Abstract
The influence of ChatGPT and similar models on education is being increasingly discussed. With the current level of enthusiasm among users, ChatGPT is envisioned as having great potential. As generative models are unpredictable in terms of producing biased, harmful, and unsafe content, we argue that they should be comprehensively tested for more vulnerable groups, such as children, to understand what role they can play and what training and supervision are necessary. Here, we present the results of a preliminary exploration aiming to understand whether ChatGPT can adapt to support children in completing information discovery tasks in the education context. We analyze ChatGPT responses to search prompts related to the 4th grade classroom curriculum using a variety of lenses (e.g., readability and language) to identify open challenges and limitations that must be addressed by interdisciplinary communities.
Original language | English |
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Title of host publication | UMAP 2023 - Adjunct Proceedings of the 31st ACM Conference on User Modeling, Adaptation and Personalization |
Publisher | Association for Computing Machinery |
Pages | 22-27 |
Number of pages | 6 |
ISBN (Electronic) | 9781450398916 |
DOIs | |
Publication status | Published - 26 Jun 2023 |
Event | 31st ACM Conference on User Modeling, Adaptation and Personalization, UMAP 2023 - Limassol, Cyprus Duration: 26 Jun 2023 → 30 Jun 2023 Conference number: 31 |
Conference
Conference | 31st ACM Conference on User Modeling, Adaptation and Personalization, UMAP 2023 |
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Abbreviated title | UMAP 2023 |
Country/Territory | Cyprus |
City | Limassol |
Period | 26/06/23 → 30/06/23 |
Keywords
- n/a OA procedure