Identifying patterns of learning : a case study of MIT's Introductory Programming Course (6.000x)
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
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The ever-increasingly relevant introductory programming course offered at MIT presents a unique opportunity to uncover student learning patterns and common behavioral motifs. The course 6.0001/6.0002 harbors a wealth of student interaction data on its companion MITx platform as well as associated grades. Although this course has been offered for the last twelve years, since 2008, little has been done to identify aspects of the course that best aid or hinder student success. This thesis will focus on finding various learner subpopulations to elucidate those materials that best aid certain students to allow for a more tailored teaching mode for future iterations of the course. In addition, this thesis will define an 'effort' statistic that encompasses the holistic engagement of a given student in order to provide an additional statistic to use when determining final grades. I begin with a course specific analysis of enrollment demonstrating the significance of this type of analysis.Given enrollment numbers that rival a general institute requirement, this analysis could easily extend its finding to these other large courses. In addition, I show how this course, by utilizing the MITx platform, best leverages a way to facilitate student introduction to a programming language. Second, I look to see how the introduction of an 'effort' statistic would positively affect grading outcomes for certain students near a letter grade border. I identify a possible mode to utilize this index during the determination of final grading as an additional measure in order to improve the issued letter grade. Lastly, curious to see generalizability of results, sought out to survey past students to see if their computed effort statistic aligned with their personal view of effort into the course. I furthermore use these findings to tabulate resources that are most helpful to student subpopulations.Collectively, the inquiries in this thesis form a foundation for a more equitable way of teaching where students are best equipped for success.
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, September, 2020Cataloged from student-submitted PDF of thesis.Includes bibliographical references (page 57).
DepartmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Massachusetts Institute of Technology
Electrical Engineering and Computer Science.