Getting Over Learning Styles

There is a landfill of studies—more than 3,000 articles and 600 books. If you Google “learning styles” you will get 9.7 million hits in 0.16 seconds. “Learning styles workshops” produces 7.8 million hits and even “critiques of learning styles” garners 460,000 items. By the numbers of instruments, handbooks, and workshops advertised online, learning styles must be a sizable industry. But after diving into the pile, my mind was full of grit and cynicism. A zealous quest has created claims and theories so bad they aren’t even wrong. There had to be something useful in all this effort or despair would settle over me like so much dust.

The periodic critiques of the research make the same points. 1) We don’t know what learning styles are. Researchers haven’t agreed on whether they are attributes, preferences, habits, strategies, or biological traits. We don’t know if they are cognitive, neurological, psychological, or situational. 2) The reliability and validity of the many instruments created to measure styles are regularly challenged. 3) No convincing data links learning styles to improved learning. Since the 1970s, critics have been making these points. They pretty much conclude that if you want to predict achievement for a particular learning style or match a teaching method to a learning style, you would have as much chance of success using signs of the zodiac.

But I did find some jewels buried in the landfill. Learning style ideas grew out of classroom wisdom. Given any pedagogical effort, some students learn and some do not. Every teacher encounters students who seem to learn in unexpected ways. Every student sometimes gets stumped by methods that work for everyone else. Thus 40-plus years of self-serving replications and furious critiques make abundantly clear that people learn in different ways. Neuroscientists agree that every brain is unique—more singular in structure than DNA or fingerprints.

We haven’t figured out how to deal with this diversity in learning. We decide what to do in the classroom based on crude averages or on the techniques that we like or do best, leaving many students to flounder or figure out how to learn on their own.

To paraphrase artificial intelligence pioneer Marvin Minsky, there is no such thing as a typical student because each brain contains many different kinds and combinations of resources. Neuroscience research suggests that the brain is not one general learning system but consists of many specialized modules developed over eons of evolution. While those modules vary, their network connections differ even more depending on genetics and experience. Thus every student brings to the classroom wiring, experiences, assumptions, and hidden semi-autonomous processes that we call euphemistically “prior knowledge.”

For example: Some students do well by starting with abstractions and working down to the concrete details. Others prefer to begin with examples and generalize abstractions. Some learn in brief spurts and others in extended periods. Students may do well by solving many easy problems while others thrive by struggling with a few hard ones. Success promotes learning in some students while failure works better for others. Some students learn impulsively, leaping into complex problems and flailing until they get a handle, while other take their time and reconnoiter carefully before proceeding to solutions. We aspire to teach in ways that promote learning, but any rule we set makes it easy for some and impossible for others.

Is there a way to cope with this bewildering array of learning options? Suppose we acknowledged that the most important work in the classroom is the work of learning that students do. Since the research on learning styles has failed to confirm that how we present material can improve student learning, maybe we should focus on what students do with course materials and think of our role more as managing a work team than transmitting metaphorical “content.”

Muska Mosston once differentiated teaching types by who made the learning decisions—teacher or student. He conceived a spectrum that ran from command, where instructors make all the decisions, through problem solving, where students make most decisions, to self-directed learning, where students make all decisions. Mosston’s ideas came from coaching. We often think of exemplary athletic performances as automatic, but that is an oversimplification. Repetition means predictability, and that gives advantage to your opponent. Elite players learn to adjust their performance to ongoing conditions. Athletes must become self-coaching to make quality decisions in the rapid changes of games.

One of the outcomes of students making decisions about how they will learn and what standards of performance they will strive for is customization. Students do the customization within the teachers’ framework. Teachers don’t attempt to do the impossible—predict students’ learning variations and design appropriate exercises. The teaching task becomes how to design a classroom situation that maximizes students’ opportunities to choose and to learn from the results of those choices.

Teachers then can focus on their most creative work—observing students’ actions and interceding to correct them. What do learners do with course materials? How do they tackle problems? What assumptions do they use? What do they do when they fail? Answers to those questions would most definitely improve our teaching.

A bit surprised, I ended up leaving the landfill hopeful.

Excerpted from Getting Over Learning Styles, The Teaching Professor, 25.6 (2011): 4,5.