Temel Kavramlar
Discovering students' self-regulated learning processes through Process Mining Techniques.
Özet
The content discusses the application of Process Mining Techniques to assess self-regulated learning in e-learning environments. It covers the challenges faced in assessing skills beyond theoretical knowledge, focusing on self-regulation. The study methodology, data preprocessing, results, and conclusions are detailed. Key highlights include the use of Inductive Miner algorithm, fitness evaluation metrics, and visualization of student behavior models.
Structure:
Introduction to e-Learning and its challenges.
Importance of self-regulated learning assessment.
Methodology: Sample selection and data preprocessing.
Results: Fitness evaluation metrics by units and Pass-Fail groups.
Visualization of student behavior models.
Conclusions: Implications for teaching-learning processes.
İstatistikler
Data was extracted from 101 university students with 21,629 traces on Moodle 2.0 platform.
Fitness values ranged from 0.659 to 0.987 for different units and student groups.
Alıntılar
"Most literature focuses on students’ achievement outcomes rather than skill assessment in e-learning."
"E-learning brings new opportunities but poses challenges for students' self-regulation skills."