While discussing the shortcomings of learning styles theory with a colleague, he said he was surprised that people are still promoting them. “I thought that nonsense was over with,” he remarked. Anyone on Twitter with a serious interest in education has likely encountered some discussion about them, be it for, against, or both. That conversation brought me to examine the issue more deeply.

To that end, I tapped into my experimental psychology expertise (that last word expressed oh so loosely) to gauge how learning styles are represented on Twitter among English speakers. Does the Twitterverse largely favor them, oppose them, or represent a collision of the irresistible force and the immovable object (which one is which I will let you, the reader, decide)?

Method

Using the Google Sheets add-on Twitter Archiver, public tweets posted between June 5th and July 4th of 2019 relating to learning styles were stored in a spreadsheet. A tweet was considered relevant if it contained any of the following phrases: learning styles, learning style, visual learner, kinesthetic learner, tactile learner, or auditory learner. Direct retweets and replies were ignored.

The Twitter Archiver collects and reports all of a tweet’s information that a Twitter user can ascertain through regular use. The following information is listed as it is part this analysis: tweet text, date of tweet, number of times liked and retweeted, user name, date joined Twitter, number of followers, and user-provided biography.

After the spreadsheet was assembled, additional tweets from a single user were deleted so that a single account would have equal representation. In other words, if a user posted several times about the topic, all but one of that account’s tweets were deleted. Each tweet was read and categorized into one of three categories:

Favors Learning Styles: The following were considered tweets that promoted or supported learning styles, either explicitly or implicitly:

• Declared that learning styles are important (“We must teach to all learning styles…”)
• Linked to a learning styles website, article, blog, or inventory
• Reported their perceived learning, often to support a contention (“I never did well with lectures because I am a visual learner…”)

Opposes Learning Styles: The following were considered tweets that opposed the approach to learning styles:

• Explicitly mentions that learning styles are a myth
• Linked to a website, article, or blog that refutes learning styles

Uncategorized: These are tweets that did not fit either category above because

• They were in a language other than English
• They could not be identified easily as one or the other (“There seems to be evidence supporting both sides of the learning styles debate”)
• Were nonsensical or difficult to comprehend

Results

A total of 1885 tweets were collected and assembled. Elimination of repeat account postings decreased the number to 1495 tweets. Eliminating Uncategorized tweets yielded a sample of 1342 tweets for further analysis. There were approximately 2.5 times as many tweets favoring learning styles (n = 958) compared to those opposing them (n = 384). The results of the subsequent analyses are as follows:

Verification

There was no statistically significant difference in the percentage of verified users between those supporting learning styles (2.1%) and those opposing them (2.9%) (X² = .73, p = .39).

Followers

Accounts of those who posted a Favorable tweet had a mean following of 4406.25 (sd = 35464.92). Those posting an Opposing tweet had a mean following of 7636.38 (sd = 62306.47). Both distributions had strong positive skews as each group had a handful of accounts with over 100000 followers, thereby warranting non-parametric analysis. A Mann-Whitney U analysis revealed a significant difference (Median Favor: 418, Median Oppose: 660.50, U = 154750, p < .001).

Days on Twitter

The number of days an account has been on Twitter was calculated by subtracting the join date from the date 7/4/19 using Microsoft Excel. Those with a Favoring tweet had mean membership of 2028.18 days (sd = 1305.94) while those with an Opposing tweet had a mean membership of 2424.96 days ( sd = 1187.86). Though equal variances were not assumed, there was a statistically significant difference between the means, t(771.28) = 5.45, p < .001.

Likes and Retweets

Because the Twitter Archiver collects tweets hours after a tweet has been posted, ascertaining a tweet’s influence through liking and/or retweeting cannot be done in a reliable way. As such, no analysis was conducted with these data.

Doctoral Degree Representation

The full name of accounts were searched for inclusion of a title or letter series that would indicate doctoral level obtainment (e.g., “Dr.”. “Ed.D.”, “Ph.D.”, etc.). Within the Favor group, 16 (1.7%) had a profile indicating doctoral degree while 23 of the Oppose group (6.0%) reported the same. This difference is statistically significant, X² = 19.89, p < .001).

App

The source of a tweet was put into one of two categories. Tweets that were posted to Twitter through a mobile Twitter app or the Twitter website were labeled as “Direct”, while those that used a third-party app (e.g., Hootsuite) were labeled “3rd Party”. The percentage of those with Direct posts was significantly higher among those in the Oppose group (66.7% vs. 45%, X² = 51.32, p < .001)

Poster Biography

The biography of each poster was copied and pasted into the website wordcounter.net. The most frequent thirty words (excluding common words such as “the”, “a”, etc.) were generated along with a frequency of each.

The following are the 30 most frequently appearing words among those in the Favor group (word, count, % occurring overall):

• education 70 (2%)
• teacher 69 (2%)
• school 65 (2%)
• all 48 (2%)
• students 36 (1%)
• life 36 (1%)
• people 35 (1%)
• development 34 (1%)
• training 33 (1%)
• mom 32 (1%)
• more 31 (1%)
• student 31 (1%)
• wife 31 (1%)
• author 30 (1%)
• world 30 (1%)
• love 29 (1%)
• educator 29 (1%)
• online 27 (1%)
• coach 26 (1%)
• own 26 (1%)
• help 25 (1%)
• support 25 (1%)
• technology 24 (1%)
• through 24 (1%)
• about 23 (1%)
• business 22 (1%)
• director 22 (1%)
• teaching 21 (1%)
• college 21 (1%)
• community 21 (1%)

The following are the 30 most frequently appearing words among those in the Oppose group (word, count, % occurring overall):

• teacher 64 (4%)
• education 57 (3%)
• own 34 (2%)
• educator 30 (2%)
• teaching 28 (2%)
• views 27 (2%)
• all 25 (1%)
• school 25 (1%)
• research 24 (1%)
• university 24 (1%)
• author 23 (1%)
• student 23 (1%)
• psychology 23 (1%)
• professor 23 (1%)
• about 19 (1%)
• ed 18 (1%)
• science 17 (1%)
• consultant 17 (1%)
• teachers 15 (1%)
• development 15 (1%)
• writer 15 (1%)
• instructional 15 (1%)
• social 14 (1%)
• technology 14 (1%)
• students 13 (1%)
• tweets 13 (1%)
• digital 13 (1%)
• work 13 (1%)
• director 13 (1%)
• schools 13 (1%)

Discussion

Gee, I hate typing out a results section. Anyway…

In opposition to my colleague’s assumption, support for learning styles theory is quite strong. There were some interesting trends. First, tweets supporting learning styles were more likely than those opposing them to have been posted using a third-party app. While the reasons for using a third-party app may vary, one of their biggest draws is that multiple posts can be scheduled at one time. This may appeal to businesses and other entities that are trying to promote some sort of enterprise. A number of tweets referenced learning styles in some way to promote a variety of things, including carpets and astrology. One should not infer, however, that the majority of the Favor group is motivated by financial gain in making their post, though it is certainly reasonable to assume that some are. Likewise, there are certainly those in the Oppose group who have their own personal, financial agenda.

It was also interesting to see that those in the Oppose group were more likely to represent themselves as  being in higher education or a research-based field. They were more likely to include a doctoral designation in their name, and the author bios were more likely to include words such as psychology, science, and professor. Interpretation of these data should be taken with great caution. Anything, including false credentials, can be posted on Twitter. Likewise, being a psychological scientist, career researcher, or possessor of a doctoral degree does not guarantee good teaching; in fact, some would claim the opposite. In a similar vein, one should not assume that those in the Favor group are impervious to research findings. Differences aside, these reporting academic designation in some way represented small subgroups.

Finally, although there are fewer of them, those in the Oppose group tended to have been on Twitter longer and have more followers. The fact that this relatively informal research could not measure the number of likes and retweets of each tweet limits the inference of how influential each group is in promoting their perspective. Nevertheless, it is clear that there are different characteristics between those promoting learning styles and those who oppose them.

Limitations

It should be noted that these tweets took place mostly in the month of June, when many educators, for good reason, do not want to “talk shop” either in person or virtually. There might be different proportions in the month of August, when many teachers (particularly in the United States) are going through professional development sessions, during which they may be more inclined to voice their thoughts about the presentations being given. Some accounts, owing to their passion or interest, posted numerous times about this topic. Multiple posts are more likely to mean more exposure ideas being promoted. Limiting their presence to one post may undermine their relative influence. Future research should take multiple postings by a single user into account.

Finally, each group is not homogenous even though this report treats them as such. For example, within the Favor group, there were tweets from students/former students who expressed displeasure in a lesson/course/instructor who did not teach to their style, parents who were grateful that schools identified the style of their child, and teachers stating the importance of identifying and adapting to a student’s style. It would be interesting to compare these taxons for potential differences. Future research (I am talking to you graduate students looking for a research project that will likely get expedited IRB review) might benefit by using a more nuanced categorization scheme.

Notes

Funding

This website was funded by my credit card. Since I have to pay them back, never mind this.

Conflict-of-interests

I like research and I like bowling. My yearning to do the latter has detracted from my ability to do this post. In fact, this post would probably be better if knocking down kegels was not on my mind.

Data

The spreadsheet is available for anyone wishing to do their own analysis. The archiver is still collecting tweets, which may be of interest to anyone wishing to continue this line of inquiry. I should warn you that reading through hundreds of tweets is a tiring process!

Peer-Review

There is none as of this writing. If you have comments or corrections, you can post them below or find me on Lane 23.

Many who seek to dispel the myth of teaching to learning styles focus on summarizing contemporary studies showing a lack of its effectiveness. This is a good thing and many do it well, but I take a different approach: I critique classic studies and references to which learning style theorists look for support. By (hopefully) pointing out the cracks in the theoretical foundation, support for the practice will crumble. My first foray is the book Learning Style: Theory and Practice by James W. Keefe. This curious 1987 paperback publication, published by the National Association of Secondary School Principals (NASSP), has 42 pages of content, not counting the references, cover pages, and the like, yet has been cited, as of this writing, 634 times according to Google Scholar.

The vehicle of the book is seemingly based on the NASSP definition provided in the first chapter: “Learning styles are characteristic cognitive, affective, and physiological behaviors that serve as relatively stable indicators of how learners perceive, interact with, and respond to the learning environment”. It goes on to describe 32 different styles based on the cognitive, affective, and physiological domains. While some of these “styles” are at least somewhat conducive to the classroom environment (such as curiosity), there are others, such as degree of self-actualization (succinctly put: a state in which one has achieved their fullest potential), that do not have a parsimonious connection to how to how a teacher should give instruction. The author does admit that some styles are of lesser importance than others while some are rather abstract.

The second chapter describes learning style assessment. In some ways, it extends the first chapter by identifying the styles of importance (at least to those who subscribe to learning styles theory). These assessments vary in terms of procedure and results, with some being more of a personality assessment. One measure described is the Myers-Briggs Type Indicator (MBTI), which is known for identifying an examinee as one of 16 personality types using a four-letter code (e.g., ISTJ). Though popular in schools, workplaces, and on social media websites, the validity of the MBTI is dubious, at best. Finally, the chapter seems to push the NASSP’s own learning styles assessment, which claims to identify 23 different styles/preferences. I wanted to see its content, but a WorldCat search revealed that the nearest library having a copy is 500 miles away. Unlike the Proclaimers, I am not willing to go that distance.

The third chapter explores brain research in support (if only indirectly) of learning styles. The crux of their contention is grounded in brain hemisphere research, in which each of the two halves of the brain have certain specialities (suggesting that there are “left-brain” and “right-brain” learners). While there are certainly differences between the two hemispheres, the idea that this creates notable differences in information processing, memory, and phenomenology is simply not supported by research.

The final chapter is dedicated to the applications of learning styles. While it had the most substance being the longest chapter, it was also the most frustrating to read through. Most, if not all, of the recommendations are built on speculation. This is most observable through its suggestions for schoolwide implementation:

Remedial Approach: Identify the styles of students who struggle. Determine whether there is a trend among them, e.g., most struggling students may have the same styles that are incongruent with the school’s way of teaching.

Diagnostic Approach: Discover the learning styles of incoming students. Use for course placement, counseling, and other parts of the school process. The author cautions that this use requires special knowledge and training of learning styles. Included is a subtle plug for the NASSP Learning Style Profile Workshops and Training Seminars.

Personalization: By personally identifying the styles of students, there will need to be special advising by counselors and other trained staff to best suit the needs of learners. As the book claims: “The only solid foundation for a responsive learning environment is careful diagnosis of individual learner traits followed by flexible instruction and systematic evaluation” (p. 38).

My Overall Take

I was hoping to find solid claims based on evidence that there are styles that have been shown 1) to play a direct role in the learning process, and 2) to effect better learning when teaching is catered to them.  This book provided neither. Rather, it read as a dense literature review of personality and perceptual differences that are assumed to create taxons of learners without providing any substantive evidence. From there, it tried to support its claims through brain research, of which the supposed applications have been discredited. Finally, instead of making suggestions for future research, it makes recommendations for what schools need to do to improve, yet gives no evidence that they could actually work.

In some ways, the book is a reaction to the misguided notion of one-size-fits-all curricula and pedagogies that were part of an earlier educational Zeitgeist. We are all different, and teacher should be aware of that. Students’ backgrounds, such as their prior education and socioeconomic status, can impact their readiness to learn. Any reasonable educator would agree, but the implication that they are styles of learning to which a teacher must cater is simply unconvincing.

Whenever I encounter literature or talks about learning styles, there seems to be a general pattern to what one is expected to know and do:

1. Every student has a preferred way of learning (often, visual, auditory, etc.).
2. With this preference, they will learn best through the particular modality.
3. Everyone still needs to learn with all of their modalities, so be sure to mix up the lessons with all of the approaches.

This seems like a nice idea, but as well-meaning as it may be, I contend that it is equally misguided. To explain this in another way, I give the analogy of tastes. We have five basic tastes: sweet, sour, bitter, salty, and umami (science postulates that there may be more, but I will stick to the five here). Some prefer sweet concoctions, others like salty things, while yet others like sour foods. A sizable percentage of us also like some combination (I love chocolate, which is a combination of sweet and bitter).

In order to have the best culinary experience, I devise the following:

1. Every eater has their own taste preference.
2. With this preference, they will taste things best through that modality.
3. Everyone still needs to eat with all of their tastes, so be sure to mix up your recipes with all of the flavors.

It becomes a little more apparent that taste preference is irrelevant. People will still be able to taste blueberry pie, spaghetti with meatballs, and lemonade just fine regardless of their taste preference. Will a “salt taster“ be incapable (or less capable) of trying new cuisines because it is not rich in sodium? In fact, we could see how an emphasis on salt could ruin some dishes. Put a cup of salt into a typical chocolate chip cookie batter recipe and see if anyone (salt lovers and salt haters alike) is going to like the batch.

When it comes to learning, cognitive psychology emphasizes using the senses that are most compatible with the lesson itself. An emphasis on salt is reasonable when working with soups while more focus on sugar should be expected with many dessert items. Likewise, one learning to tie  their shoes or change a car tire would benefit from a kinesthetic approach; the learning of word pronunciation or the differentiation of pitches emphasizes listening, regardless of what one thinks they prefer.

In the end, we might believe we have a preference for learning, but it likely has little use for actual learning.

Just some food for thought.