Visualizing, Enhancing and Predicting Students’ Success through ECTS Monitoring
- This paper serves as an introduction to the ECTS monitoring system and its potential applications in higher education. It also emphasizes the potential for ECTS monitoring to become a proactive system, supporting students by predicting academic success and identifying groups of potential dropouts for tailored support services. The use of the nearest neighbor analysis is suggested for improving data analysis and prediction accuracy.
| Author: | Pia Kramer, Michael Bragard, Thomas Ritz, Ute Ferfer, Tim Schiffers |
|---|---|
| DOI: | https://doi.org/10.1109/EDUCON60312.2024.10578652 |
| ISSN: | 2165-9559 |
| ISSN: | 2165-9567 (eISSN) |
| Parent Title (English): | 2024 IEEE Global Engineering Education Conference (EDUCON) |
| Publisher: | IEEE |
| Place of publication: | New York, NY |
| Document Type: | Conference Proceeding |
| Language: | English |
| Year of Completion: | 2024 |
| Date of first Publication: | 2024/07/08 |
| Date of the Publication (Server): | 2024/07/09 |
| Tag: | Accuracy; Data analysis; Data visualization; Engineering education; Monitoring |
| Length: | 5 Seiten |
| Note: | 2024 IEEE Global Engineering Education Conference (EDUCON), 08-11 May 2024, Kos Island, Greece |
| Link: | https://doi.org/10.1109/EDUCON60312.2024.10578652 |
| Zugriffsart: | campus |
| Institutes: | FH Aachen / Fachbereich Elektrotechnik und Informationstechnik |
| collections: | Verlag / IEEE |
