Abstract
In today’s educational landscape, from traditional schools to MOOC platforms, the prevalent model is a one-size-fits-all approach to learning content, often overlooking the unique needs and learning paces of individual students. This gap between the ideal personalized instruction by a team of personal trainers and the practicalities of standardization presents significant challenges, including diminished engagement and understanding. My PhD research proposes a Knowledge Graph-based application of core Technology Enhanced Learning (TEL) components, aiming to bridge this divide with a cost-effective method targeted to individual learning objectives and paths.
The core elements of the approach are structured around five key components: Knowledge Graphs (KGs), Large Language Models (LLMs), Flashcards, Visualization of Dynamic Competence Maps (DCMs), and a Quality Assurance (QA) review and feedback workflow.
The approach will collect empirical data on students needs and misconceptions which allow to apply learning analytics for continuous improvement of the learning material.
We hypothesize that this approach will provide a viable method for digitization and entering into a quality improvement cycle based on the rating results, offering a concrete solution for the transition from traditional learning materials.
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.
- 3.
- 4.
- 5.
- 6.
- 7.
- 8.
References
Anderson, L.W., et al.: A Taxonomy for Learning, Teaching, and Assessing. Pearson, Upper Saddle River (2000)
Bloom, B.S. (ed.): Taxonomie von Lernzielen im kognitiven Bereich, 5th edn. Beltz Studienbuch, Julius Beltz, Weinheim, Germany (1976)
Carnovale, S., Allen, C., Pullman, M., Wong, D.: Using continuous improvement in online program design: DMAIC as a tool for assurance of learning assessments. Decis. Sci. J. Innov. Educ. 14(2), 128–153 (2016). https://doi.org/10.1111/dsji.12094
Durand, G., Belacel, N., LaPlante, F.: Graph theory based model for learning path recommendation. Inf. Sci. 251, 10–21 (2013). https://doi.org/10.1016/j.ins.2013.04.017
Erler, W., Gerzer-Saß, A., Nußhart, C., Saß, J.: Die kompetenzbilanz - ein instrument zur selbsteinschätzung und beruflichen entwicklung. In: Erpenbeck, J., Rosenstiel, L.V. (eds.) Handbuch Kompetenzmessung, pp. 339–352. Schäffer-Poeschel Verlag, Stuttgart (2003)
Heffler, B.: Individual learning style and the learning style inventory. Educ. Stud. 27(3), 307–316 (2001). https://doi.org/10.1080/03055690120076583
Heist, N., Haase, P.: Flexible and extensible competency management with knowledge graphs. In: Seneviratne, O., Pesquita, C., Sequeda, J., Etcheverry, L. (eds.) Proceedings of the ISWC 2021 Posters, Demos and Industry Tracks: From Novel Ideas to Industrial Practice co-located with 20th International Semantic Web Conference (ISWC 2021), Virtual Conference, 24–28 October 2021. CEUR Workshop Proceedings, vol. 2980. CEUR-WS.org (2021). https://ceur-ws.org/Vol-2980/paper412.pdf
Ilkou, E.: Personal knowledge graphs: use cases in e-learning platforms. In: Companion Proceedings of the Web Conference 2022, WWW 2022. ACM, April 2022. https://doi.org/10.1145/3487553.3524196
Leitner, S.: So lernt man lernen. Herder Spektrum, Verlag Herder, Freiburg, Germany, 18th edn., February 2011
Malashenko, G.T., et al.: A digital model of full-cycle training based on the Zettelkasten and interval repetition system. Emerg. Sci. J. 7, 1–15 (2023). https://doi.org/10.28991/esj-2023-sied2-01
Miller, G.E.: The assessment of clinical skills/competence/performance. Acad. Med. 65(9), S63-7 (1990). https://doi.org/10.1097/00001888-199009000-00045
Preißer, R., Völzke, R.: Kompetenzbilanzierung - hintergründe, verfahren, entwicklungsnotwendigkeiten. REPORT Zeitschrift für Weiterbildungsforschung 2007(1), 62–71 (2007). http://www.die-bonn.de/id/3549. Accessed 14 Feb 2024
Reich, J.: Failure to Disrupt. Harvard University Press, London (2022)
Reich, J., Ruipérez-Valiente, J.A.: The MOOC pivot. Science 363(6423), 130–131 (2019). https://doi.org/10.1126/science.aav7958
Shemshack, A., Kinshuk, Spector, J.M.: A comprehensive analysis of personalized learning components. J. Comput. Educ. 8(4), 485–503 (2021). https://doi.org/10.1007/s40692-021-00188-7
Triebel, C.: Kompetenzbilanzierung als psychologische Intervention: Wirkfaktoren und Wirkprinzipien in Laufbahnberatung und Coaching. Dissertation, Universität der Bundeswehr München, Munich, Germany (2009). https://d-nb.info/999369652/34, Doktors der Philosophie (Dr. phil.)
Yang, Y., Lin, J., Zhang, X., Wang, M.: PKG: a personal knowledge graph for recommendation. In: Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2022. ACM (2022). https://doi.org/10.1145/3477495.3531671
Yin, Y.: Integration of a Moodle Chatbot into Online Courses utilizing State-of-the-Art NLP Techniques. Bachelorarbeit, Advisor: Alexander Tobias Neumann, RWTH Aachen University, Aachen (2023). https://publications.rwth-aachen.de/record/977904, Bachelorarbeit, RWTH Aachen University, 2023
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2025 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Fahl, W. (2025). GraphWiseLearn: Personalized Learning Through Semantified TEL, Leveraging QA-Enhanced LLM-Generated Content. In: Meroño Peñuela, A., et al. The Semantic Web: ESWC 2024 Satellite Events. ESWC 2024. Lecture Notes in Computer Science, vol 15345. Springer, Cham. https://doi.org/10.1007/978-3-031-78955-7_8
Download citation
DOI: https://doi.org/10.1007/978-3-031-78955-7_8
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-78954-0
Online ISBN: 978-3-031-78955-7
eBook Packages: Computer ScienceComputer Science (R0)