Mining Learning Styles for Personalised eLearning

In the drive to inspecting user behaviour in an adaptive eLearning system, we investigate the eye gaze movement in combination with the emotional state of learners with our experiment using eye tracker and the electroencephalography (EEG) technologies. The gaze behaviour not only indicates the type of learning style but also shows the set of cognitive activities and emotions that can contribute to the learning process. This paper discusses the first set of results of our experiment associated with monitoring the eye gaze behaviour. Six postgraduate students participated in this study. Two key findings were identified by combining many methods including boxplots and ANOVA. First, there was no effect on the complexity level of the visual/verbal learners behaviour. Second, subject's diversity has an effect on visual learner behaviour. Also, the paper describes the implemented experiment approach in our smart lab. And lastly, this paper exposes our analysis and investigation of learning styles in relation to the different courses, and how the eye behaviour is affected accordingly. The results of the EEG data will be analysed and correlated to our findings in the next piece of work.