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  4. Leveraging ChatGPT to Enhance Computational Thinking Learning Experiences

Leveraging ChatGPT to Enhance Computational Thinking Learning Experiences

Author(s)
Ouaazki, Abdessalam  
Chaire de management de l'information  
Bergram, Kristoffer  
Faculté des sciences économiques  
Holzer, Adrian  
Chaire de management des systèmes d'information  
Date issued
November 2023
In
Proceedings of the 2023 TALE Conference on Teaching Assessment and Learning for Engineering
Reviewed by peer
true
Abstract
Given the pervasive reliance on technology in modern society, teaching Computational Thinking (CT) abilities is becoming increasingly relevant. These abilities, such as modeling and coding, have become crucial for a larger audience of students, not only those who wish to become software engineers or computer scientists. Recent advances in Large Language Models (LLMs), such as ChatGPT, provide powerful assistance to complete computational tasks, by simplifying code generation and debugging, and potentially enhancing interactive learning. However, it is not clear if these advances make CT tasks more accessible and inclusive for all students, or if they further contribute to a digital skills divide, favoring the top students. To address this gap, we have created and evaluated a novel learning scenario for transversal CT skills that leveraged LLMs as assistants. We conducted an exploratory field study during the spring semester of 2022, to assess the effectiveness and user experience of LLM-augmented learning. Our results indicate that the usage of ChatGPT as a learning assistant improves learning outcomes. Furthermore, contrary to our predictions, the usage of ChatGPT by students does not depend on prior CT capabilities and as such does not seem to exacerbate prior inequalities.
Event name
IEEE TALE 2023
Location
Auckland, New Zealand
Publication type
conference paper
Identifiers
https://libra.unine.ch/handle/20.500.14713/21812
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TALE_2023_Digital_Boosts.pdf

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