GENERATIVE AI ADOPTION IN TEACHING PROCESSES: ANALYZING INSIGHTS FROM CHATGPT

Ioana Andreea Bogoslov and Eduard Stoica ()
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Ioana Andreea Bogoslov: Lucian Blaga University of Sibiu

Revista Economica, 2024, vol. 76, issue 3, 7-20

Abstract: The current reality shapes the landscape of modern society, where human activities are increasingly integrated with AI technologies. A relatively recent branch of artificial intelligence, generative AI, has shifted paradigms across various spheres of actions, particularly in recent years, with the emergence and development of tools such as ChatGPT. The educational field has not been immune to the influence of these technologies, which have been adopted almost naturally and seamlessly by the key stakeholders involved in teaching and learning processes. However, to harness the potential of generative AI effectively, maximizing its benefits while minimizing challenges or potential negative effects, a detailed exploration of this phenomenon becomes essential.Through a less conventional approach in existing research, the present study focuses on the adoption of generative AI by teachers in the teaching processes, employing the so-called thing ethnography method to interact with ChatGPT. The research findings emphasize potential strengths, weaknesses, opportunities, and threats associated with the adoption of ChatGPT as part of teachers practices, with the tool itself serving as both the central subject of the research and the interviewed subject. Moreover, through a detailed examination of interactions with the subject under study - namely, the chatbot being examined - certain limitations of the tool were observed. The insights gained from this analysis could help guide strategies and future directions for integrating generative AI into teaching activities and, more broadly, into educational processes as a whole.

Keywords: Artificial Intelligence; Education; Generative AI; Teaching (search for similar items in EconPapers)
JEL-codes: D8 I2 O3 (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:blg:reveco:v:76:y:2024:i:3:p:7-20

DOI: 10.56043/reveco-2024-0021

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