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Self-regulation during e-learning: using behavioural evidence from navigation log files
ARTICLE

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Journal of Computer Assisted Learning Volume 30, Number 3, ISSN 1365-2729 Publisher: Wiley

Abstract

The current paper examined the relationship between perceived characteristics of the learning environment in an e-module in relation to test performance among a group of e-learners. Using structural equation modelling, the relationship between these variables is further explored in terms of the proposed double mediation as outlined by Ning and Downing. These authors initially proposed that motivation and self-regulation strategies are mediators between the perception of the learning environment and performance. In our replication and extension study, we substituted self-reported self-regulation with behavioural indicators of self-regulation using navigation log files and focused on test-taking rather than general motivation. We proposed that navigational patterns captured using log files can also help deduce self-regulation in e-modules and provide information in the absence of self-reports. Path analyses provide partial support for our navigational hypotheses and the model. Implications of our results for the use of e-module data and conclusions based on navigation are discussed.

Citation

Jeske, D., Backhaus, J. & Stamov Roßnagel, C. (2014). Self-regulation during e-learning: using behavioural evidence from navigation log files. Journal of Computer Assisted Learning, 30(3), 272-284. Wiley. Retrieved March 23, 2019 from .