The Evidence of Learning

06 Jun The Evidence of Learning

To date, my philosophy of learning design and technology has relied heavily on experience and experimentation. But a foundation of evidence has always been the cornerstone of my work.

I would say that much of my career has been a pursuit of wisdom. A search for understanding by chiefly speculative means. Despite my best efforts, a research-based approach to learning design has been, at times, lacking. Not only in my own work, but in the entire field. Bold statement? Maybe. True statement? Yes.

With the help of continuing education, I have engaged in a new phase of my career. Along with it comes the opportunity to engage in the pursuit of evidence. And in evidence, there is truth.

My philosophy focuses on the need to evolve from “chiefly speculative” to quantitative observation. Workplace learning must move from a vendor-motivated environment, rife with urban myths about effective technology and approaches, to one that uses data and analysis to support the design, development and delivery of optimal learning experiences.

Evidence.

Instructional Design Models

One evidence- based approach I have observed and implemented over the course of my instructional design career is the ADDIE Model. According to Wikipedia, the ADDIE Model is the generic process traditionally used by instructional designers and training developers. The five phases—Analysis, Design, Development, Implementation, and Evaluation—represent a dynamic, flexible guideline for building effective training and performance support tools.

In my implementation of the ADDIE model with clients and instructional design teams, I have garnered the ability to be flexible and effective in my approach to the project management and execution of learning experiences. If there exists no evidence to prove our trajectory was, is or will be successful…back around the circle we go. This model calls for proof and adaptability at the same time.

And at my company TCP Learning, we even add an extra layer. We operate from the self-coined PADDIE model, adding a crucial Planning stage where we assess our client’s’ learning needs before we embark on the design project together.

Philosophers and Theorists

As a lifelong learner, I often look to the greats for guidance on my quest for wisdom. While there are many experts in the field that I may follow, there are three researchers who have truly inspired my instructional design practice. Their theories support the ability to use technology in a way that connects learning to “performance goals.”

These researchers and mentors include Richard Mayer, John Sweller and Ruth Clark.

I have been able to demonstrate the efficacy of these researchers’ theories  in my own professional practice. I have used Mayer’s Cognitive Theory of Multimedia Learning while designing and developing eLearning assets and screens. Sweller’s theory, which suggests that learning happens best under conditions that are aligned with human cognitive architecture, has served me well in the design and buildout of learning experiences. And Clark’s Cognitive Methods for Training and Performance Improvement has only served to enhance my work in the analysis of learning needs.

Vendor Driven Myths

The Debunker Club, a website designed for learning professionals who wish to correct the swarms of misinformation in the learning field, is a forum where professionals like myself can navigate the tricky waters of which research is and isn’t true in this ever-evolving industry. It’s founder, William Thalheimer, is a thought leader in the workplace learning field who often addresses the value of research-based approaches as a requirement for forward momentum in the field.

Another source that has fueled my investigation into the perpetuation of learning myths is the book, Urban Myths in Education by De Bruyckere, Kirschner, & Hulshof, The book addresses 12 different myths, including learning styles which I have personally seen being perpetuated in the workplace. The authors note “we have become saddled with a multiplicity of methods, approaches, and pseudotheories, many of which have been shown by science to be wrong or at best, only partially effective.”

Conclusion

As we come full circle, I would like to  restate my own personal philosophy:

 Workplace learning must move from a vendor-motivated environment, rife with urban myths about effective technology and approaches, to one that uses data and analysis to support the design, development and delivery of optimal learning experiences.

 I am optimistic enough to believe that future professional and academic learning endeavors will provide the kind of empirical support that is fundamental to my philosophy.