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Analysis and Improvement of Engineering Exams Toward Competence Orientation by Using an AI Chatbot

  • ChatGPT is currently one of the most advanced general chatbots. This development leads to diverse challenges in higher education, like new forms of teaching and learning, additional exam methods, new possibilities for plagiarism, and many more topics. On the other side with the development of advanced AI tools, pure knowledge will be less and less important, and demands from industry will change toward graduates with higher competencies. Education has therefore to be changed from knowledge-centered toward competence centered. The goal of this article is to use ChatGPT for analyzing and improving the competence orientation of exams in engineering education. The authors use ChatGPT to analyze exams from different engineering subjects to evaluate the performance of this chatbot and draw conclusions about the competence orientation of the tested exams. The obtained information is used to develop ideas for increasing the competence orientation of exams. From this analysis, it is visible that ChatGPT gives good performance mainly where knowledge is tested. It has, however, much more problems with transfer questions or tasks where students need creativity or complex insights for finding new solutions. Based on this result, exams and also lectures can be optimized toward competence orientation.

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Metadaten
Author:Thomas FuhrmannORCiDGND, Michael NiemetzORCiDGND
DOI:https://doi.org/10.1007/978-3-031-51979-6_42
ISBN:9783031519789
ISSN:2367-3370
Parent Title (English):Towards a Hybrid, Flexible and Socially Engaged Higher Education: Proceedings of the 26th International Conference on Interactive Collaborative Learning (ICL2023), Volume 1
Publisher:Springer Nature
Place of publication:Cham
Document Type:conference proceeding (article)
Language:English
Year of first Publication:2024
Release Date:2024/02/08
Tag:AI chatbot; ChatGPT; Competence orientation; Engineering education; Exam analysis
First Page:403
Last Page:411
Andere Schriftenreihe:Lecture Notes in Networks and Systems ; 899
Institutes:Fakultät Elektro- und Informationstechnik
Fakultät Elektro- und Informationstechnik / Labor Datenkommunikation
Fakultät Elektro- und Informationstechnik / Labor Optische Übertragungssysteme
research focus:Energie und Mobilität
Licence (German):Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG