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 their 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 information on the statistical validity of the VARK Questionnaire. Dr. Walter Leite from the Research and Evaluation Methodology program at the University of Florida has conducted a study of VARK. The paper provides evidence of the validity of the VARK for measuring learning preferences 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:

Validity: 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.

Reliability: They also explain that Cronbach's alpha would underestimate the reliability of the VARK scores, because Cronbach's alpha assumes that all items are parallel measures of the construct, which is not true with the VARK. Therefore, they provide estimates of reliability based on confirmatory factor analysis. The reliability estimates for the scores of the VARK subscales were .85, .82, .84, and .77 for the visual, aural, read/write, and kinesthetic subscales, respectively, which are considered adequate given that the VARK is not used for high-stakes decisions.

VARK STATISTICAL
Most of the data (below) is from the VARK database, October to December 2011. NOTE: Where a statistic refers to a question, please use the downloadable VARK Questionnaire from the website. The questions and their options are randomized when presented online on the VARK website so numbers on your sequence may not correspond with items below. These statistics are normally updated annually. Over one million respondents complete the questionnaire each year. One third of those, leave demographic data about themselves. If you need any statistics from the database for your research please contact us.

WHAT DOES VARK INDICATE?
Before we analyze 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 person's 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 decisions 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 affects 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 Visual but is, in fact, still multimodal, though not categorized as such by the VARK algorithm. Some modes, notably Kinesthetic, is itself, an amalgam of senses and could be said to be multimodal in the broadest sense of that word. For VARK usage it has a specific definition that should be understood if you plan to use VARK.

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 preferences in their profile, that is its strength.

SINGLE PREFERENCES
If the database indicated that respondents' choices were distributed evenly across all options then it is likely that the questionnaire would provide less discriminatory information for its respondents - most would be all-four - 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 may continue to choose the weakest options 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 September-December 2012 database (n=145538).

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. For 13 of the 16 questions there is at least one mode with more than half the respondents. On 16 occasions that 50% mark is equalled or exceeded. For two questions (Q2 and Q14)there is one weak choice (V) just below an arbitrary 20% (17%,and 19%). Visual and Aural are the lowest choices in seven questions each and Read/write in two. Conversely, Aural and Kinesthetic have four questions where they are the most popular, Read/write has six and Visual has two questions where it leads the others.

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

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 or teach 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 their profile some may have preferences for modes that are stronger than others. There are a number of ways to assemble the VARK preferences. The usual method is to distinguish 23 profiles as shown below.

Recently we have been subdividing those in the all-four VARK profile (above) into three segments. Those in Type One tend to use their preferences separately. They examine the situation and choose the preference that suits that situation. They could be described as "context specific." Others need to use all their preferences to get an understanding that suits their learning needs. It could be said that they are "context blind". Although they take longer to "understand" something new, their understanding is deeper and they have wider perspectives. The graph below shows the proportions who are in Type One and Type Two and a smaller group who lie in the transition area between the two. Note that this distinction between Type One and Type Two would also exist in the Bimodal and the Trimodal profiles but, for clarity, we have not added them into this graph. using this categorization would mean there are 26 different profiles generated by the VARK algorithm.

TABLE THREE: VARK Database September-December 2012: Distribution of Preferences
n=145358

This means, for example, that there is some Visual in several profiles - it is in the three single Visual 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 overall, total 61.6%.

SO WHAT IS NORMAL?
The database samples populations largely dominated by those in education (93%) so it is not representative of a total population.
In the absence of a distinctive distribution, what does it mean if, say, Read/write options are chosen more often? It could be argued that the proportions above, indicate biases towards those with a Read/write preference 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, 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. The hypothetical distribution of the 6560 possible and valid sets of four scores (where at least 9 options have been chosen) is shown in the graph below.

The VARK statistics don't help us decide, as they are a result rather than a cause. In the October to December 2011 database, of the options chosen, 20.7% were for Visual, 24.9% were for Aural, 26.9% were for Read/write and 27.5% were for Kinesthetic.
The content validity of VARK is the best source for resolving the argument about what is normal (see above). The strength of VARK is that its questions and options are drawn from real life learning situations and that people identify with the results that they receive. That is VARK's strength. If a large proportion of people found that 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 strength of VARK is shown by the increasing number of respondents who use it and who comment on its usefulness and the percentage of respondents who indicate that their VARK results match what they perceive as their learning preferences. In September to December 2011 (n=138000) this "Match" statistic was 57.3% of respondents who answered that question and the "No Match" was 6.3%. The remaining respondents (36.4%) chose "Don't Know" and of that group, 69% 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 for, or createm a number of additional questions so that V, K and A are the dominant options more often! In our five-yearly reviews of the questionnaire (last completed in October 2011) 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 that the average rounded scores for each mode (V, A, R and K) are 6, 7, 7 and 8. The graph below, for the respondents in October to December 2011, shows the proportions for the major profiles.

REDUCING THE COMPLEXITY
It may be useful to identify the dimensions of VARK reduced to only four modes. This can be done in two ways shown in the graph that follows and in Table Four below. For the graph, we have collected all those who have some Visual preference, all those with some Aural preference, some Read/write preference and some Kinesthetic preference. For each of these we have shown those who have a single preference and in the next sections of the bars those who have some of each preference in a bimodal profile and finally all those who have some of that preference in a trimodal profile. Those who have some of each preference in a four-part VARK profile have been omitted as that would only add equal weight to each of the bars.

To interpret the graph, for the 62094 respondents in October-December 2011 we can say that 34% of those respondents had Kinesthetic as part of the description of their profiles i.e. they either had a Kinesthetic single preference from the VARK algorithm or Kinesthetic was part of their bimodal or trimodal profiles viz. AK, RK, VK, VAK, ARK or VRK.

V, A, R and K PROPORTIONS
The database information for Table Four is from the same 62094 responses to the VARK questionnaire during October-December 2011. It uses the VARK profile descriptions (VA, VRK, mild R etc) as above and indicates how many people have some V, some A, some R and/or some K. Unlike the graph above it makes an assumption that preferences are weaker when combined. The 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.

Using these rules, the table below is formed.

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

TABLE FIVE: Groups and the percentage of V, A, R and K Options Chosen. May 2013.

This table is compiled differently from Table Four. Here we have the percentages for the total number of options chosen for various populations. For example, Females, numbering 27601 chose 20.5% of their options from the Visual choices, 24.5% from the Aural choices etc.

TABLES SIX, SEVEN and EIGHT: THE MATCH AND NO MATCH STATISTICS
In the tables below are the statistics for a question asked of all respondents after they have completed the questionnaire and seen their results. They are asked if the results match their perception of how they learn. They have three choices: "Match", "No Match" and "Don't Know." The "Match" statistic is currently 59.1% and the "No Match" statistic is 5.7% so a further 35.3% are in the "Don't Know" category. We use this statistic as a regular check on whether VARK is offering a useful service. If a larger proportion chose "No Match" we would be concerned. Some of the 23470 respondents (January-April 2013) who claimed that they did not know how they learned are shown in the tables below with the highest group first.

"Don't Know" Statistics

VARK Category	Percent of Don't Know Database Total	Percent of Total Database
VARK (All modes)	40%	37.6%
A Mild	5.7%	4.3%
R Mild	9.3%	8.7%
ARK	7.4%	6.2%
AK	4.1%	3.9%
AR	3.4%	2.9%
RK	3.8%	3.5%

Of the Don't Know group almost 60% (59.4%) were aged under 25.

Age	Percent of Don't Know Database
Under 18	21.0%
19 - 25	38.4%
26 - 34	18.0%
35 - 44	11.4%
45 - 54	7.9%
Over 54	3.3%

Sixty percent (60%) were females which is similar to the whole database percentage.

"No Match" Statistics
A total of 3759 respondents chose this category, making up 5.7% of those who answered that question. They were mostly in these VARK Profiles.

VARK Category	Percent of No Match Database	Percent of Total Database
VARK (All modes)	33%	37.6%
R Mild	12.1%	8.7%
A Mild	7.4%	4.3%
ARK	8.0%	6.2%
K Mild	6.8%	6.8%

THE DISTRIBUTION OF V, A, R AND K SCORES
The VARK website algorithm calculates each respondent's profile based on their V, A, R and K scores from the questionnaire. The scores for each individual and mode vary from zero (0) to 16. The frequency of each V, A, R and K score for all respondents in September-December 2011 (n=145358) is shown in the graphs below.

© copyright 2001 - 2011 Neil Fleming