The educational data revolution has empowered universities and educational institutes with
rich data on their students, including information on their academic data (e.g., program
completion, course enrolment, grades), learning activities (e.g., learning materials reviewed,
discussion forum interactions, learning videos watched, projects conducted), learning process (i.e., time, place, path or pace of learning activities), learning experience (e.g., reflections, views, preferences) and assessment results.
In this paper, we apply clustering to profile students from one of the largest Massive Open Online Courses (MOOCs) in the field of Second Language Learning. ...