Personalized instruction: The other half of personalized learning

As I have explained in a previous post on personalized learning, an important dimension along which personalized learning goes beyond merely adaptive learning is to personalize the experience on the instructional side, not just the learner side. Amidst all the excitement about adaptive learning, teachers remain an often-forgotten yet crucial part of the equation. Well-designed personalization takes advantage of the human intelligence embedded in expert instructors, including opportunities for them to exercise their professional judgment in deciding which activities will work best for their students given their particular contexts and constraints.

This EdSurge report mentions Rocketship’s upcoming changes, as “New model attempts to bring teachers closer to students’ online learning experience” by returning some classroom control back to the teacher:

Rocketship’s new model will shift focus from running purely adaptive programs, to using programs that give teachers greater control over content that gets assigned.

What this highlights is the need for the design of personalized learning programs to identify when to allocate decisions to teachers (possibly with recommendations among which to choose) and when to adapt the students’ learning experience immediately, without need for waiting for additional human input. While this depends in part on the professional knowledge of the instructors implementing the system, some decisions may be straightforward or simple enough to automate. Decisions best left to expert human intervention are likely to be more complex, to depend on more contingencies, to require interpersonal contact, or to have more uncertainty in their effectiveness. Where that balance lies is subject to continual readjustment, but since there are always unknowns and since social interaction is fundamental to the human experience, there will always remain a need for personalization.