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Integration of Large Language Models into Higher Education : A Perspective from Learners

Katerina, Zdravkova (författare)
University Ss. Cyril and Methodius, Macedonia
Dalipi, Fisnik, Associate professor (författare)
Linnéuniversitetet,Institutionen för informatik (IK)
Ahlgren, Fredrik, Senior Lecturer, 1980- (författare)
Linnéuniversitetet,Institutionen för datavetenskap och medieteknik (DM),Sjöfartshögskolan (SJÖ)
University Ss Cyril and Methodius, Macedonia Institutionen för informatik (IK) (creator_code:org_t)
IEEE, 2024
2024
Engelska.
Ingår i: 2<em>023 International Symposium on Computers in Education (SIIE)</em>, Setúbal, Portugal, 2023. - : IEEE. - 9798350329315 - 9798350329322
  • Konferensbidrag (refereegranskat)
Abstract Ämnesord
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  • Large language models (LLMs) are being criticized for copyright infringement, inadvertent bias in training data, a danger to human innovation, the possibility of distributing incorrect or misleading information, and prejudice. Due to their popularity among students, the introduction of many comparable apps, and the inability to resist unfair and fraudulent student usage, their educational use needs to be adapted and harmonized. The incorporation of LLMs should be defined not only by pedagogues and educational institutions, but also by students who will actively utilize them to learn and prepare assignments. In order to find out what students from two universities think and suggest about LLMs use in education, they were asked to give their contribution by answering the survey that was conducted at the beginning of the spring semester of academic 2022/23. Their feedback was quantitatively and qualitatively analyzed, showing in a better light what students think about LLMs and how and why they would use them. Based on the analysis, the authors propose an original strategy for integrating LLMs into education. The proposed approach is also adapted for those students who are not interested in using LLMs and for those who prefer the hybrid mode by combining their own research with LLMs generated recommendations. The authors expect that by implementing the proposed strategy, schools will benefit from a better education in which research, creativity, academic honesty, recognition of false information, and the ability to improve knowledge will prevail.

Ämnesord

NATURVETENSKAP  -- Data- och informationsvetenskap (hsv//swe)
NATURAL SCIENCES  -- Computer and Information Sciences (hsv//eng)

Nyckelord

AI learning tool
ChatGPT
large language models
academic integrity
students’ feedback
higher education
Data- och informationsvetenskap
Computer and Information Sciences Computer Science

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Linnéuniversitetet

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