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ChatGPT in education: a discourse analysis of worries and concerns on social media

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Abstract

The rapid advancements in generative AI models present new opportunities in the education sector. However, it is imperative to acknowledge and address the potential risks and concerns that may arise with their use. We analyzed Twitter data to identify critical concerns related to the use of ChatGPT in education. We employed BERT-based topic modeling to conduct a discourse analysis and social network analysis to identify influential users in the conversation. While Twitter users generally expressed a positive attitude toward using ChatGPT, their concerns converged into five categories: academic integrity, impact on learning outcomes and skill development, limitation of capabilities, policy and social concerns, and workforce challenges. We also found that users from the tech, education, and media fields were often implicated in the conversation, while education and tech individual users led the discussion of concerns. Based on these findings, the study provides several implications for policymakers, tech companies and individuals, educators, and media agencies. In summary, our study underscores the importance of responsible and ethical use of AI in education and highlights the need for collaboration among stakeholders to regulate AI policy.

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Data Availability

The dataset and materials supporting this study are available from the corresponding author upon reasonable request. It should be noted that restrictions apply to the availability of tweet data due to the policy from Twitter Inc. Tweet data showing user profiles or text content is not allowed to share publicly, but the tweet ids and user ids are available from the corresponding author.

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Acknowledgements

This study is based upon work supported by the National Science Foundation under grant no. 1928434.

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Authors and Affiliations

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Contributions

Lingyao Li: Conceptualization, Methodology, Data Curation, Formal Analysis, Writing - Original Draft, Writing - Review & Editing. Zihui Ma: Methodology, Data Curation, Formal Analysis, Writing - Original Draft, Writing - Review & Editing. Lizhou Fan: Methodology, Data Curation, Writing - Original Draft, Writing - Review & Editing. Sanggyu Lee: Writing - Original Draft, Writing - Review & Editing. Huizi Yu: Writing - Original Draft, Writing - Review & Editing. Libby Hemphill: Conceptualization, Funding Acquisition, Writing - Review & Editing, Supervision, Resources.

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Correspondence to Lingyao Li.

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The authors declare that they have no known competing interests or personal relationships that could have appeared to influence the work reported in this paper.

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Li, L., Ma, Z., Fan, L. et al. ChatGPT in education: a discourse analysis of worries and concerns on social media. Educ Inf Technol (2023). https://doi.org/10.1007/s10639-023-12256-9

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  • DOI: https://doi.org/10.1007/s10639-023-12256-9

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