Educational data mining and learning analytics in programming: Literature review and case studies

Petri Ihantola, Arto Vihavainen, Alireza Ahadi, Matthew Butler, Jürgen Börstler, Stephen H. Edwards, Essi Isohanni, Ari Korhonen, Andrew Petersen, Kelly Rivers, Miguel Ángel Rubio, Judy Sheard, Bronius Skupas, Jaime Spacco, Claudia Szabo, Daniel Toll

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

111 Citations (Scopus)

Abstract

Educational data mining and learning analytics promise better understanding of student behavior and knowledge, as well as new information on the tacit factors that contribute to student actions. This knowledge can be used to inform decisions related to course and tool design and pedagogy, and to further engage students and guide those at risk of failure. This working group report provides an overview of the body of knowledge regarding the use of educational data mining and learning analytics focused on the teaching and learning of programming. In a literature survey on mining students' programming processes for 2005-2015, we observe a significant increase in work related to the field. However, the majority of the studies focus on simplistic metric analysis and are conducted within a single institution and a single course. This indicates the existence of further avenues of research and a critical need for validation and replication to better understand the various contributing factors and the reasons why certain results occur. We introduce a novel taxonomy to analyse replicating studies and discuss the importance of replicating and reproducing previous work. We describe what is the state of the art in collecting and sharing programming data. To better understand the challenges involved in replicating or reproducing existing studies, we report our experiences from three case studies using programming data. Finally, we present a discussion of future directions for the education and research community.

Original languageEnglish
Title of host publicationProceedings of the 2015 ITiCSE Conference on Working Group Reports, ITiCSE-WGP 2015
PublisherACM
Pages41-63
Number of pages23
ISBN (Electronic)9781450341462
DOIs
Publication statusPublished - 4 Jul 2016
MoE publication typeA4 Article in a conference publication
EventAnnual Conference on Innovation and Technology in Computer Science Education - Vilnius University, Vilnius, Lithuania
Duration: 6 Jul 20158 Jul 2015
Conference number: 20
http://www.iticse2015.mii.vu.lt/

Publication series

NameAnnual Conference on Innovation & Technology in Computer Science Education
PublisherACM
ISSN (Print)1942-647X

Conference

ConferenceAnnual Conference on Innovation and Technology in Computer Science Education
Abbreviated titleiTiCSE
CountryLithuania
CityVilnius
Period06/07/201508/07/2015
Internet address

Keywords

  • Educational data mining
  • Learning analytics
  • Literature review
  • Programming
  • Replication

Fingerprint Dive into the research topics of 'Educational data mining and learning analytics in programming: Literature review and case studies'. Together they form a unique fingerprint.

  • Cite this

    Ihantola, P., Vihavainen, A., Ahadi, A., Butler, M., Börstler, J., Edwards, S. H., ... Toll, D. (2016). Educational data mining and learning analytics in programming: Literature review and case studies. In Proceedings of the 2015 ITiCSE Conference on Working Group Reports, ITiCSE-WGP 2015 (pp. 41-63). (Annual Conference on Innovation & Technology in Computer Science Education). ACM. https://doi.org/10.1145/2858796.2858798