Analyzing Behavioral Patterns in an Introductory Programming MOOC at University Level

Alexander Steinmaurer, Christoph Schatz, Johannes Krugel, Christian Gütl

Research output: Chapter in Book/Report/Conference proceedingConference paperpeer-review

Abstract

Massive open online courses (MOOCs) are an indispensable component in university education today. In large introductory courses especially, MOOCs can promote the efficiency of online teaching tremendously, since a large and heterogeneous group of students can be prepared for further courses and learn self-paced and self-directed. However, MOOCs are also characterized by high dropout rates and with a small group of people only completing the course. In this paper, we analyzed the Learning Object Oriented Programming MOOC from Technical University of Munich, an edX course that is dedicated to first-year students in different fields. The course run of 2019 with 2,489 enrolled users is analyzed for this purpose. The dropouts (89 %) were analyzed to better understand future course design. Interaction in the MOOC was considered in this context as a means of detecting behavioral patterns and predicting early dropouts. We found that the interaction with certain MOOC elements such as videos or the problem tool had a major impact on course success. These results may be useful for earlier dropout predictions and the design of future courses to provide an engaging environment with fewer students quitting the course.
Original languageEnglish
Title of host publicationProceedings of 2022 IEEE Learning with MOOCS, LWMOOCS 2022
PublisherACM/IEEE
Pages114-119
Number of pages6
ISBN (Electronic)9781665424868
ISBN (Print)978-1-6654-2487-5
DOIs
Publication statusPublished - 30 Sep 2022
Event2022 IEEE Learning with MOOCS: LWMOOCS 2022 - Antigua Guatemala, Guatemala
Duration: 29 Sep 202230 Sep 2022

Publication series

NameProceedings of 2022 IEEE Learning with MOOCS, LWMOOCS 2022

Conference

Conference2022 IEEE Learning with MOOCS
Country/TerritoryGuatemala
CityAntigua Guatemala
Period29/09/2230/09/22

Keywords

  • Computer aided instruction
  • Electronic learning
  • Distance learning
  • Education
  • Behavioral sciences
  • Object oriented programming
  • Programming profession
  • MOOC analysis
  • drop-out prediction
  • behavioral patterns

ASJC Scopus subject areas

  • Education
  • Computer Networks and Communications
  • Media Technology

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