Enhancing learning with inspectable student models: Worth the effort?

S.G. Tacoma*, C. Geurts, B. Slof, J.T. Jeuring, P.H.M. Drijvers

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

In electronic learning environments, information about a student's performance can be provided to the student in the form of an inspectable student model. While relatively easy to implement, little is known about whether students use the feedback provided by such models and whether they benefit from it. In this study, the use of inspectable student models in an introductory university statistics course by 599 first-year social science students was monitored. Research questions focused on whether students sought feedback from the student models, which decisions for subsequent study steps they made, and how this feedback seeking and decision making related to results on their statistics exams. Results showed a large variety among students in feedback-seeking and decision-making behavior. Lower student model scores seemed to encourage students to practice more on the same topic and higher scores seemed to evoke the decision to move to a different topic. Viewing frequency and amount of variety in decision making were positively related to exam results, even when controlling for total time students worked. These findings imply that inspectable student models can be a valuable addition to electronic learning environments and suggest that more intensive use of inspectable student models may contribute to learning.
Original languageEnglish
Article number106276
JournalComputers in Human Behavior
Volume107
DOIs
Publication statusPublished - Jun 2020

Keywords

  • feedback-seeking behavior
  • higher education
  • inspectable student model
  • log file analysis
  • statistics education

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