Enhancing E-learning effectiveness:a process mining approach for short-term tutorials
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| Title: | Enhancing E-learning effectiveness:a process mining approach for short-term tutorials |
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| Authors: | Nai, Roberto, Sulis, Emilio, Genga, Laura |
| Source: | Nai, R, Sulis, E & Genga, L 2024, 'Enhancing E-learning effectiveness : a process mining approach for short-term tutorials', Journal of Intelligent Information Systems, vol. 62, no. 6, pp. 1773-1794. https://doi.org/10.1007/s10844-024-00874-9 |
| Publication Year: | 2024 |
| Subject Terms: | Learning outcomes, Predictive process monitoring, Process mining, Tutorial design, User behaviour tracking |
| Description: | The rise of e-learning systems has revolutionized education, enabling the collection of valuable students’ activity data for continuous improvement. While existing studies have predominantly focused on prolonged learning paths, short-term tutorials offer a flexible and efficient alternative that is recently gaining increasing popularity. This article presents a methodology for investigating e-learning systems for short-term tutorials leveraging user behavior tracking and process mining techniques. A case study involving a web-based tutorial with approximately one hour of learning explores the learning processes of 250 students in Italy. The study analyzes learning outcomes and investigates the impact of different learning paths on student progress. The research questions concern i) the extraction of activity flows in short-term tutorials; ii) the prediction of outcomes in the early stages of short-term learning process. The proposed approach provides descriptive insights into the learning process which can also be used to offer prescriptive guidance. |
| Document Type: | article in journal/newspaper |
| File Description: | application/pdf |
| Language: | English |
| ISSN: | 0925-9902 1573-7675 |
| Relation: | info:eu-repo/semantics/altIdentifier/pissn/0925-9902; info:eu-repo/semantics/altIdentifier/eissn/1573-7675 |
| DOI: | 10.1007/s10844-024-00874-9 |
| Availability: | https://research.tue.nl/en/publications/12e26133-713c-49fa-8869-58ddbc1b5dce https://doi.org/10.1007/s10844-024-00874-9 https://pure.tue.nl/ws/files/351892451/s10844-024-00874-9.pdf https://www.scopus.com/pages/publications/85200961040 |
| Rights: | info:eu-repo/semantics/openAccess ; http://creativecommons.org/licenses/by/4.0/ |
| Accession Number: | edsbas.C073D1D8 |
| Database: | BASE |
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Nájsť tento článok vo Web of Science | Abstract: | The rise of e-learning systems has revolutionized education, enabling the collection of valuable students’ activity data for continuous improvement. While existing studies have predominantly focused on prolonged learning paths, short-term tutorials offer a flexible and efficient alternative that is recently gaining increasing popularity. This article presents a methodology for investigating e-learning systems for short-term tutorials leveraging user behavior tracking and process mining techniques. A case study involving a web-based tutorial with approximately one hour of learning explores the learning processes of 250 students in Italy. The study analyzes learning outcomes and investigates the impact of different learning paths on student progress. The research questions concern i) the extraction of activity flows in short-term tutorials; ii) the prediction of outcomes in the early stages of short-term learning process. The proposed approach provides descriptive insights into the learning process which can also be used to offer prescriptive guidance. |
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| ISSN: | 09259902 15737675 |
| DOI: | 10.1007/s10844-024-00874-9 |