Methods for observational studies using data from massive open online courses
Name
965831206-MIT.pdf
Description
Full printable version
Size
3.94 MB
Format
Adobe PDF
Checksum (MD5)
c0a8b9cdb464a5a89f7e59629e1ede05
Author(s)
Helbert, Justin (Justin C.)
Advisor(s)
Kalyan Veeramachaneni.
Date Issued
2016
Publisher
Massachusetts Institute of Technology
Abstract
Measuring the effect of a course component in online classes present an opportunity to use propensity score methods. Propensity score methods aim to balance the effect of self-selecting biases and other confounding variables that arise in observational studies like this, as each student decides what components they engage in throughout the course. This method is applied to an edX course, 6.002x, to estimate the effect of attempting homework and other assessments on students' final exam performance.
Description
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2016.
Cataloged from PDF version of thesis.
Includes bibliographical references (page 51).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.
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