This paper introduces AXIS (Adaptive eXplanation Improvement System), a system designed to generate and improve explanations for online learning materials. AXIS leverages learners to generate, revise, and evaluate explanations, employing machine learning to dynamically select the most helpful ones for future learners. A case study and randomized experiment demonstrate that AXIS elicits effective explanations that enhance learning, comparable to those created by experienced instructors.
Publisher
L@S 2016 Flipped Session
Published On
Apr 25, 2016
Authors
Joseph Jay Williams, Juho Kim, Anna Rafferty, Samuel Maldonado, Walter S. Lasecki, Neil Heffernan, Krzysztof Z. Gajos
