Analyzing User Behavior in a Self-regulated Learning Environment

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


E-learning systems present an opportunity for both students and the field of education that has been steadily increasing in importance, especially over the past few years. This paper examines an intra-university e-learning course built on the principle of self-regulated learning, with the goal of finding behavioral patterns in the way learners navigated the content. The limitations associated with the amount of data generated by the only 31 students who took part in the course presented a challenge to the popular machine learning algorithms, which ultimately led to a combination of sequence extraction methods and heat maps being used in the evaluation. By classifying users both according to their learning behavior and their course performance, it was possible to put organised and unorganised learning behavior into relation with course performance. The findings show a higher likelihood for students who displayed unstructured learning behavior to repeat assessments than for students demonstrating structured pathways through the learning content, who tended to attain full points on their first attempt. Additionally, students who repeated assessments often reviewed more previously studied content and had shorter sequences where they only viewed content that was new to them. Overall, the specific setting of the course and the data limitations mean that it would be beneficial to reconstruct the research with larger data sets, which would also allow for the usage of machine learning algorithms in the analysis.
Original languageEnglish
Title of host publicationInnovations in Learning and Technology for the Workplace and Higher Education - Proceedings of ‘The Learning Ideas Conference, 2021
Subtitle of host publicationTLIC 2021
EditorsDavid Guralnick, Michael E. Auer, Antonella Poce
Place of PublicationCham
Number of pages10
ISBN (Electronic)978-3-030-90677-1
ISBN (Print)978-3-030-90676-4
Publication statusPublished - 2022
EventThe Learning Ideas Conference 2021: Innovations in Learning and Technology for the Workplace and Higher Education - Virtuell, United States
Duration: 16 Jun 202116 Jun 2021

Publication series

NameLecture Notes in Networks and Systems
Volume349 LNNS
ISSN (Print)2367-3370
ISSN (Electronic)2367-3389


ConferenceThe Learning Ideas Conference 2021
Abbreviated titleTLIC 2021
Country/TerritoryUnited States
Internet address


  • E-learning
  • Self-regulated learning
  • Sequence mining

ASJC Scopus subject areas

  • Signal Processing
  • Control and Systems Engineering
  • Computer Networks and Communications

Fields of Expertise

  • Information, Communication & Computing


Dive into the research topics of 'Analyzing User Behavior in a Self-regulated Learning Environment'. Together they form a unique fingerprint.

Cite this