Publication
Granularity-Adaptive Proof Presentation
Marvin Schiller; Christoph Benzmüller
In: Vania Dimitrova; Riichiro Mizoguchi; Benedict du Boulay; Art Graesser (Hrsg.). Artificial Intelligence in Education -- Building Learning Systems tat Care: From Knowledge Representation to Affective Modelling. International Conference on Artificial Intelligence in Education (AIED-09), July 6-10, Brighton, United Kingdom, Pages 599-601, Vol. 200, IOS Press, 2009.
Abstract
Granularity matters in mathematics. For example, in
introductory textbooks intermediate proof steps are often skipped,
when this seems appropriate. We present a flexible approach to proof
presentation that dynamically adapts to specific levels of granularity in context.
Different models for granularity can be learned in our framework from
samples using machine learning techniques.