From our readers:

How can instructional designers choose the best delivery method that guides the learner's self-regulation and also results in high-impact performance change?

Instructional designers have a myriad of delivery modalities to choose from when creating a learning module. In general, the more nuanced and open-ended the desired performance, the more you would want to take advantage of a live, responsive facilitator. The more your outcomes will depend on practice, individualized feedback, adaptive sequencing, and specific observable behaviors, the more benefit you will gain from instructionally interactive e-learning.

In truth, a number of these decisions are dictated by the learning environment and available resources rather than the nature of the learning. Instructor-led training is becoming more of a luxury each day as companies decide that they will no longer assume the expense of instructors, facilities, and travel that ILT requires. Even though hybrid, custom solutions are almost always the best solution, an entire curriculum is often dictated as 100% e-learning without specific regard to instructional strategy.

So these choices are rarely a question of building the “ideal” but balancing the constraints and devising the best solution within those limits. In choosing a method and strategy, the primary questions always remain centered on the learner:

• What activity is required of the learner to demonstrate mastery? What modality will let me best achieve that, or conversely, given a modality, how can I best facilitate the learner doing this activity?
• How can I maximize individualization within the chosen modality?
• How can I maximize the value of feedback tailored to each individual?

Final Thoughts

The important thing to remember is that there is no one “ideal” solution. There are many ways to create an effective learning module. Remember, though, that the impact of the training, regardless of method and technology, depends on how the learner is engaged and motivated to respond to meaningful challenges with behaviors rooted in real performance.