Methods for observational studies using data from massive open online courses

Author(s)
Helbert, Justin (Justin C.)
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Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Advisor
Kalyan Veeramachaneni.
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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).
 
Date issued
2016
URI
http://hdl.handle.net/1721.1/106126
Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Publisher
Massachusetts Institute of Technology
Keywords
Electrical Engineering and Computer Science.
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