Clark Quinn, Ph.D., has been involved in the design, development, and evaluation of web-based learning, effectiveness evaluation methodologies, mobile learning applications, and other educational technologies for over 30 years. Dr. Quinn earned his Ph.D. in Applied Cognitive Science at the University of California in San Diego and has conducted research at the Learning Research and Development Center at the University of Pittsburgh.
In his latest book, Millennials, Goldfish & Other Training Misconceptions, Dr. Clark examines a number of myths that affect adult learning. The myths are divided into three categories: those that research has shown are not valid, design practices that aren’t supported by evidence, and common practices that have been misconstrued. This book is meant for anyone who makes decisions about learning design and delivery. It is the author’s position that it is costly to invest time and energy into developing resources that are contrary to empirical research in the science of learning, we are wasting both resources and our learner’s time.
When considering student learning styles, there is some argument that instructors should adapt teaching methods based on those different styles. The belief in learning styles dates back to the Dunn and Dunn Learning Style Model from 1975. A quick search of Google Scholar shows about 122,000 hits when searching “Dunn and Dunn Learning Styles.” The appeal of the Dunn and Dunn approach is that catering to a student’s learning style will improve learning. The counter argument is that challenging a student to adapt to a different style will expand a student’s ability to learn.
In Learning Styles: Concepts and Evidence, by H. Pashler, M. McDaniel, D. Rohrer, and R. Bjork (2008), the authors were asked to determine if the practice of adapting teaching to fit student learning styles was supported by scientific evidence. Their conclusion was “that at present, there is no adequate evidence base to justify incorporating learning-styles assessments into general educational practice (Pashler, et. al., 2008).
In establishing the criteria for their study, Pashler, McDaniel, Rohrer and Bjork concluded that any credible evidence for learning style based instruction would require specific examples where the style of teaching improved the learner’s performance. To accomplish that in a rigorous manner, learners would have to be divided into groups that matched the learner’s preferred learning style and members of each group would have to be randomly assigned to receive one of the various learning style instruction sets. All students would then take the same final test. Finally, in order to support the idea that learners benefited from being instructed in their preferred learning style, there would have to be some correlation between test scores and learning styles.
The authors’ review of the vast amount of literature on learning styles found just one study in the European Journal of Psychological Assessment by Sternberg, Grigorenko, Ferrari, and Clinkenbeard (1999) that could be described as vaguely meeting the established criteria. However, the evidence from that study was found to be unconvincing. One reason was that only 1/3 of the learners were classified into groups, and, the desired results were found through highly derived statistical calculations only after the outliers were discarded. Other studies that used more rigorous research designs contradicted the theory that teaching to an individual’s preferred learning style enhanced performance.
This is not to say that an instructor should never take a learner’s preferred style into account. The best reason for considering adapting a presentation style consistent with a learner’s preferred style is based on the learner’s performance. If the learner is struggling with material, then it is incumbent on the instructor to simplify the material until the student can demonstrate they have mastered information. If learners are already doing well, instructors should increase the challenge.
It is easy to understand the appeal of learning styles. As instructor’s we want our learners to do well. And it is our nature to look for rationale explanations for how things work. However, as sophisticated users of information, we have to be careful to differentiate between ideas that sound reasonable and ideas that can be supported by the evidence.
About the author: Dr. H. Allen Tannenbaum received a B.S. in Education from Clarion University, a Masters in Library Science from the University of Pittsburgh, and a Doctor of Business Administration in Applied Computer Science from Northcentral University. Dr. Tannenbaum has been teaching computer related topics at Central Penn since 2002.