Hidden Markov model for inferring user task using mouse movement

The assistive technology and e-learning have been widely used to improve web accessibility for disabled users. One of the issues of online web-based applications is to understand how a user interacts with online application and the strategy by which he reasons to perform a given activity. Know what the web user is doing can provide useful clues to better understand his behavior in order to guide him in his interaction process. This study proposes a methodology to analyze user mouse movement in order to infer the task performed by the user. 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.