Monday, December 17, 2012
Greetings- it has been a LONG time, but I am back with a new post. I apologize for the delay here and hope to have semi-regular posts to this blog again.
I thought I would pick up where I left off. That is, still dealing with the VARK model. Next on my list is Myers-Briggs Type Indicator, but before getting there, I have a few more papers on VARK to write about.
Today’s post is actually not specific to VARK; in fact, this paper was written in 1987 which was before VARK existed. However, the paper evaluated the evidence available at that time for VAK (the precursor to VARK), so I feel it is relevant enough to write about now.
This paper is a meta-analysis. A meta-analysis is basically an aggregation of many studies that is then analyzed to find any trends in the data. In their study, Kavale and Forness put together data from 39 studies in an attempt to find patterns and make conclusions. The authors focused on special education classes in this meta-analysis.
Across this study, three patterns of conclusions begin to emerge: 1) Current (pre-1987) methods used to sort students into visual, auditory, and kinesthetic learners do not adequately do so, 2) Many studies find no help for modality matched instruction, and 3) The studies that find benefits for modality matched instruction find very small benefits and are questionable from a research perspective. I will elaborate more on each of these points shortly.
Each study they used had a similar format. One group of students was given instruction that was matched to their preferred learning modality (either V, A, or K) and another group of students was given “regular instruction not designed to capitalize on any particular modality.”
Ok, let’s tackle each of the three above points. The first was that current (pre-1987) methods used to sort students into visual, auditory, and kinesthetic learners do not adequately do so. Kavale and Forness found that many of the studies reported a large number of cases where “a subject not selected for a modality group actually scored higher than a subject selected on the bases of a modality strength.” This number was 1 in 5 students across all modalities (V, A, and K) and was 1 in 4 students for the kinesthetic group specifically. If these students really are being sorted according to their “learning style,” the authors argue that this is a large number of improperly sorted students. The authors conclude “… although modality assessments were presumed to differentiate subjects on the bases of modality preferences, there was, in actuality, considerable overlap between preference and non-preference groups.”
Although this study was not specific to VARK, Kavale and Forness are bringing up the issue of validity of the learning styles assessment tool. One could definitely argue that VARK may not have these issues.
However, previous posts on this blog have questioned the validity of VARK as a learning style assessment tool (see VARK Part 2: More theory or VARK Learning style preferences: group comparisons)
The second point was that many studies find no help for modality matched instruction. That is, when comparing a group that received instruction specific to their preferred “learning style” to a group that just received regular instruction, there was no difference. Kavale and Forness discuss this at two levels: the whole study level and the individual subject level. At the whole study level, “The 39 studies reviewed used a variety of designs and procedures but all testing essentially the same hypothesis: matching instructional methods to individual modality preferences would enhance learning. This hypothesis was supported in 13 of the 39 studies (33%), while 67% did not offer support for the modality model.” I believe this quote speaks for itself.
At the level of the individual subjects, Kavale and Forness make the following statements:
“Hence, in two-thirds of the cases, experimental subjects exhibited no gains on standardized outcome assessments as a result of modality matched instruction.”
“Furthermore… over one third of subjects receiving instruction matched to their preferred learning modality actually scored less well than control subjects receiving no special instruction.”
Again the same pattern is found here. Modality matched instruction fails to do better than regular instruction a large portion of the time.
So, what about the studies that do find a difference for modality matched instruction? Well, as point three (above) states, the studies that find benefits for modality matched instruction find very small benefits and are questionable from a research perspective. Throughout their meta-analysis, Kavale and Forness repeatedly make statements suggesting that the gains that are seen with modality matched instruction are small. For example,
“…the gain for modality instruction translates into only a 6 percentile rank improvement. The improvement indicates that 56% of experimental subjects are better off after modality instruction, but this is only slightly above chance level (50%) and indicates conversely that 44% of experimental subjects did not reveal any gain.”
When they looked at modality matched instruction to scores on standardized tests
“…modality matched instruction produced gains of anywhere from 4 to 7 percentile ranks. These levels of improvement are only slightly about chance gains (50%) and suggest that while approximately 54% to 57% of subjects demonstrated improvement, 46% to 43% of subjects receiving this special instruction improved less than control subjects.”
When they examined modality matched instruction and reading abilities, they conclude
“… modality instruction had only modest effects on improving reading abilities. Some differences in effectiveness emerged when instructional methods were matched to modality preferences, but the positive effects were small. When modality instruction was evaluated across reading skills, 50% of the comparisons revealed effects that were not different from zero. Thus, only limited benefits appeared to accrue to reading skills when instructional practices attempted to capitalize upon particular modalities that were assumed to be the preferred instructional modes for individual subjects.”
Notice the similarities throughout these statements. Across multiple dimensions, the results are strikingly similar. They are either nonexistent (see point 2 above) or very small. Furthermore, Kavale and Forness had seven “judges” rate the studies that were used on internal validity. Basically, internal validity is a measure of the strength of the study (ie. How well were outside factors controlled?). In research, we strive for studies with high internal validity. The seven judges largely agreed on their conclusions regarding which of the studies had strong internal validity and which did not (there was a 93% inter-rater agreement). Once the studies were sorted for internal validity, were there any conclusions to be made?
YES! In fact, the studies with the lowest internal validity produced the largest differences between the modality matched instruction groups and the control (regular instruction) group. The smallest differences were found in the group of studies that had the highest levels of internal validity. Kavale and Forness conclude that “the best studies showed no positive effects for modality teaching.”
In summary, I believe Kavale and Forness say it best, so I will just use their final paragraph:
“Although the modality model has long been accepted as true, the present findings, by integrating statistically the available empirical literature, disclosed that the modality model is no effective and efforts would be better directed at improving more substantive aspects of the teaching-learning process. Both aspects of the modality model, testing and teaching, appeared problematic. No reliable assignment of subjects to preferred modality was found, as evidenced by the lack of distinction between selected groups, and no appreciable gain was found by differentiating instruction according to modality preference. Consequently, the modality concept holds little promise for special education, and the present findings provide the necessary basis for no longer endorsing the modality model, since learning appears to be really a matter of substance over style.”
Kavale, KA, Forness, SR. (1987). Substance over style: Assessing the efficacy of modality testing and teaching. Exceptional Children 54(3), 228-239.
Wednesday, April 18, 2012
An examination of the link between learning styles and course performance OR sorry all of you kinesthetic learners!
I reviewed a paper a few months ago by John Dobson. In his first paper, he examined whether differences exist in the learning styles across “sex, status, and course performance.” I had some criticisms for that paper, which you can find here, and when I came across a second paper written by Dobson, I thought it would be interesting to see what he had to say.
As with the previous paper I reviewed by this author, he is not examining the existence of learning styles. The assumption has been made that they exist. His goal is to link learning styles to class performance. In his introduction, he makes the following statement:
“…when teaching physiology to a diverse group of students, the most thorough and successful strategy is to present information using multiple learning styles.”
Notice the choice of words here. He does not say that the most successful strategy is to present information via multiple sensory modalities or in multiple ways (which there is some research to support). Instead, the wording includes the term “learning styles.” This is a pretty strong statement to make. Is there any evidence provided for this statement? Dobson cites three sources in support of this statement. Let’s examine those.
The first of the three that I could get my hands on is a paper from 2004 by Kimberly Tanner and Deborah Allen. The paper is entirely theory and provides absolutely no evidence supporting the above quote. There are a few parts of the paper that theoretically address the idea of learning styles and classroom success / teaching pedagogy, but there is no data or evidence provided in the paper. For example, Tanner and Allen state:
“From a biological perspective, the brain is the organ of learning, and as such, a learning style is likely to be a complex, emergent interaction of the neurophysiology of an individual’s brain and the unique developmental process that has shaped it through experience and interaction with the environment. Learning style, thus, is a phenotypic characteristic of an organism like any other. Given the plasticity of the human brain and its propensity to learn and likely change synaptically over time, learning styles should be considered to be flexible, not immutable- an individual’s learning style could be actively adapted, to a certain extent, to different learning environments.”
This is a theory- no evidence is provided that tie learning styles to neurophysiology. In the following paragraph, Tanner and Allen continue with “The study of human learning styles is a well-established field within the discipline of cognitive psychology.” Considering the trouble that I have had with finding evidence within the field of psychology (specifically the areas of cognitive and educational psychology), I must disagree with this statement. They go on to cite Honey and Mumford (1982), Kolb (1984), and Myers Briggs papers (Myers-Briggs, 1980). To my knowledge, these papers are very popular within educational psychology circles, but they are not talked about in most cognitive psychology textbooks nor are they in any psychology book that I could find that was specific to learning and memory (Gluck, Mercado, and Myers, 2008; Malone, 1991).
The other two sources listed are not available for free online. They appear to be largely theoretical, but if you have access to either of these articles and want to send them to me, I would greatly appreciate it (Keller, J. (1987). Development and use of the ARCS model of instructional design. J Instr Develop 10: 2-10. and Miller JA. (1998). Enhancement of achievement and attitudes through individualized learning style presentations of two allied health courses. J Allied Health 27: 150-156.)
Dobson found gender differences in learning style preference (which is different than what was found last time). Both males and females prefer visual learning the most (49% and 46% of them respectively) and kinesthetic learning the least (5% and 4% respectively), but there appear to be differences for the other two learning modalities. Females prefer aural to the read/write modality (27% to 23%) and males prefer read/write to the aural modality (29% to 17%). Although small, these differences were significant. One must question why gender differences were found in this study and not in the other study by this author that I reviewed previously (Dobson, 2010). Going to that paper, they came very close to finding a significant difference between males and females in the study. That said, their distribution of response preferences was dramatically different than in this study (with fewer “visual learners” and more “kinesthetic learners”). Why the substantial variation here? Are we talking about different populations? Both of the studies by Dobson focused on physiology students. If we are trying to classify individuals into various types of learners, yet we cannot reliably characterize the population of learners into subgroups, maybe these subgroups do not exist? The lack of reliability with characterizing the populations examined is worrisome.
Students were asked about which portion of the course they found most helpful. The vast majority of the students selected that the lecture portion of the class was aided by the lecture instructor and by the presentation materials. For the lab portion of the class, the most helpful items were the lab instructor, the lab materials, and the lab manual. The lab activities themselves were listed as most helpful by a very small minority of students. The author claims that this low number is reflective of the very small minority of students that prefer kinesthetic learning (only 4-5% of the students in this class identified this way). I have to wonder just how easily a student could differentiate the individual components of a laboratory into which were most helpful. For example, when I took labs as an undergraduate, the activity was crucial, but the lab instructor circled and helped students with various portions throughout the activity. Which portion is the most helpful? It might be difficult for students to specifically identify whether they were helped more by the activity or by their instructor.
Looking at their data, the “lecture scores for the kinesthetic group were significantly lower than those from the other three groups.” In addition, the “overall course scores from the kinesthetic group were significantly less than those from the other three groups…” The authors discuss that this indicates that kinesthetic learners are largely ignored by current teaching practices in physiology classes in college. If the author is correct, increasing the kinesthetic component of a class should lead to an increase in learning (and thus performance) with the group of “K-learners.” However, instead, all students scored better in the laboratory portion of the class. It could be argued that the kinesthetic group improved more than the other three groups, and while that is true, one must wonder whether the other three groups experienced a ceiling effect of sorts here. They are all averaging/scoring near 90% on the laboratory portion of the class. Maybe this is as high as those group averages can get? Nonetheless, the kinesthetic learners were still scoring below the other groups even when we focus on the much more kinesthetic friendly laboratory portion of the class.
I wish that the author would have provided the F statistics for their ANOVA- They claim to have found a significant interaction between learning style preferences and final scores in the lecture, lab, and overall class, but provide no statistics to back that claim. Overall, this is an interesting paper but it does little to provide us with evidence in favor of learning styles.
Dobson, J. (2009). Learning style preferences and course performance in an undergraduate physiology class. Advances in Physiological Education, 33: 308-314.
Dobson, J. (2010). A comparison between learning style preferences and sex, status, and course performance. Advances in Physiological Education, 34: 197-204.
Gluck, M, Mercado, E, Myers, C. Learning and Memory: From Brain to Behavior. 2008, Worth Publishers
Malone, JC. Theories of Learning: A Historical Approach. 1991,
Tanner, K, Allen, D. (2004). Approaches to biology teaching and learning: learning styles and the problem of instructional selection-engaging all students in science courses. Cell Biol Educ 31: 153-157.
Monday, March 26, 2012
Thus far, when I have reviewed papers in my “Take a look at the sources” series, I have focused on articles that are listed in the “Research Bibliography” portion of the VARK website. Although I have not read through all of them (or even most of them), I have been disappointed with the few that I have examined. Much of the information provided in these sources has little to nothing to do with VARK and the ties between these sources and VARK theory is unclear.
On the VARK website, there is a list of “Other Articles Specifically About VARK.” Click here for the link. I wonder if these will give me something more to work with in terms of evidence either for or against VARK theory. The following articles are listed on their website:
Leite, W. L., Svinicki, M. & Shi, Y. (2010). Attempted Validation of the Scores of the VARK: Learning Styles Inventory With Multitrait-Multimethod Confirmatory Factor Analysis Models. Educational and Psychological Measurement. 70, 323-339.
Fernandez Eugenia, The Effectiveness Of Web-Based Tutorials; Department of Computer Technology, Purdue School of Engineering and Technology, Indiana University Purdue University Indianapolis, Indiana, U.S.A..
Fleming, N.D. & Mills, C. (1992). Helping Students Understand How They Learn. The Teaching Professor, Vol. 7 No. 4, Magma Publications, Madison, Wisconsin, USA.
Fleming, N.D. & Mills, C. (1992). Not Another Inventory, Rather a Catalyst for Reflection. To Improve the Academy, 11, 137-155.
Fleming, N.D. (1995), I'm different; not dumb. Modes of presentation (VARK) in the tertiary classroom, in Zelmer, A., (Ed.) Research and Development in Higher Education, Proceedings of the 1995 Annual Conference of the Higher Education and Research Development Society of Australasia (HERDSA), HERDSA, Volume 18, pp. 308 - 313
Gardner, H., & Hatch, T. (1989). Multiple intelligences go to school: Educational implications of the theory of multiple intelligences. Educational Researcher, 18(8), 4-9.
Nooriafshar, M. and St Hill, R., (1998) Adopting The Technologies Associated With Modern Computing To Incorporate Studentsà Modal Preferences Into Course Design. Available from the authors at Faculty of Business. University of Southern Queensland, Toowoomba, Qld, 4350, Australia.
Pedersen, C. and St Hill, R (1997) Meeting the Challenge of ÎMassificationà: Taking Learner Diversity Seriously.,Available from the authors at Faculty of Business, University of Southern Queensland, Toowoomba, Qld, 4350, Australia.
St Hill, R. (1999) Some thoughts on a Whole-of-Department Approach to Teaching and Learning, Unpublished discussion paper for Department of Economics and Resources Management, University of Southern Queensland.
This seems like a decent list of “articles” to review. So, I began to look around for the above articles. I have found some rather disappointing things. First, take a close look at the list above. There are nine articles listed above. Three of them are written by Fleming or Fleming and Mills. The two papers that I reviewed before written by these authors did not provide any data, but rather theory about VARK itself. An article on theory is nice, but does not help us in our search of evidence in favor of a theory (though it should not be taken as evidence against a theory either).
The last three “articles” (Nooriafshar and St Hill, 1998; Pedersen and St Hill, 1997; St Hill, 1999) on this list are not published in any journal. Where is the scientific peer review process at work here? This is not to say that there is anything wrong with these articles, but I don’t think they would provide good evidence one way or the other with VARK. If they are not published in peer reviewed journals, their evidence would be questionable.
The second “article” listed above (by E. Fernandez) is not published either. From what I can tell, this is a website presentation that is available here:
Again, I have to point out that this is not in a scientific journal. Without a peer review process before publication, the results and theories can and should be drawn into question. This is not to say that this presentation isn’t useful or top notch. It very well might be. But if I am on a search for scientific evidence about VARK (either in favor of it or against it), this source is not very useful to me. (If you read through the presentation above, you will find that their conclusion is that there is "insufficient data to measure the impact of learning styles" anyway.)
So that leaves Howard Gardner’s multiple intelligences work cited above and a paper claiming to have validated the VARK questionnaire (Leite, Svinicki, & Shi, 2010). I am working on a review of these sources for the next few posts.
NOTE: The purpose of this post is not to discredit these “articles” or the authors of these articles. In search of evidence about VARK, I thought that a good place to look for this evidence would be with the list of articles that is provided on the VARK website. I should note that the VARK website does not claim that any of these articles provide evidence about VARK. That was something that I was hoping to find (but that I am still in search of).
Monday, March 19, 2012
A few months ago, I began reviewing some of the sources listed on the VARK bibliography. I was curious just what some of these well known and highly reputable sources had to do with VARK theory. Thus far, my conclusions have been disappointing. Four of my recent posts centered around Alan Baddeley’s memory book (Your Memory: A User’s Guide) and found nothing substantial to support VARK theory (those posts can be read through each of these links: sensory memory, visual imagery, semantic memory, workingmemory). In the post before that one, I reviewed Roger Sperry’s review of split brain work and found no relevant evidence to support VARK theories (which can be read here). So, here I go again. This time I am looking for the relevance of their Gazzaniga(1973) citation. As with the Sperry citation, it is cited internally in one of the early VARK papers (Fleming and Mills, 1992). Here is the quote:
“By questioning students, we found that many students attributed their learning difficulties to the form in which course material was presented. Some students found they had difficulties learning in situations where the course material was only presented orally, while others reported similar difficulties when the material was primarily in written form. Still other students experienced difficulty with ideas that were presented in graphics or 'without any associated concrete experiences.’ These insights prompted us to focus on sensory modality as a learning style dimension that had some preeminence over others. The notion that the way information is initially taken in by a learner influences what subsequently occurs has intuitive appeal.
“We found support for this notion in literature on neuro-linguistic programming (NLP) (Handler, 1976, 1979; McLeod, 1990; Stirling, 1987) that discussed the different perceptual modalities (aural, visual, and kinesthetic). The following questions were suggested from our exploration of this field of study, split-brain research (Gazzaniga, 1973; Sperry, 1973; Springer & Deutsch, 1985) and left brain/right brain modalities (Buzan, 1991; Edwards,1979):
1. How can students be encouraged to reflect on the nature, extent and implications of their sensory modalities?
2. As a consequence of exploring their sensory modality preference, will students modify their existing learning strategies in ways that assist their learning?”
How these questions arise from the split brain research remains to be seen. My review of Sperry’s work shed no light on that one. Perhaps the answer lies in the Gazzaniga source?
Unfortunately, I could find NOTHING in the Gazzaniga source that was worth discussing in relation to VARK. I do find these studies fascinating though, so I will share with you a few of the more interesting quotes and findings from this article. There is not much to do with VARK here, but I think it is fun nonetheless…
As Sperry’s paper was a review of mostly animal studies of split brain, Gazzaniga’s paper is a review of mostly human neuropsych work. As I discussed in the Sperry post, the prevailing theory in split brain research concerns the lateralization of language. Language and/or speech seem to be a left hemisphere task, with the contributions and abilities of the right hemisphere focusing on the spatial aspects of life (See below).
|From Gazzaniga (1973)- Notice the superiority of the left hand (right hemisphere) at drawing (a spatial task).|
In his paper, Gazzaniga describes a very interesting issue that researchers have to deal with when examining the linguistic abilities of the right hemisphere. Apparently, researchers have to look out for “cross-cuing” from one hemisphere to the other.
“We had such cross-cuing during a series of tests of whether the right hemisphere could respond verbally to simple red or green stimuli. At first, after either a red of a green light was flashed to the right hemisphere, the patient would guess the color at a chance level, as might be expected if the speech mechanism is solely represented in the left hemisphere. After a few trials, however, the score improved whenever the examiner allowed a second guess.
“We soon caught on to the strategy the patient used. If a red light was flashed and the patient by chance guessed red, he would stick with that answer. If the flashed light was red and the patient by chance guessed green, he would frown, shake his head and then say, “Oh no, I meant red.” What was happening was that the right hemisphere saw the red light and heard the left hemisphere make the guess “green.” Knowing that the answer was wrong, the right hemisphere precipitated a frown and a shake of the head, which in turn cued in the left hemisphere to the fact that the answer was wrong and that it had better correct itself! We have learned that this cross-cuing mechanism can become extremely refined. The realization that the neurological patient has various strategies at his command emphasizes how difficult it is to obtain a clear neurological description of a human being with brain damage.”
What does this have to do with VARK? Nothing at all. Fleming and Mills (1992) cites Gazzaniga (1973) and Sperry (1973) to validate their theory, but it is not clear how in fact these papers do that. How does the idea of the lateralization of language to the left hemisphere or the lateralization of spatial abilities to the right hemisphere lead to individual differences between learning styles that are sensory modality based (ie. a visual learner, auditory learner, read/writing learner, or kinesthetic learner)? Unless you are a split brained patient, the fact that these abilities (language and spatial) are separated across the hemispheres does not affect you. We are all able to process language and spatial tasks. Within us “normal” (that is, non split-brained) people, we can take items that are presented spatially and describe them linguistically (describe a picture), and we are able to take something linguistic and represent it spatially (drawing a picture to represent a written story). These studies are fascinating and I love reading them, but I fail to see how they either support or refute VARK theory.
Fleming, N.D. & Mills, C. (1992). Not Another Inventory, Rather a Catalyst for Reflection. To Improve the Academy, 11, 137-155.
Gazzaniga, M. C. (1973). The split brain in man. In R. E. Ornstein (Ed.), The nature of human consciousness: A book of readings (pp. 87-100). San Francisco: W. H. Freeman
Sperry, R. (1973). Lateral specialization of cerebral function in the surgically separated hemisphere. In F. J. McGulgan, & R. A. Schoonover, (Eds.), The psychophysiology of thinking (pp. 209-229). New York. Academic Press.
Thursday, February 23, 2012
I apologize for the long delay between my last few posts. The beginning of the semester brings sets of challenges every few months and, in addition to that, I now have a beautiful seven week old daughter at home. Finding the time to research and write these posts has gotten more difficult, as you can imagine, but look for my next posts to be up sooner rather than later.
I am taking a break from examining the sources listed on the bibliography page for VARK and instead have decided to review a paper that specifically addresses some classroom research and VARK. The paper is titled: The sensory modality used for learning affects grades.
The title of this article really caught my eye. The title alone is a fairly bold assertion. Does the study provide evidence in favor of such a claim?
So, in this study, students in physiology or research methodology classes (in the fields of medicine and sports science) were given a VARK questionnaire. Then the authors compared the average grades across the various VARK groupings and found some differences. Let’s examine what they found in more detail.
The first thing the authors did was to administer the VARK questionnaire and determine the student’s “learning style.” Students were deemed unimodal or multimodal, depending on whether they had high scores in more than one modality or not. The unimodal students were classified as a V, A, R, or a K learner. The multimodal students were also classified as a V, A, R, or a K learner based on whatever their strongest preference was. If students had two modalities tie for their strongest preference, they were excluded from the study.
The authors employed two methods of assessment in the classes: Multiple Choice questions and applied “arithmetic” questions. For the multiple choice questions, “No significant differences were detected in the outcomes of students that used different sensory modalities for learning in either unimodal or multimodal students.”
For the arithmetic questions, it gets more complicated. Here are the highlights:
“unimodal students that used the R modality for learning obtained significantly higher grades… than A and K students”
“…there were no statistically significant differences between arithmetic grades in multimodal students that used different sensory modalities for learning.”
“Multimodal A students had significantly higher scores than unimodal A students…This suggests that multimodal A students … may have used another mode better suited to solve arithmetic problems. These results support Fleming’s proposal that multimodal students are flexible and can use the mode that best suits the subject.”
“…multimodal R students had significantly lower scores than unimodal R students. …may be due to a better focus of the strength for solving problems associated with the preferred use of the R modality in unimodal students.”
Going through these, the first is fairly straight forward. The students that were classified as R learners do better at written arithmetic problems than the A and K learners. Taken at face value, this seems to be the strongest claim in this paper. However, there is one large reason to be skeptical of the author’s conclusion.
This study did not control how students with the various modalities learned. Why is that important? Well, even though a student preferred the R mode (Reading/Writing), we are unable to know that they actually used this mode more than any other mode in the class. Furthermore, the material was taught normally- that is, the instructor did not tailor the teaching of information to one modality or another. So, we can’t really conclude that the R learners did better because of their learning in the R domain. Was there more instruction targeted to the R domain or the other domains? Without controlled some of these things, this study leaves us with very little solid evidence that we can draw conclusions from.
Another interpretation of these data goes this way: Perhaps the R learners like to read more than the other types of learners and so they read more of the book and thus spent more time studying. If that is the case, the author of this paper has found that students that like to read will read more and may study more and thus get better grades. I don’t think anyone in academia would find that result to be surprising or helpful.
The other three quotes above relate to how unimodal and multimodal students compare. Fleming has suggested that multimodal students can choose which modality works best given a certain situation. In theory, this should mean that multimodal students should do better than unimodal students in each area (multimodal V vs unimodal V and so on…). Although a previous study did find this (El Tantawi, 2009), the current study did not. When comparing general groupings of unimodal and multimodal students, no differences were found. When comparing specific preferences, the multimodal A’s did better than the unimodal, which fits with Fleming’s claim, but the multimodal R’s did worse than the unimodal R’s. The author tries to explain this away as a difference in the ability to concentrate, but this finding flies directly in the face Fleming’s claim. What we are left with is the inability to accept either finding. Instead, we can say that the data from this study add little to the evidence in favor of Fleming’s claim about multimodal students choosing whichever modality works best for a given situation.
At the end of the article, Ramirez argued the following:
“…no differences in the outcome after multiple choice questions were detected between students that used different sensory modalities to obtain new information in either unimodal or multimodal students. Also, there were no differences between unimodal and multimodal students. Therefore, multiple choice questions appear not to discriminate against students with any particular sensory modality preference.”
This is an interesting claim, isn’t it? Apparently scantron exams are the way to go in all subjects including math, physics, reading, and writing. When instructors give students arithmetic problems (which were basically critical thinking problems) or if an exam focuses on problem solving without multiple choice questions, then these authors argue that the exam is biased in favor of certain students. As I stated above, a more probable interpretation of their data could be that those students that were R learners like to read, which leads them to read more, study more, and thus do better on the more difficult critical thinking portions of the class.
To finish up, the title of this article is a bit misleading, as there is no evidence presented on which sensory modality is used for learning by these students. Just because someone is an A learner does not mean that they solely use that particular modality for learning. A more appropriate title might be Student sensory modality preferences may relate to (or be predictive of) grades on arithmetic problems.
Ramirez, BU. (2011). The sensory modality used for learning affects grades. Advances in Physiology Education 35: 270-274.
El Tantawi, MMA. (2009). Factors affecting postgraduate dental students’ performance in a biostatistics and research design course. Journal of Dental Eduction 73: 614-623.
Thursday, January 19, 2012
For my final post on Baddeley’s book, Your Memory, A User’s Guide, I will be looking at his discussion of working memory and whether this can provide relevant information for VARK theory. In the past three posts, I have reviewed Baddeley’s discussion of sensory memory, his discussion of the process for the encoding of memories and his discussion of semantic memory. In general, I am still having some problems figuring out what exactly VARK theorists are citing Baddeley’s book for. In an effort to figure out the answer to this, I turn my attention to the final portion of his book where differing modalities are discussed- working memory.
Baddeley is known and discussed in upper division (usually) psychology classes for his model of working memory. Most people have heard of the idea that we have short-term memory and long-term memory. Our short-term memory would be for items that are needed over the next few seconds (or maybe minutes) and our long-term memory would be for things that we were going to store indefinitely (or at least for a long time). Baddeley (along with Graham Hitch in 1974) believed that the function of short-term memory was more than just short-term storage. He believed that its function is to serve as a processor for what we currently are remembering- a so-called “working memory.” Imagine that you study for a psychology exam for an entire month. As you learn new information, you would hopefully put it into long-term memory so that it will help you on exam day. Hopefully, most of the material that you learn will not be constantly on your mind each and every day. You might study here and there, and when you study it is on your mind, but when you are at work or at school (in your other classes), your focus is not on the material for your psychology exam. Now, when the exam comes, you need to access those stored memories so that you can use them to answer the exam questions. When you access that material, it comes into your consciousness and into “working memory.” Baddeley defined working memory as “a system that allowed several pieces of information to be held in mind at the same time and interrelated.”
To illustrate it in a slightly different way, we can think of “working memory” as in use throughout the day as we process the information that comes into our system. As we have a conversation and listen to the words that are coming out of our converser’s mouth, we must keep the words and ideas portrayed earlier in the sentences and conversation to be able to understand the words and ideas that are currently being spoken. As you are reading this sentence in this blog post, you must have the ideas from the earlier sentences from this post readily available to help you understand what you are currently reading. This is a working memory function.
In Baddeley’s model of working memory, he proposes an “articulatory loop system” and a “visuo-spatial scratch pad” (Baddeley and Hitch, 1974). A cursory glance at the names of these systems may lead one to a “visual” processor and an “auditory” processor. This may be what VARK theorists found useful with Baddeley’s work. So, what are these two systems?
Well, the articulatory loop system is the part of short-term memory that Baddeley believes helps with rehearsing something. When given a list of numbers to put into short-term memory (or even long-term memory), many people simply repeat the numbers over and over. This keeps these numbers ready for access from working memory. Baddeley’s model proposed that the artculatory loop system is “involved in some process of rehearsal, usually via sub-vocal speech, to maintain the memory trace.” The visuo-spatial scratch pad is the working memory component that you might use when you mentally rotate an object or even examine an object in your mind. For example, if I give you a picture of a room and have you stare at it for a few minutes, then I ask you to imagine the picture, you probably could. To do this, you are using your visuo-spatial scratch pad.
The existence of these systems is supported by a variety of experiments. Regarding the articulatory loop, there are many sources of evidence cited by Badelley, but I find the articulatory suppression literature most interesting. If subjects are given a list of words to remember and forced “to articulate repeatedly some irrelevant item such as the word the, suppression of their natural rehearsal mechanism reduces the number of words they can remember.” Basically, when not allowed to rehearse the information in our articulatory loop (because you were forced to repeat the word the), our memory abilities decrease.
As evidence for the visuo-spatial scratch pad, Baddeley discusses an experiment conducted by Stephen Kosselyn where subjects had to memorize a picture of a boat. “Kosselyn showed that a subject who had just responded to question about the stern of the boat took longer to respond to a question about the bow then one who had just responded to a question about the posthole. It was as if the subject were taking time to scan across the boat, and the greater the distance that had to be scanned the longer it took to respond” (Baddeley, 1984). It was as if subjects had the memory of the boat (stored as an image) and scanned it from one side to the next to be able to properly answer the question.
Our visuo-spatial scratch pad may be involved in many processes. Baddeley says that image-able words are easier to remember than those that are not image-able. This seems to tie with observations of children learning language. “… it seems easier to learn concrete concepts such as building, animal, or face than more abstract concepts such as twoness or roundness.”
Ok, now for tying this to VARK. VARK theories are based on separate processing via modalities (visual, auditory, reading, and kinesthetic). Could the articulatory loop be of service to the auditory and reading processors? Could the visuo-spatial scratch pad be of service to the visual processors? Maybe these working memory systems are a part of the reason why some people are V learners (according to VARK) and others are not. For example, one might be able to argue that if one has a better developed visuo-spatial scratch pad, they are more likely to be successful as a visual learner. Is there any evidence provided for this in Baddeley’s book?
Well, Baddeley’s own view appears to be that these systems are not executing critical thinking, but that they are simply “slave systems” of a central executive. He discusses research where one is given a task that leads to yes or no answers, but it is entirely dependent upon the visuo-spatial scratch pad. If you have the subject respond by speaking the yes or no answers, there is minimal interference between their answers and the task itself. If you have them point to the word yes or no (which may require more from the visuo-spatial scratch pad than a verbal response), there is some interference. Also, Baddeley discusses other research that relies primarily on the articulatory loop system and when asked to response by pointing to an answer (which is a spatial response), minimal interference is observed. When the same task is done with subjects being asked to vocalize a yes or no response, there is some interference observed. Thus, the articulatory loop and visuo-spatial scratch pad seem to be sub-systems of a larger “central executive.” In the majority of people, these sub-systems can work together effectively and Baddeley might argue that the individual differences might be found in the “central executive” and not in the individual working memory systems.
There is not much more to say that is too concretely tied to VARK. When discussing the visuo-spatial scratch pad, Baddeley says that the nature of the visuo-spatial scratch pad is “spatial in nature rather than visual.” For example, blind individuals have a concept of space and thus would use their visuo-spatial scratch pad for many non-visual things. This would argue against using the visuo-spatial scratch pad as a homolog for the V learners.
To finish up my Baddeley posts, I have one final comment to make. The last chapter in his book is titled “Improving your memory.” Here are the subheadings throughout: Everyday remembering, Demands on Memory, Visual Imagery Mnemonics, Verbal Mnemonics, Ritual and Oral Tradition, Memory Aids, Improving your Memory, Attention and Interest, Organization, Practice, Conclusion. Not one of these sections addresses individual differences between modality preferences and ability to learn the material.
In conclusion, I am disappointed with this particular citation from the VARK bibliography. It does not appear to provide any real support of VARK theories.
Baddeley, A. (1984). Your Memory: A User’s Guide, England: Penguin.
Baddeley AD, Hitch, GJ. (1974). Working Memory. In: The Psychology of Learning and Motivation¸Vol 8. Bower, GA (Ed). New York, Academic Press: pp. 47-90.
Tuesday, January 10, 2012
For my third post regarding the VARK citation of Alan Baddeley’s 1984 book, I will delve into semantic memory research (See my previous posts for why I am writing about Baddeley at all). Semantic memory involves storing the concepts and information that are necessary for the understanding of ideas and the meaning of whatever you are trying to remember. One of the central tenants of learning and memory that is discussed in many introductory psychology texts is that it is easier to remember the meaning of a particular word (a semantic memory) rather than the font and color in which they were presented (a so called visual memory) (Myers, 2006).
Baddeley goes through a significant discussion of semantic memory research; however, I believe the most relevant portion for my examination of the VARK sources is when Baddeley begins to probe into the nature of what a semantic memory is. He examines the role of language in semantic memories followed by a discussion of the role of visual images in semantic memories.
So, what is the nature of the semantic memory? How are concepts, ideas, and other important pieces of information that allow us to understand the world around us stored? Does the sensory modality that was present at the time of encoding play a role in the storage and retrieval of that memory?
According to Baddeley, “…semantics has been studied primarily by linguists or psycholinguists, and hence the greatest emphasis on meaning has been in relation to language.”
There are two main theories presented in the book regarding the relationship between language, semantics, and memory. One theory regarding the importance of language in meaning is the linguistic relativity hypothesis, initially proposed by Benjamin Lee Whorf. According to Baddeley, “Whorf argues that language is not simply a way of expressing your view of the world but that language itself determines this view.” One example that many are familiar with is the idea that Eskimos have many words for describing snow. As someone that lived in California for my entire life, I have two main words that come to my mind when I think of snow: white and cold. If given a piece of snow to examine, it would not be hard to imagine that an Eskimo would notice more details and probably remember them better than I would.
One interesting example that supports the Whorfian hypothesis involves comparing Korean and English speakers. When Korean speakers are discussing putting something into something else, they distinguish between loose and tight fits. English speakers do not do this. According to the linguistic relativity hypothesis, this would lead to differing perceptions at times and possibly a different way of understanding the world.
“To test whether these cross-linguistic differences are reflected in the way English and Korean speakers represent spatial relations, McDonough et al. (2000) showed scenes involving tight or loose fit to Korean and English speaking adults. After they had seen a few examples of either tight fit or loose fit, the subjects were shown an example of tight fit on one screen, and an example of loose fit on another. While Korean speaking adults looked longer at the kind of spatial relation they had just been familiarized with, English speakers did not distinguish between the tight and loose fit scenes, looking equally long at the familiar and novel scenes. Further, when given several examples of tight fit and one example of loose fit (or vice versa), Korean adults could easily pick out the odd picture, but English speakers could not.” (Boroditsky, 2003)
However, according to Boroditsky (2003), the Whorphian view has fallen out of mainstream psychological thought. The alternative view is that language may simply follow perception. Maybe the Eskimo has so many words to describe snow because of their frequent and varying perceptions of snow. Whorf believed that the Eskimo’s words led to their perceptual capabilities with snow and the alternative viewpoint is that the perceptions lead to the development of language. Eleanor Rosch’s work with the Dani tribe provides support for the alternative hypothesis. Apparently, the Dani have no words for specific colors, but instead of words for dark and light. Rosch found that the Dani could still discriminate between typical colors (red, green, blue, yellow) and atypical colors (periwinkle etc) (Rosch (1977) as cited in Baddeley(1984)). “Despite having no labels for red, green, and yellow, the Dani found them easy colours to handle, suggesting that language is based on perception, not the reverse.” (Baddeley, 1984).
Now, I admit that a discussion of linguistic relativity is a bit of a digression, but I will do my best to relate some of this to VARK in a bit. Bear with me while I move on to the discussion of visual images in semantic memories. It should be pretty obvious that various senses can play a role in semantic memories- without having words for it, I can appreciate and examine the details of various paintings (something with a visual component), music (something with an auditory component), and even food (something with a gustatory component). Think about the difference between two of your favorite painters. What do you like more about one or the other? Could you tell one apart from the other? What about two of your favorite musicians? Can you easily put the differences between the two into words? Many people say something like “I don’t know why I like it, but I just do.” Or, “I’m not sure how I know this is -insert band name here- but it just sounds like them.” Of course, if you are an artist or a musician, you probably can go into the details using words, but that would be the exception here and not the rule.
In my absolute favorite experiment from this book, Baddeley discusses Ian Moar’s mental triangulation experiment. In the experiment, Moar examined the mental maps of housewives from Glasgow and housewives from Cambridge. The result of Moar’s experiment is shown below. Notice that the Glasgow housewives exaggerate the size of Scotland, relative to England and the Cambridge housewives exaggerate the size of England relative to Scotland.
Here is what the real map looks like:
And here are what the Cambridge (left) and Glasgow housewives (right) came up with:
What is the point of this experiment? Aside from the obvious perceptual differences between the two groups, Baddeley uses the concept of mental maps as an example of something semantic that is probably not entirely represented linguistically. It is not a huge stretch to imagine that there is some visual imagery going on here.
“Is it possible then that semantic concepts are stored as images? There is no doubt that visual or spatial characteristics can be important. One might for example have a concept of all round things or red things, but it is much less easy to argue that a concept such as justice of guilt is primarily stored in terms of its visual characteristics. Of course one can come up with visual images that might in some sense represent justice, but such images would be of very little assistance in deciding whether justice had been done in a particular court judgment. The most plausible assumption is probably that concepts are stored in some abstract code which may be translated into a verbal or linguistic form or into an image when the need arises…” (Baddeley, 1984)
Ok, so how does this tie to VARK? The language aspects discussed above could link to the A or R parts of the theory and the visual imagery discussed has obvious ties to the V component. The K component appears to be entirely ignored in this discussion; some may argue that the concept of a muscle or motor memory could be the needed tie for the K component. However, motor memories are probably not the same types of memories that have been discussed here (procedural vs semantic, explicit vs implicit).
For this part of Baddeley’s book to be particularly useful for VARK theorists, there should be some mention of individual differences. According to VARK, the person who prefers a visual modality presentation of information should do better later (for recall) when this preference is catered to. The same would be true for any of the other modality preferences (according to VARK).
Does the information discussed in the semantic memory portion of Baddeley’s book provide support either for or against this? In my opinion, the answer is somewhere between against this and neither.
In one experiment that directly contrasts two presentation modalities, subjects were told that they had to categorize objects. They received the object in a picture format or in a written format with their names printed out. Subjects were equally fast at categorizing both formats (Potter and Faulconer (1975) as cited in Baddeley(1984)). In this experiment, no individual differences were discussed, so we are left not knowing whether there were subgroups that did better at one format or the other. Thus, there could have been subgroups (in this experiment) that were better at one or the other and when the data from each group was combined, the differences disappeared.
Furthermore, Baddeley cites Batlett (1968) concerning individual differences between visual imagery abilities and recall abilities. There do appear to be some individuals that are far superior in their ability to use visual imagery. However, for VARK to be supported, this would have to lead to recall differences later. Thus the “visual learner” not only needs to be better at the encoding/imaging portion, but also at the retrieval/recall portion. According to Baddeley, there is a “lack of a difference” between those that use visual imagery and those that use linguistic strategies. One must be careful when looking at this to reach strong conclusions one way or the other regarding VARK. VARK theories would propose the modality of presentation matters and this is something that is not discussed in this portion of the book. Thus, this lack of individual differences neither supports nor refutes VARK theory.
Theoretically, Baddeley supports a position that may argue against VARK proposed individual differences. He believes that the lack of differences between those that use visual imagery more and those that use linguistic methods are probably because regardless of how the information was encoded (through visual imagery or not), “since both draw on a single abstract store, the accuracy of what they recall will not differ” (Baddeley, 1984). Again though, one must be careful to reach a conclusion here. Without division into VARK subgroups, one could argue that no difference was found because the V learners were equally as able as the A and R learners.
So, my conclusions from this post are a bit mixed. There is no definitive evidence in favor or against VARK theories. Next up: Working Memory and VARK.
Baddeley, A. (1984). Your Memory: A User’s Guide, England: Penguin.
Boroditsky, L. (2003). Linguistic Relativity. In Nadel, L. (Ed.) Encyclopedia of Cognitive Science. MacMillan Press: London, UK, pages 917-921.
Myers, D. (2006). Psychology 8th ed. Worth Publishers.