The influence of grades on learning behavior of students in MOOCs

Abstract

In this thesis, we explore and analyze impact of grades on the behavior of students in MOOCs (Massive Open Online Courses). MOOCs often use grades to give students feedback on their understanding of course material and to determine whether a student passes the course. To better understand how student behavior is influenced by grade feedback, we conduct a study on the changes of certified students' behavior before and after they have received their grade. We define continuously participating students as students who continuously do graded assignments up until a specific assignment and how their behavior compares to certified students. Afterwards, we look into the effects of past experience and how these metrics can be used to predict grades with various machine learning models. We observe that both certified and continuously participating students do not change their learning behavior after receiving a specific grade. We also observe that both groups of students with lower grades have more consistent learning behavior than those with higher grades. Lastly, we observe no obvious correlation between past experience, student activity, and grade.