A Web-Based Recommendation System for Higher Education: SIDDATA - History, Architecture and Future of a Digital Data-Driven Study Assistant
Bitte benutzen Sie diese Kennung, um auf die Ressource zu verweisen:
https://doi.org/10.48693/294
https://doi.org/10.48693/294
| Titel: | A Web-Based Recommendation System for Higher Education: SIDDATA - History, Architecture and Future of a Digital Data-Driven Study Assistant |
| Autor(en): | Weber, Felix Schrumpf, Johannes Dettmer, Niklas Thelen, Tobias |
| ORCID des Autors: | https://orcid.org/0000-0002-7012-3378 https://orcid.org/0000-0002-0068-273X https://orcid.org/0000-0001-9944-1671 https://orcid.org/0000-0002-3337-6093 |
| Zusammenfassung: | The SIDDATA data-driven digital study assistant offers students various services that help them identify and achieve their personal study goals. The software’s features and infrastructure have evolved to become a universal platform for interactive self-regulated learning and digital study planning throughout three annual software development cycle iterations. The software is fully integrated into an existing learning management system (Stud.IP) and has been tested by more than 3000 students from three German universities during the last three years. This paper presents the SIDDATA software architecture, its design philosophy, and its modular, feature-centered application logic. Developed during a third-party funded research project with limited temporal scope, the web-based software is publicly available under an MIT license. We conclude with application opportunities for researchers, developers, educators, and higher education institutions. |
| Bibliografische Angaben: | Weber, F., Schrumpf, J., Dettmer, N., & Thelen, T. (2022). A Web-Based Recommendation System for Higher Education: SIDDATA: History, Architecture and Future of a Digital Data-Driven Study Assistant . International Journal of Emerging Technologies in Learning (iJET), 17(22), pp. 246–254. |
| URL: | https://doi.org/10.48693/294 https://osnadocs.ub.uni-osnabrueck.de/handle/ds-202304198695 |
| Schlagworte: | Digital Student Assistant; E-learning; Artificial Intelligence; Innovative Learning Technologies |
| Erscheinungsdatum: | 28-Nov-2022 |
| Lizenzbezeichnung: | Attribution 4.0 International |
| URL der Lizenz: | http://creativecommons.org/licenses/by/4.0/ |
| Publikationstyp: | Einzelbeitrag in einer wissenschaftlichen Zeitschrift [Article] |
| Enthalten in den Sammlungen: | Open-Access-Publikationsfonds virtUOS Working Papers |
Dateien zu dieser Ressource:
| Datei | Beschreibung | Größe | Format | |
|---|---|---|---|---|
| Weber_etal_JET_2022.pdf | Article | 1,03 MB | Adobe PDF | Weber_etal_JET_2022.pdf  Öffnen/Anzeigen |
Diese Ressource wurde unter folgender Copyright-Bestimmung veröffentlicht:
Lizenz von Creative Commons
