Semantically annotated learning paths

This paper shows an application of semantic lifting in the education domain. We present a metamodel for graphical representation of learning paths. This supports lecturers in the design of courses and learners to navigate through learning object to achieve their learning goals. The graphical models are semantically annotated with an ontology representing the content of the course and the learning objects. This enables reasoning for identifying learning objects dealing with specific topics and courses dealing with prerequisite knowledge. The approach is realized in ADOxx and validated with courses and lectures at a university of applied sciences in Switzerland.

Schlagwörter

Fachgebiet (DDC)

330 - Wirtschaft

Projekt

Veranstaltung

22nd International Conference on Perspectives in Business Informatics Research (BIR 2023)

Startdatum der Ausstellung

Enddatum der Ausstellung

Startdatum der Konferenz

13.09.2023

Enddatum der Konferenz

15.09.2023

Datum der letzten Prüfung

ISBN

ISSN

Sprache

Englisch

Während FHNW Zugehörigkeit erstellt

Ja

Zukunftsfelder FHNW

Publikationsstatus

Veröffentlicht

Begutachtung

Peer-Review der ganzen Publikation

Open Access-Status

Diamond

Lizenz

Zitation

Unternährer, C., Hinkelmann, K., & Schlick, S. (2023). Semantically annotated learning paths (A. Morichetta, R. A. Buchmann, K. Sandkuhl, U. Seigerroth, M. Kirikova, C. Møller, P. Forbrig, A. Gutschmidt, A.-M. Ghiran, A. Marcelletti, F. Härer, B. Re, B. Johansson, & Joint Proceedings of the BIR 2023 Workshops and Doctoral Consortium co-located with 22nd International Conference on Perspectives in Business Informatics Research (BIR 2023), Eds.; pp. 122–130). https://doi.org/10.26041/fhnw-10942

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