Abstract
The recent focus on learning analytics to analyse temporal dimensions of learning holds a strong promise to provide insights into latent constructs such as learning strategy, self-regulated learning, and metacognition. There is, however, a limited amount of research in temporally-focused process mining in educational settings. Building on a growing body of research around event-based data analysis, we explore the use of process mining techniques to identify strategic and tactical learner behaviours. We analyse trace data collected in online activities of a sample of nearly 300 computer engineering undergraduate students enrolled in a course that followed a flipped classroom pedagogy. Using a process mining approach based on first order Markov models in combination with unsupervised machine learning methods, we performed intra- and inter-strategy analysis. We found that certain temporal activity traits relate to performance in the summative assessments attached to the course, mediated by strategy type. Results show that more strategically minded activity, embodying learner self-regulation, generally proves to be more successful than less disciplined reactive behaviours.
Original language | English |
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Title of host publication | Lifelong Technology-Enhanced Learning |
Subtitle of host publication | 13th European Conference on Technology Enhanced Learning, EC-TEL 2018, Leeds, UK, September 3–5, 2018 Proceedings |
Editors | Viktoria Pammer-Schindler, Mar Perez-Sanagustin, Hendrik Drachsler, Raymond Elferink, Maren Scheffel |
Place of Publication | Cham Switzerland |
Publisher | Springer |
Pages | 385-398 |
Number of pages | 14 |
Edition | 1st |
ISBN (Electronic) | 9783319985725 |
ISBN (Print) | 9783319985718 |
DOIs | |
Publication status | Published - 2018 |
Event | European Conference on Technology Enhanced Learning (EC-TEL) 2018 - Leeds, United Kingdom Duration: 3 Sept 2018 → 5 Sept 2018 Conference number: 13th https://ea-tel.eu/the-13th-european-conference-on-technology-enhanced-learning-ec-tel-2018/ https://link.springer.com/book/10.1007/978-3-319-98572-5 (Proceedings) |
Publication series
Name | Lecture Notes in Computer Science |
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Publisher | Springer |
Volume | 11082 |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Conference
Conference | European Conference on Technology Enhanced Learning (EC-TEL) 2018 |
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Abbreviated title | EC-TEL 2018 |
Country/Territory | United Kingdom |
City | Leeds |
Period | 3/09/18 → 5/09/18 |
Internet address |
Keywords
- First order Markov models
- Learning analytics
- Process mining
- Self-regulated learning
- Temporal dynamics