Automating Next-Step Hints Generation Using ASTUS

Luc Paquette, Jean-François Lebeau, Gabriel Beaulieu, André Mayers

ASTUS is an authoring framework designed to create model-tracing tutors with similar efforts to those needed to create Cognitive Tutors. Its knowledge representation system was designed to model the teacher’s point of view of the task and to be manipulated by task independent processes such as the automatic generation of sophisticated pedagogical feedback. The first type of feedback we automated is instructions provided as next step hints. Whereas next step hints are classically authored by teachers and integrated in the model of the task, our framework automatically generates them from task independent templates. In this paper, we explain, using examples taken from a floating-point number conversion tutor, how our knowledge representation approach facilitates the generation of next-step hints. We then present experiments, conducted to validate our approach, showing that generated hints can be as efficient and appreciated as teacher authored ones.

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