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How well can completion of online courses be predicted using binary logistic regression?
University West, Department of Economics and IT, Division of Media and Design. (LINA)ORCID iD: 0000-0003-4425-9367
University West, Department of Economics and IT, Divison of Law, Economics, Statistics and Politics. (LINA)ORCID iD: 0000-0001-9781-2993
University West, Department of Economics and IT, Divison of Law, Economics, Statistics and Politics. (LINA)ORCID iD: 0000-0002-0575-4309
2016 (English)In: Proceedings of IRIS39, Information Systems Research Seminar in Scandinavia, Ljungskile, August 7-10, 2016 / [ed] Pareto, Lena, Svensson, Lars, Lundin, Johan, Lundh Snis, Ulrika Lundh Snis, 2016, 1-12 p.Conference paper (Other academic)
Abstract [en]

This article uses binary logistic regression to create models for predicting course performance. The data used is the data-trail left by students activities on a discussion forum while attending an online course. The purpose of the study is to evalute how well models based on binary logistic regression can be used to predict course completion.Three sets of data was used for this. One set collected at the end of the course, one collected after 75% of the course and one set collected after half the course. The result of the study says that it's possible to design models with an accuracy of between 70% and 80% using these methods, regardless of what time is used.

Place, publisher, year, edition, pages
2016. 1-12 p.
Keyword [en]
Online education, statistics, course completion, online forums, educational data mining
National Category
Information Systems, Social aspects
Research subject
SOCIAL SCIENCE, Informatics
Identifiers
URN: urn:nbn:se:hv:diva-10385ISBN: 978-91-87531-38-5 (USB)OAI: oai:DiVA.org:hv-10385DiVA: diva2:1059250
Conference
IRIS39, Information Systems Research Seminar in Scandinavia, Ljungskile, August 7-10, 2016
Available from: 2016-12-22 Created: 2016-12-22 Last updated: 2017-01-12

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Andersson, UlfArvemo, TobiasGellerstedt, Martin
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