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Journal Paper Published

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Top-ranked U.S. and U.K.’s universities’ first responses to GenAI: key themes, emotions, and pedagogical implications for teaching and learning

Singh, R. G.*, & Ngai, C. S. B. (2024). Top-ranked U.S. and U.K.’s universities’ first responses to GenAI: key themes, emotions, and pedagogical implications for teaching and learning. Discover Education, 3(1), 115.
 
DOI:  https://doi.org/10.1007/s44217-024-00211-w

 

Abstract

The emergence of ChatGPT, a Generative AI program, has sparked discussions about its teaching and learning value, and concerns about academic integrity in higher education (HE). An extant review of the literature indicates that a scarcity of research exists on GenAI, specifically a synthesis of the official views, guidelines and articles of top-ranked universities on the use, limitations, challenges, and opportunities brought by ChatGPT in the early phase when ChatGPT was released in 2022 until early May 2023, which can offer insights into the concerns and recommendations for educators. Using the corpus assisted discourse analysis approach, this study identified the key themes and emotions elicited by evaluations of the ChatGPT situation from a self-built corpus containing 151 articles from 47 top-ranked U.S. universities and 34 U.K. ones. Our findings indicated three prominent themes discussed on official websites, including ChatGPT as a text and content generator, use of ChatGPT in teaching and learning, and potential implications and opportunities of using ChatGPT in HE. Further examination revealed that bias, concern, worry, threat, fear, and trust were the prevailing emotions relating to ChatGPT. Illustrated with examples collected from our corpus, this paper offers an in-depth discussion of universities’ first responses to the use of ChatGPT. The insights gained have some pedagogical implications for academics, researchers and educators and may inform policy and practice in HE on the use of GenAI.
 

Keywords

ChatGPT, Corpus assisted discourse analysis, Emotion analysis, Generative AI, Higher education, Theme analysis

 

 

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