Modelling math learning on an open access intelligent tutor

This paper presents a methodology to analyze large amount of students’ learning states on two math courses offered by Global Fresh- man Academy program at Arizona State University. These two courses utilised ALEKS (Assessment and Learning in Knowledge Spaces) Arti- ficial Intelligence technology to facilitate massive open online learning. We explore social network analysis and unsupervised learning approaches (such as probabilistic graphical models) on these type of Intelligent Tu- toring Systems to examine the potential of the embedding representa- tions on students learning