2026-09-19T22:42:35Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/1231152026-06-06T00:55:16Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Erik Hemberg and Una-May O'Reilly.
Wang, Li,M. Eng.Massachusetts Institute of Technology.
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2019-12-05T18:04:19Z
2019-12-05T18:04:19Z
2019
2019
https://hdl.handle.net/1721.1/123115
1128185293
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2019
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 61-62).
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.
by Li Wang.
M.Eng.
M.Eng. Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science
62 pages
eng
Massachusetts Institute of Technology
MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.
http://dspace.mit.edu/handle/1721.1/7582
Electrical Engineering and Computer Science.
The influence of grades on learning behavior of students in MOOCs
influence of grades on learning behavior of students in Massive Open Online Courses
Thesis
application/pdf
2019-12-05T18:04:18Z
Publication
Master
EECS
unknown
unknown
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<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.</Abstract>
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