Article: Busting E-learning Myths
Part 2: 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.
Info trove or overload? Data versus Insight
Learning professionals expect to get data, and lots of it, from their learning management and training systems, but insight
is largely perceived to be unattainable.
Traditional training platforms produce aggregated data, such as the number of clicks on a series of questions, course
completion rates, average quiz scores, etc. However, these results are helpful only in tracking participation,
not in measuring learning effectiveness. Behavioral Insight, not data, is the secret sauce for taking learning to the next level,
and far from being unattainable, it is available now through truly adaptive learning solutions. These types of solutions have
certain hallmarks. In order to produce actionable insight, the learning solution must be able to:
Measure something meaningful, such as how learners are making decisions in a simulated business situation.
Give learners more agency to choose the best course of action and articulate why they’re choosing it.
Synthesize performance information into actionable output.
Here’s an example of how shifting from data to insight changes the game. A traditional learning solution may pose the question: should Maria accept a gift of sports memorabilia from an Olympic official?
However, a truly adaptive solution, designed around situational immersion and learning by application, is able to measure the factors underlying the learner’s decision. Having genuine insight into these nuances (i.e., the why’s and how’s) increases learning efficacy. For instance, the system might reveal that 50 percent of learners did not perceive sports memorabilia to be of value, instead they viewed it as a shared interest. It might also reveal that while learners may generally know not to accept an item of value from a government employee, they don’t technically understand that the members of non-governmental organizations, such as Olympic committees or economic advisory boards, still count as public officials.
Recognizing the patterns underlying employee behavior is essential if the organization wants to succeed in helping learners to make better decisions in critical business areas such as compliance and risk, sales training, product development, and more. Furthermore, the ability to present such insights proactively and intuitively is just as important as the ability to identify them in the first place. That’s why an effective, truly adaptive learning platform won’t dump data into a spreadsheet. It will enable users
to envision the insights, and the opportunities and challenges they represent, via interactive dashboards, visualization capabilities and other digital tools.