Hidden Markov Model for Inferring Learner Task Using Mouse Movement

TL;DR

This paper introduces a Hidden Markov Model approach to analyze learner mouse movements, enabling the inference of specific tasks performed in e-learning applications, thereby enhancing understanding of learner interactions.

Contribution

The paper presents a novel application of Hidden Markov Models to infer learner tasks from mouse movement data in e-learning environments.

Findings

Model successfully recognizes learner tasks from mouse movements

Effective analysis of learner interaction patterns

Potential for improving e-learning system responsiveness

Abstract

One of the issues of e-learning web based application is to understand how the learner interacts with an e-learning application to perform a given task. This study proposes a methodology to analyze learner mouse movement in order to infer the task performed. To do this, a Hidden Markov Model is used for modeling the interaction of the learner with an e-learning application. The obtained results show the ability of our model to analyze the interaction in order to recognize the task performed by the learner.