Research & Statistics

Requests

We receive numerous requests each week from those requesting permission to use VARK for their research. Unfortunately, we do not receive much feedback about the results. Please send us your results so that we can inform others. Results that are part of published papers are particularly important for us and for others.

VARK AND VALIDITY
Researchers may want infomation on the statistical validity of the VARK Questionnaire. Dr. Walter Leite from the Research and Evaluation Methodology program of University of Florida has conducted a study of VARK. The paper provides evidence of the validity of the VARK for measuring learning styles and also presents its limitations. The paper is published and the citation is:
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.

The link for the article is: http://epm.sagepub.com/cgi/content/abstract/70/2/323

The abstract reads:

The authors examined the dimensionality of the VARK learning styles inventory. The VARK measures four perceptual preferences: visual (V), aural (A), read/write (R), and kinesthetic (K). VARK questions can be viewed as testlets because respondents can select multiple items within a question. The correlations between items within testlets are a type of method effect. Four multitrait-multimethod confirmatory factor analysis models were compared to evaluate the dimensionality of the VARK. The correlated trait-correlated method model had the best fit to the VARK scores. The estimated reliability coefficients were adequate. The study found preliminary support for the validity of the VARK scores. Potential problems related to item wording and the scale's scoring algorithm were identified, and cautions with respect to using the VARK with research were raised.

From pages 18 and 19 of Dr Leite's paper, the reliability estimates for the scores of the VARK subscales were 0.85, 0.82, 0.84 and 0.77 for the Visual, Aural, Read/write and Kinesthetic subscales, respectively.

VARK STATISTICAL
Most of the data (below) is from the VARK database, January 2010. It will be updated annually. Over 750 000 respondents complete the questionnaire each year. One third of those, 250 000, leave demographic data about themselves. If you need any statistics from the database please contact us.

WHAT DOES VARK INDICATE?
Before we analyse the results from the VARK database it is necessary to examine the shape and structure of the questionnaire so that the correct statistical techniques can be used.

VARK deals with only one dimension of the complex amalgam of preferences that make up a learning style. The VARK questions and their results focus on the ways in which people like information to come to them and the ways in which they like to deliver their communication. The questions are based on situations where there are choices and decsisions about how that communication might take place.

It is important to say what VARK is not, so that other components are not perceived as being a part of it. VARK has little to say about personality, motivation, social preferences, physical environments, or intraversion-extraversion. The choice to limit VARK to modal preferences was made because that is where Neil Fleming had most success in assisting students with their learning. Of course, changing the other dimensions affected learning, but it was the modal preferences that had the most direct application for more effective learning.

THE RATIONALE FOR MULTIPLE CHOICES.
Multimodality was the expectation in the questionnaire design. The modal preferences of people are seldom singular and we live in a multimodal world. In the majority of cases people will have preferences for a number of modes and they will use strategies associated with their preferences depending on the context or situation. For example they may choose a Read/write response because the situation is biased towards it. Intuitively this makes sense, as we seldom act on the basis of input or output from only one mode. For that reason, multimodality (bi-, tri- or quad-) is likely to be the "normal" condition and single-preferences are likely to be less common. Those who have a mild, strong or very strong preference for one mode are still multimodal - it is just that one of their preferences is a little stronger than the others. For example a person with VARK scores of 6 3 3 3 is said to have a single preference for V but is, in fact, still multimodal, though not categorised as such by the VARK algorithm. Some modes, notably K, is itself an amalgam of senses and could be said to be multimodal in the broadest sense of that word.

If multimodality is the expectation in life situations, we should allow for it in the structure of the VARK questionnaire and that is why respondents can choose more than one answer to each question. But clearly if everyone chose every answer for every question then VARK would provide few insights into their strategies for learning. Allowing for multiple choices, however, reduces the discrimination of VARK. So on one hand we say that multimodality is the norm but on the other hand we are really interested in the relative strengths of particular modes within individuals. It is the ability of VARK to allow multiple choices, yet point out a person's established preferences in their profile, that is its strength.

SINGLE PREFERENCES
If the database indicated that the respondents choices were distributed evenly across all options then it is likely that the questionnaire would provide less discriminated information for its respondents - most would be VARK. The options to each question are designed so that those with a particularly strong preference will choose the response that matches their preference even when the situation in the question stem is biased towards another mode. That is how VARK discriminates and for that reason the proportion of respondents choosing each option in a question is unlikely to be close to 25% for each question. It is more likely that one or sometimes two options in each question will be very attractive to most and that only those with a strong preference will choose a different answer aligned with their modal preference.

Those who have a single-preference should continue to choose the "weakest" option despite the attraction of the dominant option (see later). So an uneven distribution across the options is expected. Table One shows this feature in the proportions (percentages) for each question taken from the January 2010 database (n=40228).

For 14 of the 16 questions there is a dominant or popular choice where more than half of the respondents have chosen it. For three questions there is one weak choice below an arbitrary 20%. Visual is the lowest choice in eight questions, A in five, R twice and K once. Conversely, Read/write and Aural are the main choices with five questions each, K for four and V for two questions.

TABLE ONE: Percentage choosing each option. Includes double counting.

Note: The table was calculated using all the choices for all respondents for each question. Many respondents chose more than one option for some questions hence the excess over 100% for the Total column.

TABLE TWO: THE VARK PREFERENCES
As in life, VARK allows for multiple approaches and strategies for learning. Most learning takes place in an environment of multiple modes and it is probably impossible to learn using one mode only. Multimodality is certainly the norm. This is similar to saying that everyone has a multimodal profile with some V, some A, some R and some K but within that profile some have a particular set of preferences. The 23 possible profiles that VARK indicates are:

TABLE THREE: VARK Database July 2010: Distribution of Preferences
n=43947

This means, for example, that there is some V in several profiles - in the three single V preferences Mild, Strong and Very Strong, and in VA, VR, VK, VAR, VAK, VRK and in VARK. Each mode is therefore represented in 10 profiles, seven of which are overlapping with other modes. Note those with a Multimodal set of preferences total 62.6%.

SO WHAT IS NORMAL?
The database samples populations of students and teachers so it is not representative of a total population. Like most databases it also contains duplicates from respondents who visit the site more than once. In the January 2010 database (n= 39407) there were 9.9% (3922) who had done the questionnaire before.
In the absence of a distinctive distribution what does it mean if Kinesthetic options are chosen more often? It could be argued that the proportions above, indicate biases towards K in our population, or, that the questionnaire measures what it measures, and that is all it does. But this is a circular argument. In questionnaires where only one option can be selected there is a balancing effect. Choosing one option precludes another so if one set of choices is popular then, by definition there will be other less popular choices. If the VARK questions and options were rewritten to balance the proportions we would be merely reflecting an hypothesis that modal preferences are balanced within our society. That is a contestable hypothesis and the statistics don't help us decide, as they are a result rather than a cause. In the January 2010 database, of the options chosen, 20.5% were for V, 24.7% were for A, 27.1% were for R and 27.7% were for K.
The content validity of VARK is the best source for resolving this argument (see above). The strength of VARK is that its questions and options are drawn from real life situations and that people identify with the results that they receive. That is VARK's strength. If a large proportion of people found the questionnaire gave them results different from their own perceptions , or the perceptions of those close to them, that would be a reason to re-examine or reject the questionnaire. The acceptance of VARK is shown in the percentage of students who say that their VARK results match what they perceive as their learning preferences. In January 2010 (n=38374) this "Match" statistic was 58.7% of our total respondents and the "No Match" was 4.6%. The remaining respondents (36.7%) chose "Don't Know" and of that total, 60% were under 25 years of age. It is not surprising that our younger respondents don't know how they learn?

If we really wanted to balance the results for V, A, R and K we should search/create a number of additional questions so that V, K and A are the dominant options more often. In our five-yearly review of the questionnaire completed in October 2006 we did not do that! As a consequence there is no distinctive distribution of VARK scores - no typical VARK profile for the general population. What we can describe is the most common final scores for each mode (V, A, R and K) which are 3, 5, 6 and 7. The graph below, for the respondents in January 2010 ,shows the proportions for the major profiles.

V, A, R and K PROPORTIONS
The database information for Table Four is from 40228 responses to the VARK questionnaire during January 2010. It uses the VARK profile descriptions (VA, VRK, mild R etc) and indicates how many people have some V, some A, some R and/or some K. This table is calculated as follows:

Each respondent's contribution sums to a single unit - 1.0.

Each respondent with a Single preference counts as 1.0.

Each respondent with two modes has each counted as 0.5.

Each respondent with three modes has each counted as 0.33 and

each respondent with four modes has each counted as 0.25.

TABLE FOUR Preferences with some proportion of V, A, R and K. January 2010.

© copyright 2001 - 2010 Neil Fleming