The Scientific Status of Learning Styles Theories

Abstract

Theories of learning styles suggest that individuals think and learn best in different ways. These are not differences of ability but rather preferences for processing certain types of information or for processing information in certain types of way. If accurate, learning styles theories could have important implications for instruction because student achievement would be a product of the interaction of instruction and the student’s style. There is reason to think that people view learning styles theories as broadly accurate, but, in fact, scientific support for these theories is lacking. We suggest that educators’ time and energy are better spent on other theories that might aid instruction.

Full text

The Generalist’s Corner
The Scientific Status of Learning
Styles Theories
Daniel T. Willingham
1
, Elizabeth M. Hughes
2
, and David G. Dobolyi
1
Abstract
Theories of learning styles suggest that individuals think and learn best in different ways. These are not differences of ability but
rather preferences for processing certain types of information or for processing information in certain types of way. If accurate,
learning styles theories could have important implications for instruction because student achievement would be a product of the
interaction of instruction and the student’s style. There is reason to think that people view learning styles theories as broadly
accurate, but, in fact, scientific support for these theories is lacking. We suggest that educators’ time and energy are better spent
on other theories that might aid instruction.
Keywords
learning styles, academic achievement, cognitive style, individual differences, teaching methods
Learning styles theories are varied, but each of these theories
holds that people learn in different ways and that learning can
be optimized for an individual by tailoring instruction to his or
her style. For example, one theory has it that some people learn
best by watching (visual learners), some by listening (auditory
learners), and some by moving (kinesthetic learners). Thus, a
first grader learning to add numbers might benefit from an
introduction that respects her learning style: the visual learner
might view sets of objects, the auditory learner might listen to
rhythms, and the kinesthetic learner might manipulate beads on
an abacus. How marvelous it would be if this theory (or a sim-
ilar theory) was true. Ideas that students had found elusive
would suddenly click, all due to a modest change in teaching
practice. But is the theory true?
Certainly, belief in learning styles theories is widespread. A
recent review (Howard-Jones, 2014) showed that over 90%of
teachers in five countries (the United Kingdom, the Nether-
lands, Turkey, Greece, and China) agreed that individuals learn
better when they receive information tailored to their preferred
learning styles. Although data on U.S. teachers are limited
(Ballone & Czerniak, 2001), our experience has been that
belief in the accuracy of such theories is widespread among the
broader public. To test this impression, we conducted a brief
survey using Amazon Mechanical Turk. Participants (N¼
313, 53.4%female, mean age ¼35.2 years) rated on a 7-
point Likert-type scale (1 ¼strongly disagree and 7 ¼strongly
agree) their agreement with this statement: ‘‘There are consis-
tent differences among people in how they learn from different
experiences: specifically, some people generally learn best by
seeing, some generally learn best by listening, and some gener-
ally learn best by doing.’’ The mean rating was 6.35 (SD ¼
1.11).
1
We observed this strong belief even though literature
reviews over the last 30 years have concluded that most evi-
dence does not support any of the learning styles theories. The
purpose of this article is to (a) clarify what learning styles the-
ories claim and distinguish them from theories of ability, (b)
summarize empirical research pertaining to learning styles, and
(c) provide suggestions for practice and implications supported
by empirical research.
What Are Learning Styles Theories?
Researchers have defined ‘‘learning styles’’ in several ways
(Messick, 1984; Peterson, Rayner, & Armstrong, 2009), but
because we are interested primarily in applications to education
(and not, e.g., in how personality dimensions impact learning),
we focus on learning styles as (a) differential preferences for
processing certain types of information or (b) for processing
information in certain ways. The former definition would
include learning styles theories that differentiate between
visual, auditory, and kinesthetic learners (Dunn, Dunn, & Price,
1984) or between visual and verbal learners (Riding & Rayner,
1998). Learning styles theories based on preferences for certain
types of cognitive processing would include distinctions
between intuitive and analytic thinkers (Allinson & Hayes,
1996) or between activist, reflecting, or pragmatic thinkers
1
Department of Psychology, University of Virginia, Charlottesville, VA, USA
2
Duquense University, Pittsburgh, PA, USA
Corresponding Author:
Daniel T. Willingham, Department of Psychology, University of Virginia, Box
400400, Charlottesville, VA 22904, USA.
Email: willingham@virginia.edu
Teaching of Psychology
2015, Vol. 42(3) 266-271
ªThe Author(s) 2015
Reprints and permission:
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DOI: 10.1177/0098628315589505
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(Honey & Mumford, 1992). Numerous theoretical distinctions
like these have been around since the 1950s (Cassidy, 2004).
Note that the definitions provided earlier distinguish learn-
ing styles from abilities. The two are often confused, but the
distinction is important. It is relatively uncontroversial that
cognitive ability is multifaceted (e.g., verbal ability and facility
with space have distinct cognitive bases), and it is uncontrover-
sial that individuals vary in these abilities. For ‘‘styles’’ to add
any value to an account of human cognition and learning, it
must mean something other than what ability means. While
styles refer to how one does things, abilities concern how well
one does them. The analogous distinction is made in sports:
Two basketball players may have equivalent ability but differ-
ent styles on the court. One may take risks, whereas the other
plays a conservative game.
Predictions and Data
Learning styles theories make two straightforward predic-
tions. First, a learning style is proposed to be a consistent attri-
bute of an individual, thus, a person’s learning style should be
constant across situations. Consequently, someone considered
an auditory learner would learn best through auditory pro-
cesses regardless of the subject matter (e.g., science, litera-
ture, or mathematics) or setting (e.g., school, sports practice,
or work). Second, cognitive function should be more effective
when it is consistent with a person’s preferred style; thus, the
visual learner should remember better (or problem-solve bet-
ter, or attend better) with visual materials than with other
materials.
Consider the first prediction. Simply enough, it means that if
you’re a visual learner today, you shouldn’t be an auditory lear-
ner tomorrow, or if you’re a visual learner on task X, you
shouldn’t be an auditory learner on task Y. This bar—consis-
tency—seems fairly low for a theoretical prediction, but most
learning styles theories have failed to vault it. Although there
are a multitude of inventories and models for assessing learning
styles, most are not reliable (Coffield, Moseley, Hall, & Eccles-
tone, 2004). And researchers are well aware of this problem. A
recent survey of 92 learning styles researchers showed that
problems of reliability were among their chief concerns with
progress in their field (Peterson et al., 2009).
Regarding the second prediction—cognitive performance—
one must draw a distinction between evidence that might sup-
port a learning styles theory and evidence that would prompt a
change in educational practice (Pashler, McDaniel, Rohrer, &
Bjork, 2009). To support the theory, one needs to observe a sta-
tistical interaction between the learning styles of individuals
and the method of instruction. For example, suppose we exam-
ined ‘‘visual learners’’ and ‘‘auditory learners.’’ Members in
each group would be randomly assigned to an instructional
condition, where material would be presented either visually
(e.g., a silent film) or auditorily (e.g., an audiotaped story). Par-
ticipants should learn better when they experience the material
in their preferred modality. Figure 1 shows a graph with a
hypothetical outcome on a test of participants’ memory for the
material.
We see the predicted effect in Figure 1: Visual learners
remember more than auditory learners when the film is shown,
and the opposite pattern appears when participants listen to the
audiotape. But everyone learns best with a visual presentation.
Practical classroom implications require a particular pattern of
data that not only supports the theory but also shows that
instruction matched to learning styles optimizes achievement
for each group. In other words, the two lines in the graph would
have to cross, indicating (in this example) that the visual lear-
ners learned best when watching the film, whereas the auditory
learners learned best when listening to the story.
Is there support for either prediction—for educational prac-
tice, or barring that, at least that the theory might be correct
(even if it’s not helpful)? No. Several reviews that span decades
have evaluated the literature on learning styles (e.g., Arter &
Jenkins, 1979; Kampwirth & Bates, 1980; Kavale & Forness,
1987; Kavale, Hirshoren, & Forness, 1998; Pashler et al.,
2009; Snider, 1992; Stahl, 1999; Tarver & Dawson, 1978), and
each has drawn the conclusion that there is no viable evidence
to support the theory. Even a recent review intended to be
friendly to theories of learning styles (Kozhevnikov, Evans,
& Kosslyn, 2014) failed to claim that this prediction of the the-
ory has empirical support. The lack of supporting evidence is
especially unsurprising in light of the unreliability of most
instruments used to identify learners’ styles (for a review, see
Coffield et al., 2004).
There is an underlying challenge to conducting research on
learning styles: It is impossible to prove that something does
not exist. However unpromising the data today, a new experi-
mental paradigm may eventually reveal that the theory was
right all along. Still, given our focus on educational application,
we set a different standard. We don’t insist that the theory be
proven definitively wrong. We are interested in classroom
practice, and before a theory is permitted to influence class-
room practice, there should be an evidence that the theory is
correct. In fact, we need more. We not only need to know that
learning styles exist but also need to know that teaching to
learning styles benefits students in some way.
Figure 1. This pattern of data would support learning styles theories
but would indicate that differences in learning styles should not be
accommodated in instruction.
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Why Do People Believe Learning
Styles Theories?
There are probably multiple reasons why people believe learn-
ing styles theories are correct, and two of these reasons strike us
as especially relevant. First, people often take things to be sci-
entific fact when they have not seen any of the evidence that
they suppose must exist. For example, most educated people
believe in the atomic theory of matter, but their knowledge
of the supporting evidence is scant. It is just something that
‘‘they’’ (i.e., scientists) have figured out. People’s belief is fur-
ther bolstered by social proof: So many other people believe the
atomic theory of matter that it would seem oddly perverse to
challenge it. Furthermore, teachers are exposed to a plethora
of materials that purportedly respect students’ learning styles,
materials that often claim a scientific basis for their design.
Once exposed to all these seemingly reliable (or at least not
overtly unreliable) sources, the confirmation bias (Nickerson,
1998) could easily support and maintain the belief. For exam-
ple, suppose a teacher was helping a student struggling with a
concept. The teacher tries a few different ways of explaining it
but to no avail. Finally, she draws a diagram, and the idea
clicks. It is natural for the teacher to conclude, ‘‘Ah, this stu-
dent must be a visual learner.’’ But perhaps any student would
have benefited from the diagram because it was an effective
way to communicate that particular idea. Or perhaps the stu-
dent needed to hear just one more explanation. Many accounts
of the sudden insight are possible, but the confirmation bias
would lead to an interpretation that supports one’s existing
beliefs.
A second possible reason for widespread belief is the confu-
sion between ability and style. As noted earlier, most research-
ers agree that ability is multifaceted and that people vary in
these abilities. From there, it is a short step to the idea that
weakness in one ability can be supplemented with strength in
another—for example, that a student having difficulty in math
might benefit from a lesson plan that played to his strength in
music. This ‘‘alternate route’’ idea certainly looks like a style.
Gardner’s (1983) theory of multiple intelligences—which is an
abilities theory—has been interpreted this way for many years
(e.g., Armstrong, 2000), although Gardner (2013) has said that
this interpretation is inaccurate. The substitution idea is inaccu-
rate, Gardner maintains, because recoding simply cannot hap-
pen, and that is part of what makes different abilities (or, in
Gardner’s theories, intelligences) different. To do math, you
have to think mathematically. To use musical cognition to
think mathematically would be like trying to use a .wmv file
in Microsoft Excel. They are simply incompatible.
We agree with Gardner, but note that it is at least theoreti-
cally possible that there may be occasional exceptions. If one
could learn material equally well in two different ways, and
if those different ways match differences in human ability, then
recoding for individual students would not only be possible but
also be effective. Indeed, there are some limited data indicating
that people who believe they are better with mental images (or
better with words) do such recoding on their own (e.g.,
Kraemer, Rosenberg, & Thompson-Schill, 2009) and that this
recoding can benefit performance (e.g., Thomas & McKay,
2010). This is not an instance of learning styles, rather, it is
an instance of ability appearing as a style.
Why All the Fuss?
So the weight of evidence fails to support learning styles. So
what? Lots of theories are poorly supported and most do not
merit an article in Teaching of Psychology. The difference here
is that the idea has seeped into popular culture, and many peo-
ple believe it, perpetuating its (ungrounded) influence in educa-
tional settings and products. Happily, it seems only rarely to
influence how students study. Less happily, learning styles the-
ories, when invoked, are most often offered as an explanation
for poor classroom performance. Most of us have had a student
protest, ‘‘Your teaching is not compatible with my learning
style,’’ with the expectation that the teacher will make individ-
ual accommodations that go beyond quality instruction.
Learning styles theories ought to be debunked, and a great
place for this to happen is in our psychology classrooms. One
could simply tackle it head on, of course, telling students about
the theory and the lack of evidence. But it strikes us as an excel-
lent opportunity to have students think through the problem
themselves. If they believe it, why do they believe it? What
does evidence look like in psychological science? What would
evidence for this particular theory look like? Could students
collect relevant evidence in the classroom? Indeed, evaluating
learning styles theories might serve as an excellent classroom
research project. Take, for example, the following two class-
room scenarios.
Class Activity Scenario 1
With the intent to explore challenges around research intended
to assess the impact of styles on learning, the teacher can mod-
erate a classroom experiment. To do this, the teacher might cre-
ate a learning activity that requires students to identify their
own best learning styles and then attempt to learn new material
(e.g., new vocabulary) via (a) their primary learning style or (b)
a different learning style. For example, visual learners and
auditory learners in the class might be presented with new
vocabulary. Students in each learning style group would be ran-
domly assigned to a learning condition, resulting in some visual
learners and auditory learners accessing the new vocabulary
visually (e.g., reading it in text) and some visual learners and
auditory learners accessing the new vocabulary auditorily
(e.g., listening to a recording). All students would be assessed
on the new vocabulary they learned, and class data would be
graphed and analyzed. Class discussions might focus on
expected results (e.g., higher performance on vocabulary
learned via a primary style), actual results, factors that may
have impacted results (e.g., preference or prior knowledge),
limitations to the research, and how the results may or may not
translate into classroom practice (see previous discussion about
Figure 1).
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Conducting this classroom experiment would take some
preplanning. Prior to starting this activity, students would need
to complete a learning styles assessment (e.g., http://
www.vark-learn.com/english/page.asp?p¼questionnaire), and
the teacher would need to prepare a learning opportunity where
information is available via each learning style (e.g., text to
read and audio of text). The teacher would also have to mini-
mize influencing factors such as prior knowledge or time spent
on learning. Replicating this activity for learning other infor-
mation (e.g., mathematics, application of theory, summary of
story, and memorization of dates and events) would allow stu-
dents to explore if learning styles are consistent across content
and, if not, why.
Class Activity Scenario 2
Another activity might explore the reliability of the assess-
ment of learning styles. For example, do external factors,
such as experiences prior to taking the assessment, influence
the outcome? If students have recently completed activities
or had experiences that positively impacted outcomes, would
they be more or less likely to select an answer based on that
experience or memory? For example, if someone recently lis-
tened to an audible Global Positioning System (GPS) to find
a location, would that person be more likely to select an
audible method of delivery for directions over using a map,
even if they consider themselves to be a visual learner?
Would a bad experience with an auditory GPS, but a good
experience reading a map, prompt a self-identified auditory
learner to select a more visual method for directions? If
recent experiences matter, does that change the reliability
of the measure? Class exploration and discussion can address
these elements.
Differences and Commonalities in
Educational Practice
The hope underlying learning styles theories is that an under-
standing of student differences will improve instruction. But
then, too, we expect that there are some aspects of the mind that
do not differ, that are common across students, and that honor-
ing these basic features will improve instruction. There is a ten-
sion in applying these two types of knowledge in the classroom.
On one hand, obsession with student individuality will lead to
paralysis: If every student is unique, how can teachers draw on
their experiences with other students to improve the instruction
of this particular student? If each student is unique, there is no
reason to think that what worked before will work now. On the
other hand, if teachers focus solely on what they believe is true
of all students, then teachers are likely to identify one set of
‘‘best practices’’ and stubbornly apply those practices to all
students.
To many, learning styles offer a middle ground—a middle
ground between treating every student the same way and treat-
ing every student uniquely. The proposed solution has been to
create categories of learners based on their unique learning
styles. Categorization means using a few, easily observed fea-
tures to infer that other features are present. For example, by
observing some perceptual features of an object—it is round,
red, and shiny—we categorize it as an apple and thus can safely
infer other nonobservable properties: It has seeds inside, it is
edible, and so on. Similarly, learning styles also categorize.
By gaining knowledge of a few properties (e.g., answers on a
questionnaire), teachers hope to infer other characteristics
(e.g., how the student will respond to different types of instruc-
tion) that can be used to improve the educational process. The
point of this article, however, is that such categorization ulti-
mately fails.
More broadly, the history of psychology shows very limited
success in finding any useful categorization scheme for stu-
dents. By far, the most successful type of categorization is one
that is already painfully obvious to educators: Differences in
prior knowledge and ability ought to be respected (Cronbach
& Snow, 1977).
Psychology has had much greater success describing com-
monalities among students than it has had in describing cate-
gorization schemes for differences. Researchers have
compiled a fairly impressive list of properties of the mind
that students share. And although going from lab to class-
room is not straightforward, there is evidence that students
benefit when educators deploy classroom methods that capi-
talize on those commonalities. For example, we know that
spacing learning over time and quizzing (among other meth-
ods) improve memory (Dunlosky, Rawson, Marsh, Nathan,
& Willingham, 2013). We know that teachers can modify the
classroom environment to decrease problem behaviors
(Osher, Bear, Sprague, & Doyle, 2010). In mathematics,
there is a particular developmental progression by which
teachers can best teach numbers and operations (National
Mathematics Advisory Panel, 2008). In reading, phonics
instruction benefits most children (Reynolds, Wheldall, &
Madelaine, 2011).
Thus, psychologists have made some impressive contribu-
tions to education. When it comes to learning styles, however,
the most we deserve is credit for effort and for persistence.
Learning styles theories have not panned out, and it is our
responsibility to ensure that students know that.
Declaration of Conflicting Interests
The authors declared no potential conflicts of interest with respect to
the research, authorship, and/or publication of this article.
Funding
The authors received no financial support for the research, authorship,
and/or publication of this article.
Note
1. Half of the subjects saw a reverse-coded version (There are not
consistent differences among people in how they learn ...). The
reverse-coded mean was 5.22 (SD ¼2.19), which was significantly
lower than the rating for the standard question, t(311) ¼5.65,
p< .001. We suspect that this difference was due to some participants
Willingham et al. 269
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failing to understand the reverse wording. In the standard version,
very few subjects (2.1%) indicated that they thought the learning
styles theory is incorrect (as noted by choosing 1 or 2 for their
response). In the reverse-code condition, 20.4%of participants
chose a rating indicating disagreement. We suspect these subjects
wanted to agree with learning styles theory but got confused by the
wording (i.e., disagreeing with a negative statement).
References
Allinson, C., & Hayes, J. (1996). The cognitive style index. Journal of
Management Studies,33, 119–135.
Armstrong, T. (2000). Multiple intelligences in the classroom (2nd ed.).
Alexandria, VA: ASCD.
Arter, J. A., & Jenkins, J. A. (1979). Differential diagnosis-
prescriptive teaching: A critical appraisal. Review of Educational
Research,49, 517–555.
Ballone, L. M., & Czerniak, C. M. (2001). Teachers’ beliefs about
accommodating students’ learning styles in science classes. Elec-
tronic Journal of Science Education,6, 1–43.
Cassidy, S. (2004). Learning styles: An overview of theories, models,
and measures. Educational Psychology,24, 419–444.
Coffield, F., Moseley, D., Hall, E., & Ecclestone, K. (2004). Should
we be using learning styles? What research has to say to practice.
London, England: Learning and Skills Research Center.
Cronbach, L. J., & Snow, R. E. (1977). Aptitudes and instructional
methods: A handbook for research on interactions. Oxford, Eng-
land: Irvington.
Dunlosky, J., Rawson, K. A., Marsh, E. J., Nathan, M. J., & Willing-
ham, D. T. (2013). Improving students’ learning and comprehen-
sion by using effective learning techniques: Promising directions
from cognitive and educational psychology. Psychological Science
in the Public Interest,14, 4–58.
Dunn, R., Dunn, K., & Price, G. E. (1984). Learning style inventory.
Lawrence, KS: Price Systems.
Gardner, H. (1983). Frames of mind: The theory of multiple intelli-
gences. New York, NY: Basic Books.
Gardner, H. (2013, October 16). Multiple intelligences are not learn-
ing styles. Retrieved from http://www.washingtonpost.com/blogs/
answer-sheet/wp/2013/10/16/howard-gardner-multiple-intelligences-
are-not-learning-styles/
Honey, P., & Mumford, A. (1992). The manual of learning styles.
Maidenhead, England: Peter Honey Publications.
Howard-Jones, P. A. (2014). Neuroscience and education: Myths and
messages. Nature Reviews Neuroscience,15, 817–824. doi:10.
1038/nrn3817
Kampwirth, T. J., & Bates, M. (1980). Modality preference and teach-
ing method: A review of research. Academic Therapy,15,
597–605.
Kavale, K. A., & Forness, S. R. (1987). Substance over style: Asses-
sing the efficacy of modality testing and teaching. Exceptional
Children,54, 228–239.
Kavale, K. A., Hirshoren, A., & Forness, S. R. (1998). Meta-analytic
validation of the Dunn and Dunn model of learning-style prefer-
ences: A critique of what was Dunn. Learning Disabilities
Research & Practice,13, 75–80.
Kozhevnikov, M., Evans, C., & Kosslyn, S. M. (2014). Cognitive style
as environmentally sensitive individual differences in cognition: A
modern synthesis and applications in education, business, and
management. Psychological Science in the Public Interest,15,
3–33.
Kraemer, D. J. M., Rosenberg, L. M., & Thompson-Schill, S. L.
(2009). The neural correlates of visual and verbal cognitive styles.
The Journal of Neuroscience,29, 3729–3798.
Messick, S. (1984). The nature of cognitive styles: Problems and
promise in educational practice. Educational Psychologist,19,
59–74.
National Mathematics Advisory Panel. (2008). Foundations for suc-
cess: The final report of the National mathematics advisory panel.
Washington, DC: U.S. Department of Education.
Nickerson, R. S. (1998). Confirmation bias: A ubiquitous phenom-
enon in many guises. Review of General Psychology,2, 175–220.
Osher, D., Bear, G. G., Sprague, J. R., & Doyle, W. (2010). How can
we improve school discipline? Educational Researcher,39, 48–58.
Pashler, H., McDaniel, M., Rohrer, D., & Bjork, R. (2009). Learning
styles concepts and evidence. Psychological Science in the Public
Interest,9, 105–119.
Peterson, E. R., Rayner, S. G., & Armstrong, S. J. (2009). Researching
the psychology of cognitive style and learning style: Is there really
a future? Learning and Individual Differences,19, 518–523.
Reynolds, M., Wheldall, K., & Madelaine, A. (2011). What recent
reviews tell us about the efficacy of reading interventions for strug-
gling readers in the early years of schooling. International Journal
of Disability, Development, and Education,58, 257–286.
Riding, R., & Rayner, S. (1998). Cognitive styles and learning strate-
gies: Understanding style differences in learning behaviour. London,
England: David Fulton Publishers Ltd.
Snider, V. E. (1992). Learning styles and learning to read: A critique.
Remedial and Special Education,54, 228–239.
Stahl, S. A. (1999). Different strokes for different folks? A critique of
learning styles. American Educator,23, 1–5.
Tarver, S., & Dawson, M. M. (1978). Modality preference and the
teaching of reading. Journal of Learning Disabilities,11, 17–29.
Thomas, P. R., & McKay, J. B. (2010). Cognitive styles and instruc-
tional design in university learning. Learning and Individual Dif-
ferences,20, 197–202.
Author Biographies
Daniel T. Willingham is a pro-
fessor of psychology at the Uni-
versity of Virginia, where he has
taught since 1992. He trained as
a cognitive psychologist and today
focuses on the application of cog-
nitive psychology to K-16 educa-
tion. He writes the ‘‘Ask the
Cognitive Scientist’’ column for
American Educator magazine and
is the author of Why Don t Stu-
dents Like School?, When Can You
Trust the Experts?, and Raising
Kids Who Read.
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Elizabeth M. Hughes is an assistant
professor of special education at
Duquesne University, in Pittsburgh,
PA. She is a former elementary
school teacher and received her doc-
toral degree from Clemson Univer-
sity. Her research focuses on
effective instructional approaches,
strategies, and assessments for stu-
dents who are low achievers or who
have disabilities in reading or mathe-
matics. Recent projects include
exploring the use of young adult lit-
erature featuring characters with disabilities to increase empathy and
content knowledge of students enrolled in teacher education pro-
grams and using video modeling to teach academic skills to adoles-
cents with autism spectrum disorder.
David G. Dobolyi is a PhD candi-
date in cognitive psychology at
the University of Virginia and a
student of Dr. Chad Dodson and
Dr. Michael Kubovy. He possesses
a background in computer pro-
gramming and software develop-
ment, and his research focuses on
using the best statistical modeling
techniques to answer a variety of
theoretical and applied questions.
Domains of interest include eye-
witness confidence, Parkinson’s
disease, and the evaluation of life
episodes through the use of ‘‘big
data.’’ His dissertation work exam-
ines the role of featural and familiarity justifications on the interpreta-
tion of eyewitness confidence and accuracy.
Willingham et al. 271
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