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The Impact of Artificial Intelligence on Teaching and Learning – A Look into ChatGPT and the Future of Sustainable Assessments in Industrial Engineering

Article scientifique 2025 Anglais

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The advances in artificial intelligence (AI) have drawn more attention to its imminent influence on teaching and learning in higher education institutions. However, ChatGPT has the potential to generate incorrect information, can be biased and is characterised by ethical concerns, such as dishonest use by scholars can potentially lose employment due to the technology. It is against the backdrop of these challenges that this paper aimed to investigate the use of ChatGPT in educational settings and to illustrate AI’s potential benefits and challenges by the generation of a marking memorandum using ChatGPT. The IDEE theoretical framework was used for identifying the expected outcomes, determining the appropriate level of automation, ensuring that ethical issues are taken into consideration, and evaluating the effectiveness of ChatGPT in accomplishing the anticipated outcomes. A marking memorandum for two assessments was generated using ChatGPT and the AI software passed the Principles of Management module from a University of Technology in South Africa, but failed some sections of the Production Engineering module. The findings of the study revealed that ChatGPT can positively impact lecturers and students by establishing the originality of their ideas and building upon existing ideas more efficiently. It was recommended that the University of Technology establishes standards and policies that embrace AI and involve all staff in the adoption of AI technologies. This paper advocates the adoption of human-AI tool augmentation. Future research direction should encompass the social and ethical implications of deploying AI in engineering education. Keywords: Artificial Intelligence, Teaching and Learning, Sustainable Assessments, ChatGPT

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Dewa, M. (2025). The Impact of Artificial Intelligence on Teaching and Learning – A Look into ChatGPT and the Future of Sustainable Assessments in Industrial Engineering. https://doi.org/10.38159/ehass.20256915

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