Semantically annotated learning paths
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Author (Corporation)
Publication date
2023
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Course of study
Collections
Type
04B - Conference paper
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Parent work
Special issue
DOI of the original publication
Series
Series number
Volume
Issue / Number
Pages / Duration
122-130
Patent number
Publisher / Publishing institution
Place of publication / Event location
Ascoli Piceno
Edition
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Practice partner / Client
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.
Keywords
Subject (DDC)
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
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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
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