Prerequisite Structure Discovery in Intelligent Tutoring Systems
Louis Annabi Sao Mai Nguyen
This paper addresses the importance of Knowledge Structure (KS) and Knowledge
Tracing (KT) in improving the recommendation of educational content in
intelligent tutoring systems. The KS represents the relations between different
Knowledge Components (KCs), while KT predicts a learner's success based on her
past history. The contribution of this research includes proposing a KT model
that incorporates the KS as a learnable parameter, enabling the discovery of
the underlying KS from learner trajectories. The quality of the uncovered KS is
assessed by using it to recommend content and evaluating the recommendation
algorithm with simulated students.