HCMay 20, 2014

Hidden Markov Model for Inferring Learner Task Using Mouse Movement

arXiv:1405.5249v1
Originality Synthesis-oriented
AI Analysis

This addresses the issue of monitoring learner behavior in e-learning for educators or developers, but it is incremental as it applies an existing method to a new domain.

The study tackled the problem of understanding learner interactions in e-learning applications by proposing a Hidden Markov Model to infer tasks from mouse movements, with results showing the model's ability to recognize tasks.

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.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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