Semantically annotated learning paths

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Publication date
2023
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04B - Conference paper
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Pages / Duration
122-130
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Ascoli Piceno
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Abstract
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.
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Event
22nd International Conference on Perspectives in Business Informatics Research (BIR 2023)
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13.09.2023
Conference end date
15.09.2023
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Language
English
Created during FHNW affiliation
Yes
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Published
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Peer review of the complete publication
Open access category
Diamond
License
'https://creativecommons.org/licenses/by/4.0/'
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