Abstract
Digital systems that enable so-called intelligent, adaptive or personalized learning are thought to bear great potential for the future of education. Research and development towards such innovative learning systems has therefore evolved into an expanding field. Two of the key challenges are (1) to automate the extraction of expert knowledge and (2) the development of an advanced domain model, on which the system can draw. To tackle these challenges, our interdisciplinary contribution is to suggest adopting a novel approach to creating educational knowledge graphs of texts (1), which can then be further annotated and supplemented by instructors and students (2). In particular, we will outline practical use cases for blended learning scenarios in Higher Education.
This work was supported by the German Federal Ministry of Education and Research for the tech4comp project under grant No. 16DHB2102.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
- 2.
Tarql: https://tarql.github.io/.
- 3.
RDF mappings: https://gitlab.com/Tech4Comp/t-mitocar-rdf-transformation.
References
Chen, P., Lu, Y., Zheng, V.W., Chen, X., Yang, B.: KnowEdu: a system to construct knowledge graph for education. IEEE Access 6, 31553–31563 (2018)
Hofmann, S.: E-Learning und ontologisch strukturierte Planung webbasierter Lehr-Lern-Szenarien. Logos Verlag Berlin GmbH (2015)
Holmes, W., Bialik, M., Fadel, C.: Artificial Intelligence Education. Center for Curriculum Redesign, Boston (2019)
Kalyuga, S.: Prior knowledge principle in multimedia learning. In: The Cambridge Handbook of Multimedia Learning, pp. 325–337 (2005)
Pirnay-Dummer, P., Ifenthaler, D.: Reading guided by automated graphical representations. Instr. Sci. 39(6), 901–919 (2011)
Rizun, M., et al.: Knowledge graph application in education: a literature review. Acta Universitatis Lodziensis. Folia Oeconomica 3(342), 7–19 (2019)
Seel, N.M., Hanke, U.: Erziehungswissenschaft. Springer, Berlin, Heidelberg (2015). https://doi.org/10.1007/978-3-642-55206-9
Author information
Authors and Affiliations
Corresponding authors
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Meissner, R., Köbis, L. (2020). Annotated Knowledge Graphs for Teaching in Higher Education. In: Bielikova, M., Mikkonen, T., Pautasso, C. (eds) Web Engineering. ICWE 2020. Lecture Notes in Computer Science(), vol 12128. Springer, Cham. https://doi.org/10.1007/978-3-030-50578-3_43
Download citation
DOI: https://doi.org/10.1007/978-3-030-50578-3_43
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-50577-6
Online ISBN: 978-3-030-50578-3
eBook Packages: Computer ScienceComputer Science (R0)