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The Impact of Artificial Intelligence on Cognitive Load in Computing Education
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division Vi3. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Education Research.ORCID iD: 0000-0002-5791-4765
Mid Sweden University; University of Gävle.
2024 (English)In: Proceedings of the 19th SweCog Conference / [ed] Jonas Olofsson; Teodor Jernsäther-Ohlsson; Sofia Thunberg; Linus Holm; Erik Billing, Swedish Cognitive Science Society , 2024, p. 23-26Conference paper, Published paper (Refereed)
Abstract [en]

The rapid development of Generative AI (GAI) makes an impact in many fields of our society, and for higher education this is a fact that must be addressed. Research has reported on GAI creating new challenges, and GAI as a catalyst for a transformation of higher education (Chiu, 2024; Yusuf et al., 2024). According to Chiu (2024) the four most important educational domains to consider are learning, teaching, assessment and administration. This study had a focus on learning, and as pointed out by Choudhuri et al. (2024), there is a gap in the understanding of the potential and the pitfalls when using GAI in computing education. The aim of this paper is to explore the potential impact of AI technologies on cognitive load, relevant for computing education at higher education level. The research question to answer is:

What is the potential impact of AI technologies on cognitive load in computing education according to recent research?

Place, publisher, year, edition, pages
Swedish Cognitive Science Society , 2024. p. 23-26
Series
Skövde University Studies in Informatics, ISSN 1653-2325 ; 2024:1
Keywords [en]
Artificial Intelligence, Cognitive Load, Computing Education, Scoping Literature Review
National Category
Didactics Human Computer Interaction
Research subject
Computer Science with specialization in Computer Science Education Research
Identifiers
URN: urn:nbn:se:uu:diva-540185ISBN: 978-91-989038-1-2 (print)OAI: oai:DiVA.org:uu-540185DiVA, id: diva2:1904967
Conference
19th SweCog Conference, Stockholm, Sweden, 10-11 October, 2024
Available from: 2024-10-10 Created: 2024-10-10 Last updated: 2024-10-11Bibliographically approved

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CiteExportLink to record
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