ......................................................................................................46
Hypothesis Analyses ...........................................................................................47
Summary ..............................................................................................................54
CHAPTER 5. DISCUSSION ..............................................................................56
Design Summary .................................................................................................56
Findings ...............................................................................................................57
Contributions to Literature ..................................................................................65
Recommendations for Future Research ...............................................................65
Summary ..............................................................................................................67
References ...........................................................................................................69
Appendices ..........................................................................................................77
A. Retention Test ..........................................................................................77
B. Transfer Test ............................................................................................81
C. Mental Effort Questionnaire ....................................................................86
D. Demographic Questionnaire ....................................................................88
E. Informed Consent Form ..........................................................................90
F. Permission by Paas ..................................................................................93
G. Institutional Review Board Approval ......................................................95
POWERPOINT DESIGN FOR STATS vii
LIST OF TABLES
Table 1. PowerPoint Modifications to Each Condition ............................................... 35
Table 2. Three Phases of the Study .............................................................................. 36
Table 3. Means and Standard Deviations per Treatment ............................................. 48
Table 4. Summary of Analyses and Findings ............................................................... 54
LIST OF FIGURES
Figure 1. Working Memory and Information Flow ...................................................... 12
Figure 2. Cognitive Load Capacity and Element Interactivity ..................................... 16
Figure 3. Split-Attention Principle ............................................................................... 19
Figure 4. Redundancy Principle ................................................................................... 22
Figure 5. Self-Reported Mental Effort Means by Treatment ........................................ 48
Figure 6. Retention and Transfer Test Score Means by Treatment .............................. 51
POWERPOINT DESIGN FOR STATS
1
CHAPTER 1
POWERPOINT DESIGN FOR STATISTICS AND THE SPLIT-ATTENTION
AND REDUNDANCY PRINCIPLES
This chapter explains the need to examine the application of cognitive load
theory (CLT) and cognitive theory of multimedia learning (CTML) in developing
PowerPoint lessons for an introduction to statistic course. Additionally, it provides a
theoretical framework for CLT and CTML, the purpose of the study, the research
hypotheses, and the limitations and delimitations which form the basis of this study.
Background of the Problem
Undergraduate statistic courses for the social sciences serve as a gateway for
many social sciences majors, social service careers (counseling, for example) and as
viable options for general education math requirements (Zieffler et al., 2008). Yet,
these courses produce student anxiety towards the subject (Onwuegbuzie & Wilson,
2003) which can lead to avoidance of the course (Onwuegbuzie, 1997). The
complexity of the subject for novice learners leads to negative reputation for statistics
courses (Conners, McCown & Roskos, 1998; Gal & Ginsburg, 1994).
Statistics is a complicated subject that involves interpretational, mathematical,
and logical components. Cognitive load theory (Paas, Renkl & Sweller, 2004;
POWERPOINT DESIGN FOR STATS
2
Sweller, 1988) provides an appropriate framework for understanding and addressing
the difficult nature of statistics for novice learners. The theory evolved to address
instructional material that is high in element interactivity, or high in intrinsic load
(Sweller, 1994). Sweller (2010) uses element interactivity to describe the amount and
combination of bits of knowledge that a learner must learn, organize and apply.
Especially for novice learners in an introduction to statistics course, limited working
memory capacity (Baddeley, 1992) and high element interactivity make it difficult to
develop appropriate mental representations such as schemas of the material and to
then apply the material for solving problems (Sweller, 1988).
CLT proposes to facilitate learning of high element interactive material by
reducing extraneous load and increasing germane load to capitalize on working
memory limitations (Paas, Renkl & Sweller, 2004). The split-attention principle states
that the separation of textual and visual information in the presentation of instructional
material increases extraneous load because learners must use mental efforts to
integrate the information, efforts that do not necessarily aid in the learning of the
material. Thus, physically integrating textual and visual information reduces
extraneous load (Chandler & Sweller, 1992). The integration of textual and visual
information in instructional material benefits learning the most when the material
poses high intrinsic load (Chandler & Sweller, 1991). Statistics material for novice
learners poses such high intrinsic load because of its high element interactivity (Paas,
1992; Wang, Vaughn & Liu, 2011).
POWERPOINT DESIGN FOR STATS
3
Cognitive theory of multimedia learning (Mayer & Moreno, 2002) applies
CLT more specifically for the use of animation in instructional settings (Moreno &
Mayer, 1999). CTML has formulated principles for multimedia tools to capitalize on
the working memory’s limited and dual-channel capacities to increase learning (Mayer
& Anderson, 1991). The redundancy principle of CTML posits that on-screen text
should be excluded when audio narration is included (Mayer & Moreno, 2002). In
this way, the multimedia presentation capitalizes on the learner’s dual-channel of
working memory, a channel for audio information and a channel for visual
information. Otherwise, on-screen text may potentially overload the visual channel
(Mayer & Moreno, 1998). However, redundancy of verbal and textual information
may benefit learners when textual information can serve as an attention-guiding
mechanism. Mayer & Johnson (2008) delivered PowerPoint instructional material
where the redundancy benefited the learner. Further testing how the redundancy
principle affects PowerPoint teaching behooves instructors of statistics because, as an
animation tool often used in the classroom (Savoy, Proctor & Salvendy, 2009),
instructors serve as the live narrators during PowerPoint lectures.
Studies that apply basic principles of CTML such as the redundancy principle
show large learning effect sizes in comparison to control groups; in some cases,
reported Cohen’s ds are greater than 1.0 (Mayer & Moreno, 2002). Results are
stronger for measures of transfer, learning that occurs when participants develop
strong schemas for material that they can then apply in different cases or problems.
Effect sizes for measures of transfer can be twice as big than those of retention (Mayer
POWERPOINT DESIGN FOR STATS
4
& Moreno, 1998), which attests to CTML’s guidance towards effective learning and
schema acquisition and its potential to further benefit PowerPoint use for learning.
Studies based on CTML and, to some extent, CLT have been criticized for
their highly controlled laboratory settings (Tabbers, Martens & van Merrienboer,
2004). Often, these studies use animation software such as Adobe Flash (Mayer et al.,
1999; Mayer & Anderson, 1991; Mayer & Moreno, 1998; Moreno & Mayer, 1999;
Moreno & Mayer, 2000, Moreno & Mayer, 2002; Wang et al., 2011) that instructors
of statistics may not be familiar with. Few studies look at how PowerPoint lectures
can capitalize on CLT and CTML principles despite the fact that PowerPoint is the
most common instructional tool utilized by college instructors (Savoy et al., 2009).
Statement of the Problem
Few studies on the principles of CLT and CMTL utilize PowerPoint, an
instructional tool likely to be used by college instructors of statistics. Both CLT and
CTML provide a framework for breaking down statistics material with some
successful attempts having been made in the literature (Aguinis & Branstetter, 2007;
Paas, 1992; Wang et al., 2011). Those studies that animate statistics material (Wang
et al., 2011) use an animation program unlikely to be utilized by statistic instructors
thus limiting the studies’ usability to college instructors. The framework provided by
both theories have led to greater learning outcomes yet require more instructional
material preparation on the part of the instructor. If instructors are to invest time to
align PowerPoint statistics lessons with CLT and CMTL principles, it is important to
test the benefits to learning outcomes. Currently, it is unclear how the live narration of
POWERPOINT DESIGN FOR STATS
5
the instructor and the amount and placement of text on PowerPoint slides can affect
student learning.
Purpose of the Study
The purpose of this study is to evaluate the application of cognitive load theory
and cognitive theory of multimedia learning in a PowerPoint lesson, specifically by
applying the split-attention principle and the redundancy principle, to increase learning
in an introduction to statistics course. Randomly assigned students experienced one of
three conditions (split-attention PowerPoint lesson, redundancy PowerPoint lesson,
and a control PowerPoint lesson) with statistics material that is high in element
interactivity. Measures of learning (retention and transfer) and perceptions of mental
effort are recorded to test whether there were any statistically significant differences
between the three groups.
Both theories have been applied to the instructional design of challenging
material with high element interactivity such as statistics (Aguinis & Branstetter,
2007; Paas, 1992; Wang et al., 2011). These studies, however, did not use
PowerPoint, a multimedia tool highly likely to be used by college instructors (Savoy et
al., 2009). Given the importance of introduction to statistics and the propensity of
PowerPoint as an instructional tool, there is a need to determine whether the
application of these theories is effective enough to merit manipulation of PowerPoint
to garner greater learning potential.
This study focuses on the opportunity for theory-based interventions through
the use of common classroom tools such as PowerPoint.
POWERPOINT DESIGN FOR STATS
6
Research Questions
1. Does an animated PowerPoint lecture based on the split-attention principle
significantly decrease mental effort while learning?
2. Does an animated PowerPoint lecture based on the split-attention principle
significantly increase learning of statistics material?
3. Does an animated PowerPoint lecture based on the redundancy principle
significantly decrease mental effort while learning?
4. Does an animated PowerPoint lecture based on the redundancy principle
significantly increase learning of statistics material
5. Is there a significant difference in learner’s mental effort exertion between
watching an animated PowerPoint lecture based on the split-attention principle and
watching an animated PowerPoint lecture based on the redundancy principle?
6. Is there a significant difference in the learning of statistics material between an
animated PowerPoint lecture based on the split-attention principle and an animated
PowerPoint lecture based on the redundancy principle?
Hypotheses
1. There is a statistically significant decrease in mental effort for a group who
watched an animated PowerPoint based on the split-attention principle compared
to a control group
2. There is a statistically significant increase in learning scores (retention and
transfer) for a group who watched an animated PowerPoint based on the split-
attention principle compared to a control group
POWERPOINT DESIGN FOR STATS
7
3. There is a statistically significant decrease in mental effort between a group who
watched an animated PowerPoint based on the redundancy principle compared to a
control group
4. There is a statistically significant increase in learning scores (retention and
transfer) between a group who watched an animated PowerPoint based on the
redundancy principle compared to a control group
5. No directional hypothesis is provided for research question 5 because it is unclear
from the literatures will most decrease mental effort (split-attention principle or
redundancy principle)
6. No directional hypothesis is provided for research question 5 because it is unclear
from the literatures will most increase learning scores (split-attention principle or
redundancy principle)
Significance of the Problem
The results of this study inform instructors of statistics, particularly courses
under behavioral sciences, and any other technical and high element interactive
courses. The theory-based approach to teaching statistics utilized here best captures
the full capacity of PowerPoint as an instructional tool. By applying basic principles
of two theories, PowerPoint facilitates the learning of a topic often feared by students
(Onwuegbuzie, 1997) and often difficult to learn (Conners et al., 1998; Gal &
Ginsburg, 1994).
POWERPOINT DESIGN FOR STATS
8
Methodology
The study applies a between-subjects, single factor experimental design to
compare the effectiveness of two interventions against a control group to investigate
the research problem. Through a controlled experiment, the principles of CLT and
CTML are best tested on PowerPoint. Additionally, the study randomly assigns
students enrolled in a statistics course and introduces topics not yet covered. The
design is appropriate because a causal relationship may be established.
Assumptions
For purposes of this study, it is assumed that subjects are introspective enough
to respond to a measure of mental effort. Students have the ability to gauge their own
mental processes and limitations while learning a lesson and working through
problems. Additionally, it is assumed that students can control and follow a recorded
PowerPoint lecture. Finally, it is assumed that students can read, comprehend and
answer the measurement questions from retention and transfer tests.
Limitations
This study is limited to subjects who voluntarily agree to participate. Extra
credit in their introduction to statistics course was offered, but no further
compensation was awarded. Given the nature of the topic of study, students were
recruited while enrolled in said course. Another limitation is the nature of
convenience samples. Students for this study are enrolled in the same community
college. Thus, the samples are not true random samples.
POWERPOINT DESIGN FOR STATS
9
Delimitations
This study will confine itself to surveying students at an urban community
college located in the United States southwest. This study will focus on the split-
attention principle and the redundancy principle of CLT and CTML, and their effects
on learning statistics. Student mental effort is measured through Paas’ Cognitive Load
Mental Effort Questionnaire (1992). Student learning is measured through both a
retention test and transfer test. Only students who have not previously enrolled in the
statistics course and fully completed all phases of the study will be included in the
final analyses.
Organization of the Study
Chapter 1 of the study has presented the introduction, the background of the
problem, the statement of the problem, the purpose of the study, the questions to be
answered, the research hypotheses, the significance of the study, a brief description of
the methodology, the assumptions, limitations, and delimitations.
Chapter 2 is a review of relevant literature. It addresses the following topics:
cognitive load theory and element interactivity, cognitive theory for multimedia
learning, theory-based approaches to statistics, and studies using PowerPoint as an
instructional tool.
Chapter 3 presents the methodology used in the study, including the research
design; population and sampling procedure; and the instruments and their selection or
development, together with information on validity and reliability. Each of these
sections concludes with a rationale, including strengths and limitations of the design
POWERPOINT DESIGN FOR STATS
10
elements. The chapter goes on to describe the procedures for data collection and the
plan for data analysis.
Chapter 4 presents the results of the study. Chapter 5 discusses and analyzes
the results, culminating in conclusions and recommendations.
POWERPOINT DESIGN FOR STATS
11
CHAPTER 2
REVIEW OF THE LITERATURE
This chapter provides an overview of learning and critical studies based
on cognitive load theory (CLT) and cognitive theory of multimedia learning (CTML).
The chapter further reviews two principles and their impact on learning. The first is
known as the split-attention principle in CLT and it is known as the spatial contiguity
principle in CTML. The second is known as the redundancy principle in both CLT and
CTML. The chapter also reviews the limited research on applications of CLT and
CTML on PowerPoint lessons. And finally, the chapter also discusses studies on
teaching and learning statistics. This literature review does not address other factors
that affect student learning (such as motivation) or other factors that are outlined in the
limitation section of chapter 1.
Literature Review
Background on Working Memory
Baddeley (1992) states that working memory is divided into three components:
central executive, visuospatial sketchpad and phonological loop. The central
executive controls attention; it chooses and organizes information from the learning
environment. Because our working memory is limited and it can only maintain about
seven bits of information, the central executive works to discern through large
POWERPOINT DESIGN FOR STATS
12
amounts of information encountered in a learning environment. The visuospatial
sketchpad and the phonological loop, also referred to as the two-channel system,
stream information to the central executive. The former receives visual information
while the latter receives audio information from the learning environment. Figure 1
below visually displays the flow of information through this model of the working
memory. Although both of these channels are also limited, they are independent of
each other. CLT and CTML propose that maximizing the use of both channels
expands on the limitations of the working memory system (Paas, Renkl & Sweller,
2004). That is, if the learning environment presents information in these two
modalities (in visual and audio modes), the learner better capitalizes on the limitations
of his or her working memory.
Figure 1. Working Memory and Information Flow
POWERPOINT DESIGN FOR STATS
13
Working memory, then, is particularly important for CLT and CTML because
it is the nexus for information processing. Within working memory, the learner can
utilize prior knowledge stored in long-term memory to pair it with new information; in
this way, schemas are developed (Sweller, 1988). Alternatively, as bits of new
information are organized in the environment as large chunks, working memory can
treat each large chunk as one bit of information rather than several pieces of
information, thus allowing for more use of the limit space in working memory
(Sweller, 1994). Finally, the learning environment can guide the central executive, the
attention-controlling mechanism of the working memory, to attend to only information
relevant to the instructional material. This prevents overload of the system with
information that is irrelevant to the subject matter (Sweller, van Marrienboer, Jeroen
& Paas, 1998). This last point is most important for novice learners. These learners
often feel overwhelmed by new math problems, for example, because they do not
know how to guide their attention through high element interactivity (Sweller, 1998).
Cognitive Load Theory
Cognitive load theory (CLT) purports to increase the effectiveness of
instructional material design to prevent overload of a learner’s limited working
memory. According to CLT, instructional material can be measured for its element
interactivity (Sweller, 1994; Sweller, 1988) and material with high levels of element
interactivity requires effective use of limited working memory (Sweller, 2010). To
determine a lesson’s element interactivity, the lesson is broken down to the number of
bits of factual, conceptual, or procedural knowledge (the elements) and the level of
POWERPOINT DESIGN FOR STATS
14
intricacies involved between these bits of knowledge (the interaction) (Brunken et al.,
2003; Paas et al., 2003; Sweller, 1988). For example, the learning of literal translations
of words into another language has low element interactivity (Samur, 2012). The bits
of knowledge that is required for learning that “perro” is “dog” in Spanish includes:
(a) the word “perro,” and (b) the word “dog.” A linear interaction between these two
bits does not exhaust the working memory capacity. However, a lesson in statistics
would have high element interactivity (Paas, 1992; Wang, Vaughn & Liu, 2011).
Thus, a CLT-based approach is apt for statistics material.
According to CLT, the cognitive load in working memory is divided into three
components: intrinsic load, extraneous load, and germane load (Sweller, 2010; Sweller
1994). Intrinsic load is equivalent to the level of element interactivity. Material that is
low on element interactivity will pose a low intrinsic load on the working memory.
Intrinsic load, therefore, depends on the complexity of the material, and an instructor
cannot necessarily decrease intrinsic load (Sweller, 2010). Extraneous load refers to
information or elements in the learning material or environment that are unnecessary
for the learning of the material. This includes instructional material that includes
excessive elements such as too much text on a presentation slide. Additionally, the
presentation of material can pose extraneous load by forcing learners to guide their
attention in a seemingly complicated presentation of information such as the inclusion
the same directions multiple times at once (Chandler & Sweller, 1991). Any
instructional method that adds to the base element interactivity of the instructional
material is considered extraneous load (Sweller, 2010; Sweller, 1994). Finally,
POWERPOINT DESIGN FOR STATS
15
germane load allows learners to attend to material, organize material, and to form
preliminary schemas with material. However, germane load is made up of the
resources remaining in working memory after both intrinsic and extraneous loads are
used (Sweller, 2010).
All three loads are additive, and together, they cannot exceed the capacity of
working memory (Paas, Renkl & Sweller, 2004). Because the difficulty of the
material (or the element interactivity) cannot be altered, intrinsic load is fixed with
few exceptions (Van Merica, 2003). The remaining space of working memory is left
for extraneous and germane loads. Figure 2 below depicts the different load
availability depending on the material’s element interactivity. The instructional
delivery has the potential to pose more extraneous load than germane load. Therefore,
CLT proposes several principles for instructional deliveries that aim to reduce
extraneous load to increase germane load (van Gog, Paas, & Sweller, 2010; Sweller,
2010; Mousavi, Low & Sweller, 1995; Chandler & Sweller, 1992; Chandler &
Sweller, 1991).
POWERPOINT DESIGN FOR STATS
16
Figure 2. Cognitive Load Capacity and Element Interactivity
Cognitive Theory of Multimedia Learning
Cognitive theory of multimedia learning was developed to apply CLT to
animation and multimedia formats used for learning. CTML posits that constructivist
learning takes place within the working memory system, as described by Baddeley
(1992). Much like CLT, three major assumptions guide the theory: (a) visual and
auditory information are processed in separate channels in working memory, (b)
working memory has a limited capacity, and (c) learning occurs through active
processing of information whereby the learner can select relevant information,
organize it, and integrate it with existing knowledge (Mayer & Moreno, 2002; Mayer
& Moreno, 1998). The first point alludes to Baddeley’s two channels that process
visual and auditory information separately (as shown in Figure 1). Through this two-
channel system, potentially two different bits of information can enter the working
memory. Depending on their physical connection in the instructional presentation, the
POWERPOINT DESIGN FOR STATS
17
learner will automatically code these as one; otherwise, the learner will need to take
cognitive resources to do so (Mayer & Anderson, 1991). The use of this two-channel
system benefits learners in multimedia presentations where both visual and auditory
information are presented.
Therefore, CTML is specifically applied to learning environments that utilize
multimedia and animation. Multimedia consists of any platform that simulates motion
picture as opposed to a static picture. Apparent movement must be involved and
objects in motion must be artificially created. More importantly, the multimedia must
contain an instructional message, an explanation that is delivered in both verbal and
pictorial ways (Mayer & Moreno, 2002). In fact, CTML posits that narration is a key
to multimedia delivery because it best capitalizes on the two-channel system (Mayer,
Moreno, Boire &Vagge, 1999).
However, there are several ways to overload one channel, both channels or
working memory in general. Within CTML, this overload is referred to as cognitive
overload (Mayer & Moreno, 2003). Much like CLT, element interactivity of the
material will pose a strain on cognitive load; for CTML, this is referred to as
representational holding. The limited working memory may be overloaded with
incidental processing (referred to as extraneous load in CLT) or essential processing
(referred to as germane load in CLT). Incidental processing occurs when a learner is
forced to process nonessential aspects of the instructional delivery. Essential
processing occurs when the learner has the ability to make sense of learning material
and can appropriately attend to the material. To reduce the cognitive load, CTML’s
POWERPOINT DESIGN FOR STATS
18
principles aim to equally redistribute essential processing to both channels and reduce
representational holding by segmenting and presenting material into chunks (Mayer &
Moreno, 2003). In reducing cognitive load, the learner maximizes the combination of
representational holding and essential processing and is able to make schematic
connections with the material and information from the long-term memory.
One way CTML has proven to alleviate overload of the visual channel is by
substituting text with narration. Narration can alleviate load from the visual channel
as text is initially taken in as visual information (Mayer & Moreno, 2003). Holding
auditory words and visual pictures in working memory at the same time is best for
constructing connections with the material (Moreno & Mayer, 2002).
Split-Attention Principle (CLT) and Spatial Contiguity Principle (CTML)
The split-attention principle (CLT) and the spatial contiguity principles
(CTML) are similar principles that purport to avert cognitive overload (Mayer &
Moreno, 1999; Mayer & Moreno, 1998). These principles state that the separation of
textual and visual information in the presentation of instructional material increases
extraneous load or incidental processing because learners are forced to use mental
efforts to integrate the information, efforts that do not necessarily aid in the learning of
the material. Thus, physically integrating textual and visual information in
instructional deliveries reduces extraneous load (Sweller, 2010). When this
extraneous load is reduced, the learner does not need to add steps to his or her learning
by using cognitive resources to integrate the material. Avoiding this issue increases
germane load (Chandler & Sweller, 1992) or essential processing (Mayer & Moreno,
POWERPOINT DESIGN FOR STATS
19
2003). Figure 3 below displays two learning presentations where one uses the split-
attention principle and the other does not.
Figure 3. Split-Attention Principle
The integration of textual and visual information in instructional material
benefits learning the most when the material poses high intrinsic load (Chandler &
Sweller, 1991). In their study, Chandler and Sweller conducted six experiments to test
the split-attention principle for integrating information using both electric engineering
and biology concepts. The authors hypothesized and tested the idea that more element
interactivity in material would require more integration of text and visual information
in the material. In the first four experiments, the split-attention principle was applied
for introductory material used to train electricians. They found that complex
procedural instructions are best learned when physically integrated into a visual
diagram; for reading feasibility, the integrated text was numbered. Those who studied
material in this format outperformed a group of trainees who read a diagram with the
written steps on the side of the diagram. The trainees in the experimental group
outperformed the control group not only immediately following the lesson but also
POWERPOINT DESIGN FOR STATS
20
one week and 12 weeks after the training. Through a second experiments, the
researchers also found the following: (a) split-attention principle is less of a concern
with low element interactive material, (b) directions in low element interactive
material often went ignored because the diagram itself was easy enough to understand,
and (c) providing directions both integrated and separate from diagram actually harms
learning when material is low on element interactivity.
In a follow up study to further investigate the effects of the split-attention
principle, Chandler and Sweller (1992) find similar results. In their first experiment,
the researchers tested the effectiveness of integrating text in a diagram for a machinery
skills training program. An experimental group and a control group were given
unlimited time to study the material, which was different from the experiments
conducted in the previous study (Chandler & Sweller, 1991). The trainees were then
tested for their knowledge a week after training. The experimental group significantly
outperformed the control group. In their second experiment, the researchers looked at
the traditional structure of a psychology journal article. Specifically, they
hypothesized that the separation of methods and results sections created extraneous
load. Participants in an introduction to psychology course read an article in the
conventional format while another group of students read the same article in an
integrated format. This latter format applies the split-attention principle because it
integrates the “story” of the article into one piece rather than separate sections. The
integrated group significantly outperformed the conventional group in a retention test.
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Within CTML, the split-attention principle is known as spatial contiguity
principle and similar results are found (Moreno & Mayer, 1999). These studies and
others (Mayer & Moreno, 1998; Mousavi, Low & Sweller, 1995) support the
effectiveness of the split-attention principle. In integrating two sources of
information, primarily visual and textual, the learner has better ability to attend to both
allowing for the use of germane load. Otherwise, the learner would use extraneous
load to integrate the material in working memory before beginning to learn the
material (Sweller, 2010).
Redundancy Principle
Another principle of CLT and CMLT that aims to avert cognitive overload is
the redundancy principle. This principle states that if both narration and the text of
that narration are included in the instructional delivery that includes visual
information, the learner will experience the redundancy effect. This incidental load
overloads the visual channel (Mayer & Moreno, 1998) and creates an extra step of
adjusting attention for the learner, thus slowing essential processing (Mayer &
Moreno, 2003). The redundancy principle, then, suggests that instructional delivery
can lessen the load of the visual channel by removing text. Additionally, redundancy
principle states that if the visual information is removed, that is both narration and text
of the narration are presented without an accompanying visual picture, the visual
channel does not experience overload (Moreno & Mayer, 2002). Figure 4 below
displays two learning presentations where one uses the redundancy principle and the
other does not.
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Figure 4. Redundancy Principle
Mayer, Moreno, Boire and Vagge (1999) tested how the redundancy principle
influences the effectiveness of narration towards learning. In their study, participants
learned about a car break system. Participants who experienced both the narration and
visual information simultaneously outperformed participants who experienced a
presentation of text and narration with visual information. Learning was measured
through a retention test, which allowed the researchers to determine if the students
effectively made schematic representations of the material. The researchers concluded
that the dual representation of narration and visual information capitalizes on the dual-
channel system for information processing. Moreno and Mayer (1999), Mayer and
Anderson (1991), and Kalyuga, Chandler, and Sweller (2004) found similar results in
their multimedia presentation regarding car break systems, bicycle pumps, and
machinery usage, respectively. In the condition where participants heard only
narration, learning scores were highest. When text was not integrated on the screen,
POWERPOINT DESIGN FOR STATS
23
which contrasts CLT’s split-attention principle and CTML’s spatial contiguity effect,
participants performed better on a transfer test because of the narration. On-screen
words are processed in the visual channel and thus eliminating these has the potential
to unload from the channel but also allow for the maximization of limited attention
(Mayer & Moreno, 1998). Kalyuga, Chandler, and Sweller (2004) found that the
redundancy principle may decrease cognitive load more than the split-attention
principle.
Studies on PowerPoint and CLT and CTML Principles
The redundancy principle is complicated when considering PowerPoint
presentations made in a classroom. According to the definition of multimedia,
PowerPoint presentations are a form of live multimedia learning experiences. In
these, however, the narrator is the instructor. Mayer and Johnson (2008) investigate if
under certain conditions redundancy can facilitate learning. The researchers highlight
that the process of selecting relevant words and images, an essential processing
mechanism, is an important initial step in CTML’s model for learning. Thus, they
tested if two- or three-word descriptions placed next to the appropriate visual
information would guide learners’ attentions and facilitate their learning. In using
short descriptions, there is no need for the learners to process entire sentences.
Additionally, placing the descriptions next to the visual or diagram satisfies the split-
attention principle and spatial contiguity principle. As such, extraneous processes are
decreased. In two experiments, one presenting the workings of lighting and the other
presenting the workings of a car break, participants scored significantly higher on
POWERPOINT DESIGN FOR STATS
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retention tests when the short descriptions were used as compared to a presentation
that did not use any text (fully applying the redundancy principle). However, no
significant differences were found in transfer test scores.
Other studies have applied CLT and CTML principles to the use of PowerPoint
with strong results supporting the principles of these theories (Chang, Chien, Chiang,
Ming-Chao & Hsin-Chih, 2013; Mayer, Griffith, Jurkowitz & Rothman, 2008; Savoy,
Proctor & Salvendy, 2009). The Savoy et al. (2009) study looked at PowerPoint and
how the default settings of PowerPoint may not be conducive to learning because the
default settings do not necessarily apply CTML’s principles. Researchers prepared a
simple PowerPoint presentation for a class on industrial engineering that did not
animate information. A group of students received the lecture with this PowerPoint
while other students received a traditional lecture with the use of a chalkboard. While
the retention of oral information was low for the PowerPoint group, there were no
other significant differences in learning between the groups. The simple use of
PowerPoint then is not enough to facilitate learning. However, the researchers also
discovered that students perceived information on the PowerPoint as more important
than oral information or chalkboard information and students prefer PowerPoint
lecture over traditional lecture. This suggests that college students automatically draw
their attention to PowerPoint slides and thus come to expect more learning from this
tool.
In his quasi-experimental study using several classes on literature search and
access, Wecker (2012) also studied the impact that the use of PowerPoint has on the
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retention of oral information. He finds a speech suppression effect where PowerPoint
slide information subdues all other information in the classroom such as the lecturer’s
vocal information. Wecker finds that this is not due to exhausting cognitive load of
students, as students reported low mental effort and the material is low on element
interactivity. Instead, Wecker attributes the findings to a “dysfunctional allocation of
attention,” whereby students place much more emphasis on the PowerPoint slides and
no attention is placed on the narrator. He finds that students who rate PowerPoint as
highly important performed the worst on retention tests for the oral information. He
proposes the use of “concise” PowerPoint presentation whereby slides contain
minimal information and black slides with no text provided are used when the lecturer
wants to draw attention to oral information.
It is important to reiterate that in the Wecker (2012) study, material covered by
this presentation was low on element interactivity and constitutes factual knowledge,
two areas where CLT and CTML are not necessarily suggested. Regardless, the study
points to current student adjustments and expectations of a PowerPoint lesson. Of
interest, then, is the Mayer and Johnson (2008) study because the researchers decrease
the amount of textual information. In doing so, learners were better able to select and
attend to information on the screen. In this case, PowerPoint still facilitated learning.
Learning Measurements
The effectiveness of these principles on learning outcomes has been measured
using retention and transfer tests (Chandler & Sweller, 1991; Chandler & Sweller,
1992; Mayer & Moreno, 1998; Mayer & Moreno, 2002; Mayer, Moreno, Boire &
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26
Vagge, 1999; Moreno & Mayer, 1999). Retention tests denote a learner’s ability to
make representational connections with the material during the instructional delivery;
they measure factual and conceptual understanding (Anderson et al., 2001). A strong
score in a retention score indicates that the instructional delivery maximized essential
processing. The transfer tests are even stronger indicators of learning; it measures
conceptual understanding and the learner’s ability to apply it (Anderson et al., 2001).
Transfer looks at the learner’s ability to use learned material in a new situation. In
fact, when some of the aforementioned studies applied CTML principles for
experimental groups, Cohen’s d was greater for transfer test scores than for retention
test scores; at times, Cohen’s d was doubled. That is, the CTML principles cause an
even greater effect on transfer than on retention for learners (Mayer & Moreno, 2002;
Mayer & Moreno, 1998).
Studies that have applied the split-attention principle and the redundancy
principle show strong evidence for learning. These studies measure learning with a
test of transfer, and in comparing a control group with a group that received
instruction founded in the redundancy principle, there are large effects separating the
two groups. The median Cohen’s d among spatial contiguity principle studies is 0.48
while the median Cohen’s d among redundancy principle studies is 0.77 (Mayer &
Moreno, 2002).
Limitations on CLT and CTML Studies
Studies of these principles do have drawbacks such as low ecological validity
and generalizability. In their study, Tabbers, Martens and van Merrienboer (2004)
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27
aimed to address these concerns. The study addresses criticisms that previous CTML
studies took place in highly controlled laboratory settings and that the principles could
not be generalized to classroom settings. In the study, the authors developed web-
based multimedia lesson on the topic of instructional design. Applying principles of
CTML to an online course format, the authors provided a realistic environment for
online learners. Learners controlled time-on-task for learning whereas in previous
studies, time for all conditions was based on narration length (Mayer & Anderson,
1991; Mayer & Moreno, 1998; Moreno & Mayer, 2000). In conducting this
experiment, Tabbers et al. concluded the following that supports CTML principles: (a)
participants report less mental effort for animated instruction that utilized the
redundancy principle, and (b) participants scored higher on retention test when
presentation includes animation. Alternatively, conclusions reached by this study that
contrast CTML principles’ purposes include: (a) participants with visual text spent less
time studying, and (b) participants that experienced redundancy effect scored higher
on retention and transfer tests. The authors note that these conclusions may suggest
that previous research on CTML principles may be more suitable for procedural
information (like statistics) as this particular study utilized instructional design as its
course content. Additionally, the authors note that previous research on CTML
principles may be more effective when instructional deliver is system-paced, much
like a live lecture, rather than learner-paced.
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CLT and CTML Studies on Statistics
There are few studies around the topic of teaching statistics where CLT or
CTML principles have been applied. The following section highlights some of these
studies while also highlighting their limitations. The limitation of these kinds of
studies allow for the opportunity to further investigate the teaching methods for
statistics.
In one of the first studies to use cognitive load theory to teaching statistics,
Paas (1992) applied the idea of element interactivity to explain students’ methods for
problem solving. Paas hypothesized that students benefit more from studying worked-
out problems or by completing partly worked-out problems than they would solving a
conventional problem from beginning. His hypothesis was based on the idea that
statistics problems are high in element interactivity, and that several bits of knowledge
interact for one problem. Worked-out or partially worked-out problems alleviate
cognitive load from learners because they no longer have to juggle several elements in
their working memory. Instead, they can focus on the sense-making process for the
problem. This especially proved effective for novice learners, who according to Paas
(1992) and Sweller (1988), tend to engage in means-ends analysis, a strategy for
solving problems where by learners experience cognitive overload because they try to
maintain too many subgoals in working memory.
After receiving general instructions, participants in Paas’ study were divided
into three groups that practiced the instructional material via a conventional problem, a
worked-out problem, or a partially worked-out problem. Afterwards, participants took
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a transfer test. Participants in the conventional problem condition significantly scored
lower on the transfer test than the participants in the other two conditions. These
students also scored higher on a self-reported measure of mental effort. With these
results supporting worked-out and partially worked-out problems, Paas suggests that
transfer abilities were stronger because these two conditions may have allowed for
better schema acquisition.
A similar study by Leppink et al. (2012) found that novice learners benefit a
great deal from worked-out examples because it allows these learners to gain
propositional knowledge and conceptual knowledge. However, more experienced
learners gained less from worked-out problems and gained more from formulating
arguments about statistical data and test results, even though experienced learners self-
reported a higher mental effort in this condition than did novice learners in the
worked-out problems condition.
In a study of teaching statistics through an interactive computer simulation,
Wang, Vaughn and Liu (2011) used the concept of animation interactivity to test
student learning. Depending on the degree of animation interactivity, the learners had
different degrees of control over the presented content. The degree of control was
manipulated as follows: (a) information was static with no animation, (b) information
had some animation, (c) information could be manipulated by inputting answers
(adjusting to learner correct or incorrect answers), or (d) information input influenced
the provided feedback to your answers. Novice learners were taught concepts of
hypothesis testing, and were then tested on learning and confidence through a pre-and-
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post test design; participants also rated their perception of the program. While
participants had a positive perception of the program in all conditions, the level of
animation of interactivity did not significantly impact confidence towards the material.
Additionally, only some measures of learning, such as understanding and lower-level
application, were impacted. Unlike previously mentioned CTML studies, there was
no significant impact on retention or higher-level transfer. The researchers note that
this may be due to lack of confidence or competence in using a computer program to
learn statistics. Even though the participants appreciated the new setting, as indicated
by their positive perception rating of the program, it is still a new format from which
to learn complicated material.
Other studies considered guiding questions as a method for learning statistics.
Van Merrienboer and Sweller (2005) indicated that guiding questions could reduce
cognitive load because these breaks down high element interactive material into more
digestible chunks. This, in turn, allows more room in working memory for the
formation of knowledge structures about the subject matter. Two studies studied this
hypothesis. In the first, Bude, van, Imbos and Berger (2012) used guiding questions to
attempt to lower cognitive load and increase learning and understanding of statistics.
In one group, students received guiding questions for a problem until reaching the
“achievement” questions. In the other group, no guiding questions were asked.
Although there were no differences in self-reported cognitive load, students in the
“guiding questions” group scored higher on measures of achievement and transfer test
questions. In this experiment, no formal instruction was given during the experiment.
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These students were allowed to participate after a class lecture on the topic. Here,
students underwent an authentic classroom experience before the study, but the
structure of the lecture was not studied. Novice learners benefitted from guiding
questions and additional information about the problem to help conceptualize the
issue.
In a final study, Anguinis and Branstetter (2007) apply both CLT and CTML
to their classroom setting in an action research study. The study took a quasi-
experimental approach and divided students into two groups (traditional lecture group
and a theory-based teaching approach group). Additionally, the research conducted a
pre-post comparison design to measure for increase in statistics knowledge. In fact,
those students who underwent the theory-based teaching approach significantly
increased in statistics knowledge than the other group. However, this study does not
go into detail about the differences of both teaching approaches. Although it mentions
the CLT and CMTL principles used in their theory-based teaching approach, it falls
short of providing specific application of theses.
Several limitations exist with the aforementioned statistics studies. In Paas’
study (1992), the methodology included a computer-based training strategy. That is,
this study did not simulate a classroom environment. Also, the Leppink et al. study
(2012) was conducted in a laboratory setting with conventional paper materials. While
the Wang, Vaughn, and Liu study (2011) and the Anguinis and Branstetter study
(2007) attempt to apply CLT and CTML principles in a more realistic setting, they
also maintain limitations. Wang, Vaugh and Lie (2011) use a computer program that
POWERPOINT DESIGN FOR STATS
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may be too complex to program for statistics professors. Anguinis and Branstetter
(2007) do not supply enough information about the instructional materials to replicate
their study or their efforts in the classroom.
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CHAPTER 3
RESEARCH METHODOLOGY
The purpose of the study is to investigate the application of cognitive load
theory (CLT) and cognitive theory for multimedia learning (CTML) to the design of
lecture instruction, specifically by redesigning aspects of statistics PowerPoint lessons
to comply with the effects of split-attention and redundancy principles. This chapter
discusses the research questions, the hypotheses, and a description of the research
methodology. The latter includes the population and sampling procedure,
instructional material, instrumentation, and procedures for data collection and
analysis.
Research Questions
1. Does an animated PowerPoint lecture based on the split-attention principle
significantly decrease mental effort while learning?
2. Does an animated PowerPoint lecture based on the split-attention principle
significantly increase learning of statistics material?
3. Does an animated PowerPoint lecture based on the redundancy principle
significantly decrease mental effort while learning?
4. Does an animated PowerPoint lecture based on the redundancy principle
significantly increase learning of statistics material?
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34
5. Is there a significant difference in learner’s mental effort exertion between
watching an animated PowerPoint lecture based on the split-attention principle and
watching an animated PowerPoint lecture based on the redundancy principle?
6. Is there a significant difference in the learning of statistics material between an
animated PowerPoint lecture based on the split-attention principle and an animated
PowerPoint lecture based on the redundancy principle?
Research Design
The study utilized a between-subjects, single factor experimental design with a
control group and two experimental groups. The experimental groups in this study
watched an animated PowerPoint lecture on z-scores with modifications to the
placement of text, and the control group watched the same animated PowerPoint
lecture with bullet lists for the text separated from visual information. Participants
were randomized into one of the three conditions.
Table 1 outlines the specific modifications made to each condition. These
modifications are the independent variables (split-attention/spatial contiguity principle
and redundancy principle).
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Table 1.
PowerPoint Modifications to Each Condition
Group CLT and CTML Effect
Tested
Modifications to PowerPoint
Lecture
Control
(CNT)
None None: Text information
presented as bullet list while
separated from corresponding
visual information
Experiment Group 1
(SPA)
Split-Attention (CLT)/
Spatial Contiguity
Principle (CTML): close
proximity of material (such
as words and visual aids)
reduces extraneous load
Text information location
adjusted to be integrated with
corresponding visual
information
Experiment Group 2
(RPA)
Redundancy Principle
(CLT/CTML): Excluding on-
screen text when including
narration reduces extraneous
load
Text information removed
(with the exception of key
“markers”)
The three groups underwent the following three phases during the study
(outlined in table 2). In phase one, participants individually watched the instructional
material, a recorded PowerPoint lecture on z-scores and probability on a computer
screen. In phase two, participants took retention and transfer tests. In phase three,
participants filled Paas’ (1992) cognitive load measurement test. This test is a self-
reported measure where participants report perceived levels of mental effort
experienced during the learning and application of the material. This three-phased
design has been used by several CLT and CTML studies (Moreno & Mayer, 1999;
Moreno & Mayer, 2000; Moreno & Mayer, 2002; Mousavi, Low & Sweller, 1995) to
measure for learning and self-reported cognitive load.
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Table 2.
Three Phases of the Study
Phase 1 Phase 2 Phase 3
Instructional
material:
PowerPoint lecture
on a computer screen
Retention and
transfer tests:
Retention and transfer
questions
Cognitive load test:
Paas’ (1992) mental
effort measurement
test
The dependent variables include the retention test scores, the transfer test
scores, and the mental effort rating. For the purposes of this study, learning was
measured through retention of the instructional material and ability to transfer and
apply material to similar problems. The retention test provides an indication for the
extent to which the instructional material guided participants’ selective attention to
better retain information. The transfer test provides an indication for the extent to
which the instructional material helps participants understand concepts in order to
make inferences (Mayer, Moreno, Boire & Vagge, 1999). Paas’ (1992) cognitive load
measurement test provides an indication for the extent to which the instructional
material imposed mental effort as an indicator of cognitive load.
Population and Sample
The target population for this study is undergraduate students enrolled in
introduction to statistics for the behavioral sciences. The sample was selected from an
urban community college in the United States southwest. Students enrolled in an
introductory statistics course under the psychology department during the fall semester
of 2013 were recruited.
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37
At the beginning of the semester, students enrolled in these courses were
offered extra credit for participation. Students who decided not to participate were
offered an alternative opportunity for extra credit. Interested students were asked to
participate during the second week of the semester before the course covered z-scores.
Participants were randomly assigned into one of the three conditions.
Students who previously enrolled in an introduction to statistics course were
excluded from the analyses. Students who experience computer difficulties during the
experiment were excluded from the analyses as well.
Instructional Material
A 15-minute PowerPoint lesson on z-scores and probability was used. The
lesson presents the following information: (a) standard deviation as arms extending
out from the mean, (b) z-scores as counts of standard deviation, (c) the z-score scale,
(d) calculation of a z-score from an X value, and (e) using z-scores to find proportions
under the bell curve. The lesson was developed using the following two learning
objectives: (a) students should understand that a z-score provides a precise description
of a location in a distribution based on the distribution’s standard deviation, and (b)
students should understand and identify simple probability from the bell curve (68%,
95%, 2.5%) based on whole-numbered z-scores. The lesson assumes that participants
do not have an understanding of standard deviation. Therefore, it presents a standard
deviation as arms that extend out from the mean on a normal curve where one arm
extended out on both sides of the mean captures 68% of the scores and two arms
POWERPOINT DESIGN FOR STATS
38
extended out on both sides of the mean captures 95% of the scores. The lesson does
not present a method for calculating a standard deviation.
The PowerPoint was created using Microsoft PowerPoint 2008 for Mac
version 12.0 using a Mac Operating System X version 10.7.5. The PowerPoint
contains both text and images to explain the concepts. In the control group (CNT), the
text was maintained in one text box. Every textual piece of information is numbered
so that collectively the text on the slide appears as a bullet point list, a default setting
of the PowerPoint program. In the split-attention group (SPA), the text was broken up
into separate text boxes. Every numbered piece of information (from the CNT
PowerPoint) was placed in its own text box. Each textbox was located in proximity to
its corresponding visual information. The font size of the text was the same as in the
CNT PowerPoint. In the redundancy group (RPA), textual information was removed.
Only the numbers that appeared in both CNT and SPA to order the textual information
was used. The font size of the numbers was the same as in the CNT and SPA
PowerPoint lessons. For all three PowerPoints, the “Custom Animation” function of
PowerPoint is used. Every textbox and its corresponding visual information
separately emerged onto the slide but did not separately disappear from the slide.
For narration purposes, one master script was used. The script applied to all
three PowerPoint lessons. No instructors from the community college served as the
voice of the narrator for the lesson. The recording of the voice narration was done
using Audacity 2.0.3 with a Mac Operating System X version 10.7.5.
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39
The recording of each PowerPoint lesson was done using QuickTime Player
version 10.1 with a Mac Operating System X version 10.7.5. The combination of each
PowerPoint lesson video and voice narration was done using iMovie version 8.0.6
with the same Mac operating system.
Instrumentation
Based on Paas’ work (1992), Mayer et al.’s work (1999), and content-based
assessments, survey instruments were developed and used to collect participant
responses to key construct items. For this study, the following instrumentation is
used: (a) retention and transfer test to elicit scores regarding mastery of the content,
(b) Paas’ (1992) mental effort measure to elicit data regarding participants’ cognitive
load during instruction, and (c) survey questionnaire to elicit data regarding student
characteristics.
1. Retention and transfer tests. Content-based questions were developed to test
the learning outcomes of participants (Appendix A and B). The questions were
structured as multiple-choice measures of content mastery based on the two learning
objectives. Multiple-choice instruments were also used for measuring learning
outcomes in previous studies focusing on cognitive load (Paas, 1992) and CTML
(Wang et al., 2011). The retention test is a recall test with 12 questions developed
based on the z-score content covered by the PowerPoint lesson. The transfer test is an
application test with 12 questions developed based on new problems with similar
procedural and inferential content covered by the PowerPoint lesson. An original of
30 questions (15 retention and 15 transfer questions) were evaluated for content
POWERPOINT DESIGN FOR STATS
40
validity by a panel of current statistics instructors at the undergraduate level. An item
analysis was conducted with 35 students enrolled in an introduction to statistics course
in the summer 2013 semester. The review and analysis resulted with the remaining 12
retention and 12 transfer questions.
2. Paas’ (1992) Cognitive Load Mental Effort Questionnaire (Appendix C), a
9-point Likert-scale test, was used to measure cognitive load. Students self-reported
the level of mental effort they felt they utilized while watching the PowerPoint lecture.
The questionnaire’s reliability (alpha > 0.8) and convergent, construct, and
discriminate validity have been demonstrated (Gimino, 2000; Paas, van Merrienboer
& Adam, 1994). Paas extended permission for the use of the questionnaire in this
study (Appendix F).
3. In a demographic questionnaire (Appendix D), students provided
information such as previous statistics experience, race and gender. The first item was
used to check for prior knowledge. The last two items were used to assess if the
PowerPoint lecture inadvertently benefited particular groups of participants.
Data Collection
Participants were given a notice of Informed Consent (Appendix E) prior to
beginning the study. A signature was required to continue with the study. Participants
accessed the PowerPoint lesson video through Windows Media Player on a Lenovo
ThinkCentre computer with a Windows 7 operating system and a 23 inch Lenovo
monitor. Each computer in a lab was assigned one of three conditions for the study.
Participants were randomized to a condition. The computer number, date, and time of
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41
participation were recorded with all the participant’s materials. In this way, data was
coded and inputted into SPSS for further analyses.
To hear the 15-minute PowerPoint lesson, participants were given headphones
to connect to the computer. These were given to the participants as a gift for
participation at the end of the study. Participants were told not to stop the video and to
finish watching it in its entirety.
After watching the lecture, students completed the retention and transfer tests
on paper. Participants were provided space on the test paper to work out problems.
They were asked to circle the correct answer out of four possible answers for each of
the 12 questions per test. Ten minutes were provided for each test’s completion.
In the final phase, participants were given Paas’ (1992) mental effort
questionnaire and a demographic questionnaire on paper. After completing the form,
participants were thanked and debriefed.
Validity and Reliability
Internal validity is achieved by conducting a true experiment and randomly
assigning participants to three conditions, one of which was a control. All students
had equal chance of being chosen for one condition and as such individual difference
factors are spread throughout the study (Goodwin, 2008). Additionally, the lesson
format followed suit with an introduction to statistics textbook (Gravetter & Wallnau,
2011) and two statistics instructors of the same community college where the study
took place agreed that the PowerPoint lesson covers material appropriately. Finally,
the study’s use of both a retention and transfer test increases the construct validity.
POWERPOINT DESIGN FOR STATS
42
This study provides two measures to address learning of participants, which also
increases measurement validity.
Threats to statistical conclusion validity are addressed by using retention and
transfer tests that had alpha levels of at least .70 (as reported in Chapter 4) and by
having a total of 12 questions on each of these tests. In this way, power is not
diminished because low reliability and restriction of range of measurements are
avoided. Additionally, running a one-way ANOVA first (discussed below) avoids an
inflated Type I error rate that may come with running several statistical tests for
comparing three groups. Finally, power analysis for a one-way ANOVA was
conducted using G*Power 3.1.7 to address statistical power. Assuming an alpha level
of .05, a large effect size of .25, and a statistical power level of .08, it was determined
that at least 35 participants per group were needed, and this was met.
External validity is achieved because the instructional material is a recorded
lecture unlike studies on CLT and CTML that simulate a game or an online animated
demonstration (Wang et al., 2011) or that rely on online learning techniques (Tabbers
et al., 2004). Because the intent of this study is to investigate whether CLT and
CTML principles used on a PowerPoint lesson may impact learning, a recording
provides a controlled and realistic simulation. In this way, threats to setting and
treatment validity are addressed. The study does not place participants in a live lecture
because of the numerous confound variables associated with such an approach.
Finally, the participants did self-select to enroll in the statistics course. However, this
POWERPOINT DESIGN FOR STATS
43
study’s intended population is students who would enroll in such a course, thus
addressing sample validity.
Data Analysis
The three groups were either coded as 1 (CNT), 2 (SPA) or 3 (RPA). Number
of correct answers for the retention test and for the transfer test was recorded for each
participant. Cognitive load was coded using the 9-point Paas scale, where 1 represents
a low mental effort and 9 represents a high mental effort. From the demographic
questionnaire, gender is recorded as 1 (female) or 2 (male) and race and ethnicity is
recorded as 1 (American Indian), 2 (Asian or Asian American), 3 (African American),
4 (Latino), 5 (Native Hawaiian), 6 (White), or 7 (Other or Unreported). All data was
stored in Microsoft Excel and transferred to SPSS 21.0 (Statistical Package for Social
Sciences) for analyses. Descriptive statistics were calculated to summarize and
describe the data from this study. Sample sizes, means, and standard deviations were
reported for each group’s retention test, transfer test, and cognitive load scores.
The study was a between-subject, single factor design. Using SPSS, a one-
way analysis of variance (ANOVA) test was applied to find significant differences
among the three groups for the retention test scores, transfer test scores, and Paas
mental effort scores. A post hoc Tukey’s HSD test will also be run to find differences
between two groups. To test the first and second hypotheses on split-attention, the
SPA group will be compared to the CNT group. To test the third and fourth
hypotheses on redundancy principle, the RPA group will be compared to the CNT
group. To test the fifth and sixth hypotheses on the differences between split-attention
POWERPOINT DESIGN FOR STATS
44
and redundancy principles, the SPA group were compared to the RPA group.
Additionally, Cohen’s d was calculated for all three comparisons to measure effect
sizes. Effect size measures the relationship strength between two variables and shows
the magnitude of change caused by the independent variables (Gravetter, & Wallnau,
2011). As such, appropriate comparisons can be made to studies of CTML (Mayer &
Moreno, 1998; Mayer & Moreno, 2002), all of which report effect sizes as Cohen’s d.
POWERPOINT DESIGN FOR STATS
45
CHAPTER 4
FINDINGS
The purpose of the study was to investigate the application of CLT and CTML
to the design of a PowerPoint statistics lesson. Specifically, a control animated
PowerPoint lesson on z-scores was redesigned to comply with either the split-attention
principle or the redundancy principle. Participants were randomly assigned to watch
one of the three different PowerPoint lessons (control, split-attention, or redundancy
conditions) on an individual computer screen. After the 15-minute lesson, participants
were measured on both perceptions of mental effort and learning performance to
determine whether there were any significant differences. This chapter presents the
data collected and the findings based on those data, including sections on
demographics, hypothesis analyses, and summary.
This study utilized a between-subjects, single factor experimental design with a
control group and two experimental groups. The sample was drawn from students
enrolled in an introduction to statistics for the behavioral sciences course during the
fall 2013 semester at an urban community college located in the US southwest.
Participants were recruited from nine sections out of 11. Two sections were omitted
from the study because their lab rooms differed from the other nine sections. The total
number of participants was 170.
POWERPOINT DESIGN FOR STATS
46
Data were gathered using the instruments specified in chapter 3, including a
retention test (12 questions), a transfer test (12 questions), mental effort questionnaire
(3 questions), and a demographic questionnaire. Content validity of the learning
measures was obtained through expert review and revision of the instruments through
an item analysis. Analysis indicated a reliability measure for the retention test of
alpha = .70 and a reliability measure for the transfer test of alpha = .72. An instrument
using the rating scaled developed by Paas (1992) was used to measure mental effort as
an indicator of cognitive load. The scale’s reliability (alpha > .8) and convergent,
construct, and discriminate validity have been previously demonstrated (Paas et al.,
1994).
Demographics
A total of 170 students took part in the overall study, but the findings reflect
the results of N = 162 participants. Eight students were removed from analyses. Six
of these students were removed because they indicated on the demographic
questionnaire enrollment in a previous introduction to statistics course for at least
three weeks. Two students were removed because they experienced technical
difficulties during the study.
The following descriptive information reflects the N = 162 eligible
participants. Respondents indicated that 80% were female and 20% were male. This
is reflective of the enrollment of the nine sections were 70% of students were female
and 30% of students were male. Respondents indicated that 48% were White, 38%
were Latino, 6% were Asian or Asian American, 4% were African American, 2%
POWERPOINT DESIGN FOR STATS
47
were Native American or Native Hawaiian, and 2% did not report a specific race or
ethnicity. These figures roughly approximate the total population of the community
college students, with the exception of Latino students showing a somewhat higher
percentage in the sample group. The average age for participants was M = 25.6 with a
SD = 7.5, which is also reflective of the student population at the community college.
Hypothesis Analyses
The following section provides the results of statistical analyses testing each of
the reported hypotheses and research questions. These separately address three
dependent variables: mental effort, retention of information, and transfer of
information. The results are divided into these three categories and specific
hypotheses and research questions are addressed therein.
The means of three treatments, which include a control PowerPoint (CNT), a
split-attention PowerPoint (SPA), and a redundancy PowerPoint (RPA), are compared
using one-way ANOVAs for each of the three dependent variables. Analyses with
significant results are followed by Tukey HSD post-hoc tests to address hypotheses
and research questions that make comparisons of two treatments. Table 2 provides the
number of participants for each treatment (CNT, SPA, and RPA) and the mean and
standard deviation for each of the three dependent variables.
POWERPOINT DESIGN FOR STATS
48
Table 3.
Means and Standard Deviations per Treatment
Mental Effort
(9-point scale)
Retention Test
(12 questions)
Transfer Test
(12 questions)
Treatment N M SD M SD M SD
CNT 53 6.26 1.38 7.45 2.70 6.04 2.66
SPA 55 5.59 1.38 8.49 2.28 8.24 2.57
RPA 54 5.50 1.62 8.50 2.11 7.52 2.49
Mental Effort
Figure 5 illustrates the mean differences in self-reported mental effort between
the three treatments. More mental effort was reported in the CNT group (M = 6.26,
SD = 1.38) than in the SPA group (M = 5.59, SD = 1.38) and the RPA group (M = 5.5,
SD = 1.62). An analysis of variance indicated that there was at least one significant
difference between the reported mental efforts, F(2,159) = 4.34, p = .015, η
2
= .051.
To address specific hypotheses and research questions regarding mental effort, post
hoc Tukey HSD tests were conducted. Cohen’s d was also calculated to measure
effect size where applicable.
Figure 5. Self-Reported Mental Effort Means by Treatment
POWERPOINT DESIGN FOR STATS
49
H1: There is a statistically significant decrease in mental effort for a group who
watched an animated PowerPoint based on the split-attention compared to a control
group
A Tukey HSD test indicated that the mean scores of mental effort for the SPA
group (M = 5.59, SD = 1.38) and the CNT group (M = 6.26, SD = 1.38) differed
significantly at p = .047. The group who watched a PowerPoint based on the split-
attention principle reported a decreased mental effort as compared to the group who
watched the control PowerPoint. Cohen’s d was calculated at d = .488. The effect
size was found to be near Cohen’s (1988) convention for a medium effect (d = .5).
H3: There is a statistically significant decrease in mental effort between a group who
watched an animated PowerPoint based on the redundancy principle compared to a
control group
A Tukey HSD test indicated that the mean scores of mental effort for the RPA
group (M = 5.50, SD = 1.62) and the CNT group (M = 6.26, SD = 1.38) differed
significantly at p = .021. The group who watched a PowerPoint based on the
redundancy principle reported a decreased mental effort as compared to the group who
watched the control PowerPoint. Cohen’s d was calculated at d = .508. The effect
size was found to be near Cohen’s (1988) convention for a medium effect (d = .5).
RQ5: Is there a significant difference in learner’s mental effort exertion between
watching an animated PowerPoint lecture based on the split-attention principle and
watching an animated PowerPoint lecture based on the redundancy principle?
POWERPOINT DESIGN FOR STATS
50
A Tukey HSD test indicated that the mean scores of mental effort for the SPA
group (M = 5.59, SD = 1.38) and the RPA group (M = 5.5, SD = 1.62) did not differ
significantly at p = .944. This result suggests that no differences in mental effort were
experienced between the group who watched a PowerPoint based on the split-attention
principle and the group who watched a PowerPoint based on the redundancy principle.
Retention Test and Transfer Test Scores
Figure 6 illustrates the mean differences in retention test scores and transfer
test scores between the three groups. Retention test scores were lowest in the CNT
group (M = 7.45, SD = 2.70) compared to the SPA group (M = 8.49, SD = 2.28) and
the RPA group (M = 8.50, SD = 2.11). An analysis of variance indicated that there
was at least one significant difference between the retention test score means, F(2,159)
= 3.44, p = .035, η
2
= .041.
Transfer test scores were also the lowest in the CNT group (M = 6.04, SD =
2.66) compared to the SPA group (M = 8.24, SD = 2.56) and the RPA group (M =
7.52, SD = 2.49). An analysis of variance indicated that there was at least one
significant difference between the transfer test score means, F(2,159) = 10.20, p =
.000, η
2
= .114.
To address specific hypotheses and research questions about learning, post hoc
Tukey HSD tests were conducted. Cohen’s d was also calculated to measure effect
size where applicable.
POWERPOINT DESIGN FOR STATS
51
Figure 6. Retention and Transfer Test Score Means by Treatment
H2: There is a statistically significant increase in learning scores (retention and
transfer) for a group who watched an animated PowerPoint based on the split attention
principle compared to a control group
Retention Test.
A Tukey HSD test indicated that the mean scores on the retention test for the
SPA group (M = 8.49, SD = 2.28) and the CNT group (M = 7.45, SD = 2.70) did not
differ significantly; the differences in means approached significance at p = .063. The
findings suggest a trend where the retention test score mean for the group who
watched a PowerPoint based on the split-attention principle was an increase from the
score mean for the group who watched the control PowerPoint.
Transfer Test
A Tukey HSD test indicated that the mean scores on the transfer test for the
SPA group (M = 8.24, SD = 2.57) and the CNT group (M = 6.04, SD = 2.66) differed
POWERPOINT DESIGN FOR STATS
52
significantly at p = .001. Participants who watched a PowerPoint based on the split-
attention principle scored higher on the transfer test as compared to the participants
who watched the control PowerPoint. Cohen’s d was calculated at d = .841. The
effect size was found to exceed Cohen’s (1988) convention for a large effect (d = .8).
H4: There is a statistically significant increase in learning scores (retention and
transfer) between a group who watched an animated PowerPoint based on the
redundancy principle compared to a control group
Retention Test.
A Tukey HSD test indicated that the mean scores on the retention test for the
RPA group (M = 8.50, SD = 2.11) and the CNT group (M = 7.45, SD = 2.70) did not
differ significantly; the differences in means approached significance at p = .061. The
findings suggest a trend where the retention test score mean for participants who
watched a PowerPoint based on the redundancy principle was an increase from the
score mean for the group who watched the control PowerPoint.
Transfer Test
A Tukey HSD test indicated that the mean scores on the transfer test for the
RPA group (M = 7.52, SD = 2.49) and the CNT group (M = 6.04, SD = 2.66) differed
significantly at p = .009. Participants who watched a PowerPoint based on the
redundancy principle scored higher on the transfer test as compared to the participants
who watched the control PowerPoint. Cohen’s d was calculated at d = .574. The
effect size was found to exceed Cohen’s (1988) convention for a medium effect (d =
.5).
POWERPOINT DESIGN FOR STATS
53
Research Question 6: Is there a significant difference in the learning of statistics
material between an animated PowerPoint lecture based on the split-attention principle
and an animated PowerPoint lecture based on the redundancy principle?
Retention Test.
A Tukey HSD test indicated that the mean scores on the retention test for the
SPA group (M = 8.49, SD = 2.28) and the RPA group (M = 8.50, SD = 2.11) did not
differ significantly. The means in retention scores for participants in both treatments
were almost similar with a difference of .01.
Transfer Test
A Tukey HSD test indicated that the mean scores on the transfer test for the
SPA group (M = 8.24, SD = 2.57) and the RPA group (M = 7.52, SD = 2.49) did not
differ significantly at p = .315. Although not significant, the findings suggest a trend
where participants who watched the PowerPoint based on the split-attention principle
scored higher on the transfer test as compared to participants who watched the
PowerPoint based on the redundancy principle.
Table 4 summarizes the findings from these analyses.
POWERPOINT DESIGN FOR STATS
54
Table 4.
Summary of Analyses and Findings
Hypothesis Treatment
Comparisons
Dependent
Variable
Test p-values Effect Size
Mental
Effort
3 Groups Mental
Effort
One-Way
ANOVA
.015* Medium
(η
2
= .051)
H1 SPA v. CNT Mental
Effort
Tukey HSD .047* Medium
(d = .488)
H3 RPA v. CNT Mental
Effort
Tukey HSD .021* Medium
(d = .508)
RQ5 SPA v. RPA Mental
Effort
Tukey HSD .944 -
Retention 3 Groups Retention
Test Score
One-Way
ANOVA
.035* Medium
(η
2
= .041)
H2 SPA v. CNT Retention
Test Score
Tukey HSD .063 -
H4 RPA v. CNT Retention
Test Score
Tukey HSD .061 -
RQ6 SPA v. RPA Retention
Test Score
Tukey HSD 1.000 -
Transfer 3 Groups Transfer
Test Score
One-Way
ANOVA
.000* Large
(η
2
= .114)
H2 SPA v. CNT Transfer
Test Score
Tukey HSD .000* Large
(d = .841)
H4 RPA v. CNT Transfer
Test Score
Tukey HSD .009* Medium
(d = .574)
RQ6 SPA v. RPA Transfer
Test Score
Tukey HSD .315 -
Note: Significance was set at an alpha of .05
Summary
Chapter 4 addressed the data collected and the statistical tests performed,
including a series of one-way ANOVAs, post hoc Tukey HSD tests, and measures of
effect size that addressed the hypotheses and research questions. Data analyses
support hypotheses on mental effort and transfer. The one-way ANOVA supports
hypotheses on the retention of information, but post-hoc tests limit these findings.
POWERPOINT DESIGN FOR STATS
55
Finally, the data analyses does not support any significant differences between split
attention and redundancy principles as outlined in the research questions about mental
effort, retention, and transfer.
POWERPOINT DESIGN FOR STATS
56
CHAPTER 5
DISCUSSION
This chapter includes the following three sections: Design Summary, Findings,
Contribution to Literature, and Recommendations for Future Research. The Summary
of Findings section provides an overview of the study methodology and results. The
Conclusions section provides the findings for each of the hypotheses and research
questions as well as interpretations of the results. The Contribution to Literature
section provides an overview of the study’s impact to CLT and CTML literature. The
Recommendations for Future Research section provides considerations for further
inquiry.
Design Summary
The purpose of the study was to investigate the application of cognitive load
theory (CLT) and cognitive theory of multimedia learning (CTML) to the design of a
PowerPoint lesson for an introduction to statistics course on z-scores. The lesson was
developed using the following two learning objectives: (a) students should understand
that a z-score provides a precise description of a location in a distribution based on the
distribution’s standard deviation, and (b) students should understand and identify
simple probability from the bell curve (68%, 95%, 2.5%) based on whole-numbered z-
scores.
POWERPOINT DESIGN FOR STATS
57
Specifically, two principles of CLT and CTML (split-attention and redundancy
principles) were applied to create three PowerPoint manipulations. With the control
PowerPoint, text and visual information were separated. With the split-attention
PowerPoint, text and visual information were integrated. With the redundancy
PowerPoint, text was removed and indicators were placed around the visual
information to draw learner’s attention to specific visual areas while the narrator
spoke. Participants were measured on perceptions of mental effort and learning
performance, both retention and transfer, to determine if statistically significant
differences existed between PowerPoint conditions.
A between-subjects, single factor experimental design with a control group and
two experimental groups was used. Participants were randomly assigned to a
condition. The sample was drawn from students enrolled in an introduction to statistics
for the behavioral sciences course during the fall 2013 semester at an urban
community college located in the US southwest. Participants were recruited from nine
sections. The total number of participants used for data analyses was N = 162.
Findings
Analyses of variance were conducted to measure differences in mental effort
and learning. These tests were used to compare the mean of self-report mental effort
and the mean performance scores on a retention test and a transfer test between the
three conditions (control, split-attention, and redundancy). Tukey HSD tests were
conducted as post hoc tests to find specific differences between pairs of conditions.
Cohen’s d was also used to measure effect sizes where applicable.
POWERPOINT DESIGN FOR STATS
58
Mental Effort
The analysis of variance conducted for mental effort revealed that at least one
significant difference existed between the three treatments (p = .015). The control
group reported the highest level of mental effort whereas the split-attention and the
redundancy groups reported virtually the same level of mental effort. While both
principles reduced cognitive load, there did not appear to be a significant difference
between the two treatments. As a self-reported measure, this provides insight into the
participants’ perceptions on the PowerPoint’s ability to aid their learning process. For
a topic like statistics that has high element interactivity (Paas, 1992; Sweller, 1988),
reducing extraneous load will benefit the learner.
H1: There is a statistically significant decrease in mental effort for a group who
watched an animated PowerPoint based on the split-attention principle compared to a
control group
The split-attention principle did significantly decrease cognitive load. The
self-reported mental effort was lower for the participants who watched the split-
attention PowerPoint compared to the participants who watched the control
PowerPoint (p = .047). Additionally, a medium effect size was observed (d = .49) for
the split-attention principle.
This finding supports previous research (Chandler & Sweller, 1992; Mayer &
Moreno, 2003; Sweller, 2010) that finds the split-attention principle to decrease
cognitive load. Redesigning the PowerPoint to integrate text with visual information
may allow learners to more easily process information compared to a PowerPoint that
POWERPOINT DESIGN FOR STATS
59
separates text and visual information. The learner no longer needs to use mental effort
to match the text with the visual information and can focus on essential processing of
z-score information.
H3: There is a statistically significant decrease in mental effort between a group who
watched an animated PowerPoint based on the redundancy principle compared to a
control group
The redundancy principle did significantly decrease cognitive load. The self-
reported mental effort was significantly lower for the participants who watched the
redundancy PowerPoint compared to the participants who watched the control
PowerPoint (p = .021). Additionally, a medium effect size was observed (d = .50) for
the redundancy principle.
This finding supports previous research (Mayer & Moreno, 2003; Moreno &
Mayer, 2002) on the redundancy principle and its effect on cognitive load.
Redesigning the PowerPoint to eliminate text and only provide markers as attention
grabbers allowed learners to more easily process information. Mayer and Moreno
(2003) showed that information presented in both text and audio form is redundant and
uses both channels of the working memory (referred to as redundancy effect). In such
a learning environment, the learner cannot maximize his or her cognitive limitations.
Removing the text, then, decreases the extraneous load on the learner. Potentially, the
learners reported ease of understanding the material because the redundancy
PowerPoint relied on the vision and voice.
POWERPOINT DESIGN FOR STATS
60
RQ5: Is there a significant difference in learner’s mental effort exertion between
watching an animated PowerPoint lecture based on the split-attention principle and
watching an animated PowerPoint lecture based on the redundancy principle?
No significant difference was found in self-reported mental effort between
viewing the split-attention PowerPoint and viewing the redundancy PowerPoint (p =
.944). Not one of the principles appeared to more effectively decrease cognitive load
than the other principle. In considering the principle’s individual comparison to the
control PowerPoint, this finding suggests that both principles reduce extraneous load
equally the same.
While no difference in mental effort was found between these two principles, it
may be that they reduce cognitive load in different ways. Xie and Salvendy (2000)
note that it is difficult to measure the three loads posited by CLT (intrinsic,
extraneous, and germane). While Paas’ (1992) instrument measures overall load, Xie
and Salvendy point to the fact that this scale relies on participants’ introspections.
Even though there was an overall drop in mental effort for these two principles, there
is a possibility that the rearrangement of the three types of loads may look different as
a result of each principle.
Learning: Retention and Transfer
The retention test provided an indication of how well participants remembered
the information presented in the PowerPoint lesson on z-scores. The analysis of
variance conducted for retention revealed that at least one significant difference
existed between the three treatments (p = .035). The control group scored the lowest
POWERPOINT DESIGN FOR STATS
61
on the retention test compared to the split-attention and the redundancy groups; in
these two latter groups, retention test scores were virtually the same. While both
principles facilitated a higher performance on the retention test compared to the
control, there did not appear to be a significant difference between the two
experimental treatments.
The transfer test provided an indication of how well participants applied the
information presented in the PowerPoint. The analysis of variance conducted for
transfer revealed that at least one significant difference existed between the three
treatments (p = .001). The control group scored the lowest on the transfer test
followed by the redundancy group. The split-attention group scored the highest on the
transfer test.
H2: There is a statistically significant increase in learning scores (retention and
transfer) for a group who watched an animated PowerPoint based on the split-attention
principle compared to a control group
There was a significant increase in learning scores with the split-attention
principle. The split-attention group performed better on tests of learning compared to
the control group. This was especially true for the results of the transfer test (p =
.001). Results for the retention test approached significance at an alpha level of .05 (p
= .063). Additionally, a large effect (d = .841) was observed for the split-attention
principle on the transfer test.
The findings for the transfer test validate previous research that support the
split-attention principle’s positive effect on learning, especially transfer. Previous
POWERPOINT DESIGN FOR STATS
62
research (Chandler & Sweller, 1991; Chandler & Sweller, 1992; Moreno & Mayer,
1999) found significant differences in transfer scores between split-attention principle
material and control material. Mayer and Moreno (2002) found a median Cohen’s d
of d = .48 in their review of studies that apply the principle. The observed effect size
for the present study exceeds the median. The split-attention principle applied to the
PowerPoint may have compartmentalized for the learner several steps for
understanding the use of z-scores. Perhaps in doing this for the learner, he or she has
the opportunity to process new information and problems for more efficient transfer.
The findings for the retention test fell just short of expectations and only
approached significance, according to the post hoc Tukey HSD test. This contradicts
previous research (Mayer & Johnson, 2008) that finds the split-attention principle aids
retention of information. Two reasons may explain this study’s finding. First, the
visual representation of the z-score information by itself was effective that the
placement of the text did not matter much. The design of the PowerPoint in the visual
aspect may have been the primary source for retention. Second, a weakness of this
study may be highlighted in these results. A low reliability measure of α = .70 may
have limited the possibility for a more significant finding.
H4: There is a statistically significant increase in learning scores (retention and
transfer) between a group who watched an animated PowerPoint based on the
redundancy principle compared to a control group
The redundancy principle did significantly increase learning scores. The
redundancy group performed better on tests of learning compared to the control group.
POWERPOINT DESIGN FOR STATS
63
This was especially true for the results of the transfer test (p = .009). Results for the
retention test approached significance at an alpha level of .05 (p = .061). Additionally,
a medium effect (d = .574) was observed for the redundancy principle on the transfer
test.
The findings for the transfer test validate previous research that support the
redundancy principle’s effect on learning, especially transfer. Previous research
(Mayer & Moreno, 2003; Mayer, Moreno, Boire & Vagge, 1999) has found significant
differences in transfer scores between redundancy principle material and control
material. Mayer and Moreno (2002) found a median Cohen’s d of d = .77 in their
review of studies that have applied the principle. The observed effect size for this
study is below this median. The redundancy principle applied to the PowerPoint
streamlined verbal and visual information leading to better understanding the use of z-
scores. Perhaps in doing this for the learner, he or she has the opportunity to process
new information and problems for more efficient transfer.
The findings for the retention test fell just short of expectations given the post
hoc Tukey HSD test. This contradicts previous research (Kalyuga, Chandler &
Sweller, 2004; Mayer & Johnson, 2008; Mayer & Moreno, 2003) that finds the
redundancy principle to also aid retention of information. Again, two reasons may
explain this study’s finding. First, the visual representation of the z-score information
by itself was effective that the elimination of the text did not matter much. The design
of the PowerPoint in the visual aspect may have been the primary source for retention.
POWERPOINT DESIGN FOR STATS
64
Second, a weakness of this study may be highlighted in these results. A low reliability
measure of α = .70 may have limited the possibility for a more significant finding.
RQ6: Is there a significant difference in the learning of statistics material between an
animated PowerPoint lecture based on the split-attention principle and an animated
PowerPoint lecture based on the redundancy principle?
The results do not indicate any significant differences in learning between the
split-attention principle and the redundancy principle. This was especially true for the
results of the retention test (p = 1.00) where test score means were essentially the
same. Results for the transfer test did not indicate significance (p = .315).
The findings for the transfer test support previous findings (Mayer & Johnson,
2008) that show no difference in transfer test scores between the split-attention
principle and the redundancy principle when used on a PowerPoint presentation. In
this same research, differences were noted between both principles in retention scores
where the split-attention principle caused higher retention scores. Alternatively, the
higher median Cohen’s d of d = .77 for the redundancy principle, compared to the split
attention principle’s d = .44, suggests that redundancy principle would be more
effective. The results of this study supported neither possibility. Two reasons may
explain this study’s finding. First, the visual representation of the z-score information
was equally effective that the elimination of the text mattered little. Second, as
indicated by Mayer and Johnson (2008), as long as the learner’s attention is directed in
the lesson, the learner’s extraneous load will be minimal. Thus, it may not matter if
POWERPOINT DESIGN FOR STATS
65
short text appears next to corresponding visual information or if only a marker appears
there to draw the learner’s attention.
Contributions to Literature
The findings of this study provide strong support for the CLT and CTML
principles while leaving questions unanswered. In accordance with previous research,
the results for this study support the use of the split-attention principle and the
redundancy principle for developing PowerPoint lessons to both decrease mental
effort and increase learning outcomes. Specifically, the study provides evidence that
these principles are beneficial for material that is high in element interactivity such as
statistics.
The study compared the split-attention and redundancy principles to address
questions about effectiveness. Previous research indicates that the effect size for the
redundancy principle is larger compared to the effect size of the split-attention
principle as these relate to transfer. However, learning outcomes in retention tests
have been stronger when applying the split-attention principle in comparison to the
redundancy principle. The present study complicates these findings because it finds
no evidence to suggest a lower mental effort or higher learning outcome when using
one principle over the other. Additionally, evidence in this study supports split-
attention principle for higher transfer.
Recommendations for Future Research
Research on CLT and CTML provide principles for improving learning, and
this study aimed to address previous recommendations and criticisms of the theories.
POWERPOINT DESIGN FOR STATS
66
This study applied two principles and found that learning does increase, especially for
transfer. A PowerPoint lesson on z-scores that a student is likely to experience in an
introduction to statistics course was used for the study. In doing so, the study
addresses previous criticisms (Tabbers, Martens & van Merrienboer, 2004) about
CLT’s and CTML’s applicability to real world teaching techniques. Additionally,
participants consisted of new students in a statistics course, a subject identified by
CLT and CTML research as optimal for the use of said principles because of its high
element interactivity (Paas, 1992; Sweller, 1988). Finally, the PowerPoint software
was utilized to develop the lesson, a software program that most higher education
instructors use (Savoy, Proctor & Salvendy, 2009).
While this study examined aspects of mental effort and learning when applying
principles of CLT and CTML, additional questions remain.
1. How would note taking impact the results of these types of studies?
Participants were not allowed to take notes while watching the PowerPoint lesson for
the present study. Savoy, Proctor, and Salvendy (2009) found in their in-class study
that students rely heavily on PowerPoint text for notes. Students attend to PowerPoint
text more than to the instructor’s verbal information. To address this issue, Wecker
(2012) developed a PowerPoint presentation method whereby some slides show
information and other slides are completely black. The intent of the black slides is to
redirect students’ attentions to the instructor’s verbal information. Future research
should look at the interaction between redundancy principle and note taking in the
classroom. Potentially, redundancy principle may redirect students’ attentions from
POWERPOINT DESIGN FOR STATS
67
the text on the PowerPoint to the verbal instruction, forcing students to write the
verbal information.
2. If mental effort is reduced, why was the effect size for transfer larger than
for retention? In the present study, transfer benefited from reduced cognitive load but
retention did not at a significant level. Transfer, arguably, is more cognitively
strenuous than retention for novice learners. Reducing cognitive load frees working
memory capacity enough for transfer to benefit. It should be expected that retention
also benefit from the additional working memory space when cognitive load
diminishes. Further understanding the impact of CLT and CTML to both transfer and
retention would benefit instructors as they choose to apply these principles.
3. Could the two principles have reduced cognitive loads in different ways?
Results from Paas’ (1992) mental effort questionnaire indicate no significant
difference in mental effort for participants in the split-attention condition and the
redundancy condition. Additionally, participants in both treatments reported
significantly lower mental effort than participants in the control condition. A method
for measuring intrinsic, extraneous and germane load should be developed to help
determine the specific effect each principle has on cognitive load.
Summary
This study provides insight into the use of CLT and CTML principles on
PowerPoint lessons. Specifically, the split-attention principle and the redundancy
principle were applied to a PowerPoint lesson on z-scores for an introduction to
statistics for the behavioral sciences course. The study found that modifications to the
POWERPOINT DESIGN FOR STATS
68
instructional material using these principles significantly decreased mental effort and
increased transfer. The results also suggest these principles may tend to impact
retention. Significant findings also indicated both medium and large effect sizes.
The findings of this study are relevant to instructors of technical and
procedural material with high element interactivity, such as statistics, who use
PowerPoint as their primary instructional method. Integrating text boxes with visual
information significantly increases learning. Removing the text may also benefit the
learner. Additionally, the findings are relevant for online and distant learning
instruction. Students viewed the PowerPoint lessons for this study at individual
computer screens.
More research needs to be conducted to better understand the in-class student
dynamic with these modified PowerPoint lessons. Questions of student note-taking
and text dependency remain unanswered. Additionally, it is unclear why transfer
benefits more than retention when cognitive load is decreased.
POWERPOINT DESIGN FOR STATS
69
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77
APPENDICES
APPENDIX A
Retention Test
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78
Please write your computer #: _____________________
Retention Test
Instructions: Read and answer as many of the 12 questions below. Circle the
correct answer. You can write on this paper if you would like. You may not use
a calculator.
1. What does a z-score of 1 represent?
a. One complete standard deviation
b. One complete X above the mean
c. The mean
d. Percentages above the mean
2. A positive z-score tells you which of the following?
a. The standard deviation is of greater value than the mean
b. The standard deviation is of lower value than the mean
c. The corresponding X value is above than the mean
d. The corresponding X value is below the mean
3. Which of the following best describes a z-score’s purpose?
a. It measures distances between the beginning and the end of a set of
scores
b. It measures distances between two X scores
c. It measures distances between an X score and a mean
d. It measures distances between one standard deviation and another
standard deviation
4. What position in the distribution corresponds to a z-score of z = +2.00?
a. Above the mean by 2 points
b. Above the mean by a distance equal to 2 standard deviations
c. Below the mean by 2 points
d. Below the mean by a distance equal to 2 standard deviations
POWERPOINT DESIGN FOR STATS
79
5. Which of the following z-score values represents the location closest to the
mean?
a. z = +0.50
b. z = +1.00
c. z = -1.00
d. z = -2.00
6. A population has a standard deviation of σ = 6. What position is identified by
a z-score of z = -2.00?
a. Two points above the mean
b. Two points below the mean
c. Twelve points above the mean
d. Twelve points below the mean
7. Consider the image below. The mark labeled as “A” is best represented by
which z-score?
a. z = -1.0
b. z = -0.5
c. z = +0.5
d. z = +1.0
A
POWERPOINT DESIGN FOR STATS
80
8. Approximately what percentage of a bell curve is located between z = -1.00
and z = +1.00?
a. 34%
b. 95%
c. 68%
d. 2.5%
9. Approximately what percentage of a bell curve is located above z = +2.00?
a. 2.5%
b. 97.5%
c. 5%
d. 13.5%
10. Approximately what percentage of a bell curve is located below z = -1.00?
a. 84%
b. 16%
c. 34%
d. 68%
11. What z-score value separates the bottom 50% from the top 50%?
a. z = -2.00
b. z = -1.00
c. z = -0.50
d. z = 0.00
12. Only 16% of newborn babies weigh less than Baby Mikey. Which z-score
best represents Baby Mikey?
a. z = +2.00
b. z = +1.00
c. z = -1.00
d. z = -2.00
POWERPOINT DESIGN FOR STATS
81
APPENDIX B
Transfer Test
POWERPOINT DESIGN FOR STATS
82
Please write your computer #: _____________________
Transfer Test
Instructions: Read and answer as many of the 12 questions below. Circle the
correct answer. You can write on this paper if you would like. You may not use
a calculator.
1. For a group with a mean age of µ = 50 and a standard deviation of σ = 10, what is
the z-score corresponding to X = 65?
a. +0.25
b. +0.50
c. +0.75
d. +1.50
2. The IQ is an intelligence test. A very smart student is said to have an IQ score that
is three standard deviations above the mean. If this student’s IQ score is reported
as a z-score, what would the z-score be?
a. z = µ + 3
b. z = µ + 3σ
c. z = +3
d. z = + 3σ
3. The average weight of newborn babies is 8 pounds. Baby Jerry’s weight is
reported with a z-score of z = -2. What do we know about Baby Jerry?
a. Baby Jerry weighed 6 pounds
b. Baby Jerry weighed 8 pounds
c. Baby Jerry weighed less than 8 pound
d. Baby Jerry weighed less than 6 pounds
4. On an exam with a mean of µ = 60, you have a score of X = 52. Which standard
deviation below would give you a z-score value that is closest to the mean?
a. σ = 8
b. σ = 6
c. σ = 4
d. σ = 2
POWERPOINT DESIGN FOR STATS
83
5. A three year old, Jason, weighs 30 pounds and is told he is slightly above average.
Another three year old, Mark, weighs 25 pounds and is told he is slightly below
average. Which of the following may be true?
a. Mark has a z-score of z = 0
b. Mark has a z-score of z = -0.50
c. Jason has a z-score of z = 0
d. Jason has a z-score of z = -0.50
6. For a stats class’ final exam, George scored 2 standard deviations below the mean.
Lorena had a lower z-score than George. According to the bell curve for the stats
class (located below), what is a potential score for Lorena?
a. X = 45
b. X = 50
c. X = 55
d. X = 60
Stats Class Final Exam Scores
7. In the last 15 years, the high temperature on September 1
st
has averaged µ = 100
degrees with a standard deviation of σ = 12. Last year, the high temperature for
that date was 103 degrees. Based on this information, which of the following best
describes last year’s temperature on September 1
st
?
a. Above average
b. Abnormally above average
c. Above average, but it is impossible to describe how much more above
average
d. There is not enough information to compare last year with the average
60
65
55
POWERPOINT DESIGN FOR STATS
84
8. The SAT is a college entrance exam. Scores on the SAT form a bell curve with a
mean of µ = 500 and a standard deviation of σ = 100. If ASU only accepts
students who score in the top 50% on the SAT, what is the minimum score needed
to be accepted?
a. 600
b. 550
c. 500
d. 450
9. Max attends ASU where the average student has an IQ of µ = 100 with a standard
deviation of σ = 10. After taking an IQ test at ASU, Max is told that only 2.5% of
ASU students have a higher IQ than he does. Which of the following may be
Max’ IQ score?
a. 80
b. 85
c. 115
d. 120
10. Alex, a four-year-old child, weighs 30 pounds. At this age, boys weigh an average
of µ = 35 pounds with a standard deviation of σ = 5 pounds. Which of the
following statements is most true about Alex?
a. He is in the bottom 2.5%
b. He is in the top 2.5%
c. He weighs more than at least 10% of boys his age
d. He weighs more than at least 40% of boys his age
11. Ashley’s math test score was reported as a z-score of z = -1. Which of the
following statements is most true about Ashley?
a. Ashley did better than 95% of the class
b. Ashley did better than 50% of the class
c. Ashley did better than 34% of the class
d. Ashley did better than 16% of the class
POWERPOINT DESIGN FOR STATS
85
12. John records his commute time to work each morning for a year. He takes an
average of µ = 40 minutes to get to work with a standard deviation of σ = 5
minutes to represent his data. If we draw John’s commute times into a bell curve,
what percent of the time did John’s drive to work take between 35 minutes and 45
minutes?
a. 68%
b. 50%
c. 34%
d. 18%
POWERPOINT DESIGN FOR STATS
86
APPENDIX C
Mental Effort Questionnaire
POWERPOINT DESIGN FOR STATS
87
Please write your computer #: _____________________
Cognitive Load Mental Effort Questionnaire
Please circle one rating for each of the 3 following statements.
POWERPOINT DESIGN FOR STATS
88
APPENDIX D
Demographic Questionnaire
POWERPOINT DESIGN FOR STATS
89
Please write your computer #: _____________________
Questionnaire
Please answer the following questions. Remember, your responses are anonymous.
You may leave any questions you prefer not to answer blank.
1. I consider myself a
___ Female
___ Male
___ I decline to answer
2. How old are you? _____ _____ I decline to answer
3. What is your primary ethnic background?
___ American Indian or Alaska Native ___ Native Hawaiian or Pacific Islander
___ Asian or Asian American ___ White or Euro-American
___ Black or African American ___ Other: ________________________
___ Latino or Hispanic ___ I decline to answer
4. Have you taken a statistics course prior to this semester
___ No ___ Yes
If yes…
When did you take the course? ____________________________________
Where did you take the course? ____________________________________
For how long did you take the course? _____________________________
5. What comments do you have about this research project?
_____________________________________________________________________
_____________________________________________________________________
_____________________________________________________________________
_____________________________________________________________________
POWERPOINT DESIGN FOR STATS
90
APPENDIX E
Informed Consent Form
POWERPOINT DESIGN FOR STATS
91
POWERPOINT DESIGN FOR STATS
92
POWERPOINT DESIGN FOR STATS
93
APPENDIX F
Permission by Paas
POWERPOINT DESIGN FOR STATS
94
Subject: RE: Permission to Use Mental Effort Questionnaire
From: “Paas, Fred”
Date: Sat, June 8, 2013 12:43 AM
To: Ilder Andres Betancourt Lopez
Dear Ilder,
Your study sounds very interesting.
Yes you can use the scale, which I have attached. The only thing I
ask is to use the appropriate references if you publish your work.
Best wishes and good luck with your studies, Fred
POWERPOINT DESIGN FOR STATS
95
APPENDIX G
Institutional Review Board Approval
POWERPOINT DESIGN FOR STATS
96
POWERPOINT DESIGN FOR STATS
97
Abstract (if available)
Abstract
Statistics is a complicated subject to teach because it involves interpretational, mathematical, and logical components. Given the importance of introduction to statistics for many non‐technical students and the propensity of PowerPoint as an instructional tool, there is a need to determine whether the application of cognitive load theory and cognitive theory of multimedia learning provide effective principles for manipulating PowerPoint lessons for greater learning potential. This study evaluated the split‐attention and redundancy principles in a PowerPoint lesson on z‐scores and their potential to decrease mental effort and increase learning. Through an experimental approach, participants were recruited from an introduction to statistics for the behavioral science courses at a community college and were randomly assigned to one of three conditions (control PowerPoint, split‐attention PowerPoint, and redundancy PowerPoint). After watching the recorded PowerPoint lecture, participants self‐reported mental effort and answered retention and transfer test questions to measure learning. Analyses of variance with post‐hoc Tukey HSD tests were conducted. Findings suggest that manipulating the PowerPoint with the principles decreases mental effort and increases learning, especially for transfer.
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Betancourt Lopez, Ilder Andres
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PowerPoint design based on cognitive load theory and cognitive theory of multimedia learning for introduction to statistics
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