Data quality challenges in educational process mining: building process-oriented event logs from process-unaware online learning systems

Rahila Umer, Teo Susnjak, Anuradha Mathrani and Suriadi Suriadi

International Journal of Business Information Systems, 2022, vol. 39, issue 4, 569-592

Abstract: Educational process mining utilises process-oriented event logs to enable discovery of learning practices that can be used for the learner's advantage. However, learning platforms are often process-unaware, therefore do not accurately reflect ongoing learner interactions. We demonstrate how contextually relevant process models can be constructed from process-unaware systems. Using a popular learning management system (Moodle), we have extracted stand-alone activities from the underlying database and formatted it to link the learners' data explicitly to process instances (cases). With a running example that describes quiz-taking activities undertaken by students, we describe how learner interactions can be captured to build process-oriented event logs. This article contributes to the fields of learning analytics and education process mining by providing lessons learned on the extraction and conversion of process-unaware data to event logs for the purpose of analysing online education data.

Keywords: learning analytics; process mining; quiz-taking behaviour; learning management system; education data; process instance; data quality. (search for similar items in EconPapers)
Date: 2022
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