Using process mining to analyze students' quiz-taking behavior patterns in a learning management system
| Authors | |
|---|---|
| Year of publication | 2019 |
| Type | Article in Periodical |
| Magazine / Source | Computers in Human Behavior |
| MU Faculty or unit | |
| Citation | |
| web | http://www.sciencedirect.com/science/article/pii/S0747563217306957 |
| Doi | http://dx.doi.org/10.1016/j.chb.2017.12.015 |
| Field | Pedagogy and education |
| Keywords | educational data mining; learning analytics; process mining; quiz-taking behavior; student interaction analysis; learning management system |
| Description | The aim of this paper is to explore students’ behavior and interaction patterns in different types of online quiz-based activities within learning management systems (LMS). Analyzing students’ behavior in online learning activities and detecting specific patterns of interaction in LMS is a topic of great interest for the educational data mining (EDM) and learning analytics (LA) research communities. Previous studies have focused primarily on frequency analysis without addressing the temporal aspects of students’ learning behavior. Therefore, we apply a process-oriented approach, investigating perspectives on using process mining methods in the context of online learning and assessment. To explore a broad range of possible student behavior patterns, we analyze students’ interactions in several online quizzes from different courses and with different settings. Using process mining methods, we identify specific types of interaction sequences that shed new light on students’ quiz-taking strategies in LMS. We believe that these findings bring important implications for researchers studying student behavior in online environments as well as practitioners using online quizzes for learning and assessment. |
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