“…people can come up with statistics to prove anything… forfty percent of people know that.”
— Homer Simpson
Perhaps one of the most relevant debates among higher education pedagogical theories involves discovering the holy grail of educational delivery methods. Many professionals refer to the meshing hypothesis as the most valid educational model. This theory states, in essence, that effective education depends on first identifying the innate learner preferences (i.e. does the learner prefer to receive auditory instruction, or is the learner more adept at acquiring knowledge through visual or kinesthetic/tactile methods?). The learner preference is then paired with a compatible delivery method so as to ensure optimal knowledge retention. Thus, according to the meshing hypothesis, the most effective method for presenting information to learners depends largely on the learners’ knowledge acquisition preferences and abilities.
Indeed, the meshing hypothesis fits nicely into a pedagogical schema that attempts to utilize a taxonomic system for creating instructional content. Unfortunately, there is little to no credible research that supports the statistical validity of the meshing hypothesis. Pashler, McDaniel, Rohrer and Bjork (2009), reported that “very few studies have even used an experimental methodology capable of testing the validity of learning styles applied to education. Moreover, of those that did use an appropriate method, several found results that flatly contradict the popular meshing hypothesis” (p. 105).
Learning-style approaches to education are enormously popular within the fields of academia and instructional design (more than 70 different learning styles have been proposed over the past several decades), yet lack all statistical and practical credibility when it comes down to effective learning. Curry (1990) further delineated the problems in the operationalization of learning style theory, emphasizing the following complications relating to the topic of learning styles:
- Confusion in definitions
- Weakness in reliability and validity of measurements
- Identification of relevant characteristics in learners and instructional settings
To many readers, graphs similar to the one below have become an almost ingrained reality in instructional design.
![graph[1].jpg](https://images.squarespace-cdn.com/content/v1/59a6ece6d2b857a0be0ccba1/1511975565357-03Z1VICC98PG46VURNSC/graph%5B1%5D.jpg)
The lack of a labeled y-axis aside, this graph seems to represent one of the great faux truths in education today. The graph itself is deceptively intuitive (e.g. research rarely conveniently falls cleanly into intervals of 10, 20, 30…). The truth is that nobody seems to be able to locate the original research from whence these values are derived. There is essentially no data to back up these numbers. This graph, and others like it, may have originated from Edgar Dale’s “Cone of Experience”, developed in 1946 (at the height of the visual education movement) and replicated in 1969. Note that Dale’s graph is void of any form of numerical values or implications of empirical support:
Dale’s Cone of Experience (Dale, 1969, p. 107)
Essentially what we as professors and instructional designers are hoping for is a statistical interaction between a learning style and an instructional method. Unfortunately, such a statistical interaction will not be found in the educational research databases, assuming the research methodology is sound. What this means in terms of instructional design and course development is that we should eschew the popular approaches of learning styles, and ground ourselves in the fundamentals of learning theories: Behaviorism, Cognitivism, and Constructivism. The American Psychological Society dedicated an entire issue of their flagship scientific publication to researching learning styles, and the conclusion is that from a research methodology standpoint it is not a sound theory.
The field of eLearning is concerned with utilizing technology to provide learning solutions to accommodate the aforementioned learning theories (see: www.learning-theories.com). Such solutions may include:
- online interactivity
- videos/observation
- simulation or scenario-based learning
- screencasts
- just-in-time tools
- mobile interfacing
- hands-on exercises
- problems solving and critical thinking
- mindmapping
- group collaborative projects
- interactive discussion boards
- game based learning
- multimedia
- etc.
An excellent TED talk explains not only the myth of learning theories and the fallacies of the meshing hypothesis, but also the dangers of categorization from learner, instructor, and pedagogical standpoints. In reality, the content of the material being taught should dictate whether content is being presented in a tactile, auditory, or visual manner - not whether or not a learner thinks that s/he has an innate personal preference for receiving instruction.
In short, it is important to not underestimate the value of readings or lecture-based delivery (whether in a classroom or virtual setting), just as instructors should not rely entirely on experiential learning or discussion groups. Although the concept of learning styles was created with the best interest of students in mind, it would appear that research does not support the claim that students learn differently one from another. In other words, an “auditory learner” can learn a great deal from a hands-on exercise, and a “visual learner” can learn from both worksheet exercises and lectures-just as well as other students. Thus, effective pedagogy should cater to learning theories and focus on providing a variety of delivery methods, as opposed to attempting to distinguish among particular learning styles.
Written by Sean Nufer PsyD, eLearning Specialist for TCS Education System.
Sources
Curry, L. (1990). One critique of the research on learning styles. Educational Leadership, 48, 50–56.
Dale, E. (1946, 1954, 1969). Audio-visual methods in teaching. New York: Dryden.
Pashler, H., McDaniel, M., Rohrer D., & Bjork, R. (2009). Learning Styles: Concepts and Evidence. Psychological Science in the Public Interest, 9, 105–119.
Rogowsky, B. A., Calhoun, B. M., & Tallal, P. (2014). Matching learning style to instructional method: Effects on comprehension. Journal of Educational Psychology, 107, 64–78.