Effective learning isn't just about finding the easiest path—it's about the right kind of challenge. Two prominent theories—Desirable Difficulties (DDF) and Cognitive Load Theory (CLT)—offer valuable ...

Active learning for multi-label classification addresses the challenge of labelling data in situations where each instance may belong to several overlapping categories. This paradigm aims to enhance ...

Theoretical physicists use machine-learning algorithms to speed up difficult calculations and eliminate untenable theories—but could they transform what it means to make discoveries? Theoretical ...

The Learning Design & Learning Sciences program prepares creative and adaptable learning scientists and designers who can transform learning in diverse contexts. Our program uniquely defines learning ...

Active learning puts students at the center of the learning process by encouraging them to engage, reflect, and apply what they’re learning in meaningful ways. Rather than passively receiving ...