Article: Busting E-learning Myths
Part 1: Separating effective training from trends
From big data to burst learning, virtual reality to adaptive logic, several digital trends promise to deliver cutting-edge capabilities that can engage learners and embed knowledge like never before. On the one hand, some of these trends represent meaningful applications of modern technology that can take learning efficacy to the next level. On the other, some are not nearly as effective in application as one might expect. To separate fact from fiction in the digital age, corporate leaders must deconstruct some common e-learning myths to get at the core of what drives engagement, knowledge retention, and ultimately, return on investment.
Does the learning logic make sense? Branching versus adaptation
More and more solutions claim to offer a personalized learning experience.
Many solutions use branching, which is often mischaracterized as adaptation. While somewhat helpful, branching can’t deliver a truly personalized learning experience. In a typical branching scenario, the e-learning system conducts a pre-test or asks the user a few questions: Are you a new hire or a tenured employee? What function do you work in? Based on the response, the system sends the learner down a fixed path or “branch” of the curriculum. This pseudo personalization presumably saves time since
it spares a tenured employee, for instance, from having to wade through basic content for new hires. The problem is that once the system sends learners down a particular branch, they are locked into a fixed curriculum for a set amount of time with no way to bypass material they’ve already mastered or to lean into areas where they could use more help. The personalization in this case is not to the learner, but to the proficiency assumptions made about the selected demographic. Even though branching is better than a completely static experience with no personalization, it is still not the ideal form of logic for ensuring complete
content coverage and optimizing resource allocation and seat-time utilization.
In comparison, a fully adaptive solution is much more
respectful of the learner’s time and aptitude; therefore,
it does a better job of minimizing learner fatigue and
producing the desired educational outcomes. Just as people
learn through contextual stories and play throughout
childhood, a fully adaptive solution personalizes content
and situations both by asking about the learner’s role and by
continuously monitoring the learner’s performance. Not only
will a fully adaptive solution present role-relevant, “learnby-
doing” scenarios but it will also tailor the experience
to what the learner knows by using every interaction s/he has with the system as an input for changing what happens next in terms of the content and level of challenge. If the learner demonstrates that s/he knows how to make effective business decisions on a topic, a fully adaptive solution will move him/her on to the next subject very quickly. But, if someone demonstrates that s/he hasn’t mastered a topic, the system will provide coaching and feedback until s/he is truly proficient before moving him/her forward.
Simply put: a fully adaptive solution provides many benefits that “branching” or a partially adaptive solution cannot. True adaptation shortens the time required for training and combats learner fatigue, while ensuring the learner proves proficiency on every important topic. This returns many productive work hours back to the business while simultaneously producing greater subject-matter proficiency and driving greater behavioral change.