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Computer-Assisted Reading and Discovery for Student Generated Text in Massive Open Online Courses

HarvardX Working Paper Series Number 6

32 Pages Posted: 23 Sep 2014  

Justin Reich

Massachusetts Institute of Technology (MIT) - Office of Digital Learning

Dustin H. Tingley

Harvard University - Department of Government

Jetson Leder-Luis

Massachusetts Institute of Technology (MIT)

Margaret E. Roberts

Harvard University

Brandon Stewart

Princeton University - Department of Sociology

Date Written: September 22, 2014

Abstract

Dealing with the vast quantities of text that students generate in a Massive Open Online Course (MOOC) is a daunting challenge. Computational tools are needed to help instructional teams uncover themes and patterns as MOOC students write in forums, assignments, and surveys. This paper introduces to the learning analytics community the Structural Topic Model, an approach to language processing that can (1) find syntactic patterns with semantic meaning in unstructured text, (2) identify variation in those patterns across covariates, and (3) uncover archetypal texts that exemplify the documents within a topical pattern. We show examples of computationally-aided discovery and reading in three MOOC settings: mapping students’ self-reported motivations, identifying themes in discussion forums, and uncovering patterns of feedback in course evaluations.

Keywords: MOOC, Structural Topic Model, text analysis, forums, surveys

Suggested Citation

Reich, Justin and Tingley, Dustin H. and Leder-Luis, Jetson and Roberts, Margaret E. and Stewart, Brandon, Computer-Assisted Reading and Discovery for Student Generated Text in Massive Open Online Courses (September 22, 2014). HarvardX Working Paper Series Number 6. Available at SSRN: https://ssrn.com/abstract=2499725 or http://dx.doi.org/10.2139/ssrn.2499725

Justin Reich (Contact Author)

Massachusetts Institute of Technology (MIT) - Office of Digital Learning ( email )

77 Massachusetts Avenue
Cambridge, MA 02139
United States

Dustin H. Tingley

Harvard University - Department of Government ( email )

1737 Cambridge Street
Cambridge, MA 02138
United States

Jetson Leder-Luis

Massachusetts Institute of Technology (MIT) ( email )

77 Massachusetts Avenue
50 Memorial Drive
Cambridge, MA 02139-4307
United States

Margaret E. Roberts

Harvard University ( email )

1875 Cambridge Street
Cambridge, MA 02138
United States

Brandon Stewart

Princeton University - Department of Sociology ( email )

Princeton, NJ
United States

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