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.

Keywords

Subject (DDC)

330 - Wirtschaft

Project

Event

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

Exhibition start date

Exhibition end date

Conference start date

13.09.2023

Conference end date

15.09.2023

Date of the last check

ISBN

ISSN

Language

English

Created during FHNW affiliation

Yes

Strategic action fields FHNW

Publication status

Published

Review

Peer review of the complete publication

Open access category

Diamond

License

Citation

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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