Abstract
This paper focuses on the study of automated process discovery using the Inductive visual Miner (IvM) and Directly Follows visual Miner (DFvM) algorithms to produce a valid process model for educational process mining in order to understand and predict the learning behavior of students. These models were evaluated on the publicly available xAPI (Experience API or Experience Application Programming Interface) dataset, which is an education dataset intended for tracking students’ classroom activities, participation in online communities, and performance. Experimental results with several performance measures show the effectiveness of the developed process models in helping experts to better understand students’ learning behavioral patterns.
Highlights
Process mining, a subset of data mining, is a tool where students’ collected activity logs can be used to discover non-trivial learning process information and create process models in terms of data flow diagrams, Petri nets, etc
The x-API education learning dataset used for the experiments shows the students’ behavior in the learning process
It was observed from the experiments that learning model discovery using process mining techniques could be useful for preventing dropouts or burdens in learning management systems
Summary
A subset of data mining, is a tool where students’ collected activity logs can be used to discover non-trivial learning process information and create process models in terms of data flow diagrams, Petri nets, etc. The main objective of process mining techniques are to extract an unambiguous process model from event logs and bridge the gap between traditional simulated model-based process analysis and data-oriented analysis techniques, such as machine learning and data mining. EPM uses end-to-end processes rather than local patterns to extract knowledge from event logs recorded using various ICT tools, such as online learning management systems (LMS) and MOOCs (massive open online courses) [4]. During the COVID-19 pandemic, online teaching and learning have become inevitable for students and teachers. This has created the possibility for students to learn from anywhere at any time, but the effectiveness of the online teaching and learning process has not been fully explored, with students facing struggles during online learning [5]
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