The first post in this blog series reviewed whether there was adequate evidence in support of learning styles. “Is Appealing to Learning Styles Malpractice?” explored many voices, such as Tania Lombrozo and Jeremy Teitelbaum, who question not only the validity of learning styles, but also examine other neuroscience trends like the effectiveness of multitasking and left brain versus right brain tendencies. Even Howard Gardner has weighed in, warning that multiple intelligences should not be construed as fodder to argue the validity of learning styles. 

The overriding conclusion was that L&D professionals should listen to the current consensus, which calls for a move away from learning styles as an instructional design tool. No doubt, this will be hard for many practitioners. 

Learning styles have been on the table for many years. And although research shows that they may not be effective (or even real), research also shows that people have a natural tendency to adopt fads that appeal to our natural biases. As Thomas Gilovich states in How We Know What Isn’t So, humans are “fairly adept at finding a frame that is comforting.” 

Learning styles clearly fall into that camp, and many practitioners will find discarding them difficult. As far as ISD trends goes, learning styles are really not alone. In fact, practitioners often box themselves into one design acronym camp or another. Think: ADDIE, SAM, or LLAMA. Similarly, when a trend takes center stage—blended learning, flipped classroom, microlearning—a keen and ardent following quickly takes shape. 

So if running off photocopies of a learning style inventory is not sound practice, what is? And what about that alphabet soup of advice? DiSC, MMPI, VARK, ACT, and SAT instruments must tell us something, right? Maybe. Maybe not. 

Here’s the good news: Over decades of educational research, the pendulum of instruction always seems to swing toward some central tendency. All “knowns” known, L&D practitioners are well-served by revisiting the foundation of our field. For instance, consider Robert Gagne, whose nine events of instructional design model continue to provide a common thread for modern day developers. Other time-tested theories and practices that remain valuable and consistent with the newest research include:

• Vygotsky’s “Zone of Proximal Development,” which focuses on creating challenges, not frustration.

• Ogle’s KWL reading technique, which scaffolds learning based on prior knowledge.

• Bloom’s Taxonomy, which divides learning objectives into three primary domains: Cognitive Domain, Affective Domain, and Psychomotor Domain.

• Bruner’s constructivist theory, which contends that learning is all about building meaning—not to be interpreted as an invitation to break out the Legos. 

Instructional design pros can find solace in—and capitalize on—another foundation of learning: context. In other words, good design connects instructional content to the learners’ prior experiences and readiness (emotional and cognitive) for new material and behaviors. No matter what design “model” you use, your instruction must carefully and creatively deliberate facets of a specific pattern: 

Access Existing Personal Cognitive Structuring >> Learner Activates Current Framework to Stimulate Connections >> Receive New Information >> Rehearse New Information >> Discard Inaccurate Understanding by Accommodating Valid Information >> Adjust Schema/Build New Structure >> Apply, Practice Accordingly to Gain Mastery >> Refresh to Imprint Over Time >> Access Existing Structure…. 

It’s likely that some proponents will continue to argue that “learning styles” essentially boils down to a learner-centered versus instructor-centered philosophy—something that few can deny is important. But being learner-centered is not dependent on appealing to learning styles. Indeed, all instructional strategies from lectures, to collaborative and cooperative face-to-face experiences, to webinars with polls and surveys, to serious games and simulations, have the potential to be learner–centered, as well as effective and produce results. 

The key to success isn’t an adherence to learning styles but whether the instruction was skillfully designed. What’s more, there a myriad other variables that can impact knowledge transfer and application on the job—not the least of which is willingness to learn and change. Case in point: for some tasks, research may show that collaboration will aid knowledge retention. However, an expertly executed individual exercise will always trump a poorly design group activity. You get the idea. 

So, in the end, what do we actually know about learning, thinking, and instructional design? A growing body of research shows quite definitively how students learn and how instruction is created. Those dedicated to L&D need merely study the now and peer into the past for guidance, because the stoic pendulum, fortunately, nearly always comes to rest in the middle. 

Part 3 in this series will examine the need to focus on what can be “designed” into instruction to promote deep thinking and imprinting to aid significant learning and change over time.