Adaptive user support in educational environments: A Bayesian Network approach

TL;DR

This paper presents an adaptive user support system in an educational environment using Bayesian Belief Networks to provide personalized guidance based on student interactions, demonstrating promising preliminary results.

Contribution

It introduces a novel adaptive help system in an educational platform utilizing Bayesian networks derived from real student data.

Findings

System shows promising performance in preliminary evaluation

Bayesian network effectively models student interactions

Adaptive support improves guidance relevance

Abstract

This paper is concerned with the design and implementation of an innovative user support system in the frame of an open educational environment. The environment adapted is ModelsCreator (MC), an educational system supporting learning through modelling activities. The pupils typical interaction with the system was modelled us-ing Bayesian Belief Networks (BBN). This model has been used in ModelsCreator to build an adaptive help system providing the most useful guidelines according to the current state of interaction. A brief description of the system and an overview of application of Bayesian techniques to educational systems is presented together with discussion about the process of building of the Bayesian Network derived from actual student interaction data. A preliminary evaluation of the developed prototype indicates that the proposed approach produces systems with promising performance.