MDOI Convergence Chronicles 110.1129/CON.2026.01100
110.1129/CON.2026.01100
Article

AI literacy for ethical use of chatbot: Will students accept AI ethics?

Yusuke Kajiwara, Kouhei Kawabata 2024 Convergence Chronicles

Abstract

In AI literacy education, there are few examples of education based on AI ethical principles, and limited knowledge exists regarding curriculum design that incorporates AI ethical principles and its effects. Therefore, in this study, we propose a curriculum that teaches the ethical use of large language models (LLM) such as ChatGPT and verify its impact on educational effectiveness and technology acceptance among students aged 12 to 24. The validation results show that the proposed curriculum particularly contributes to the understanding of LLM concepts and their ethical use in decision support. We also demonstrate that experience using ChatGPT influences the level of understanding of ethical usage. Additionally, students aged 12 to 18 may actively adopt ChatGPT responses in decision support, and careful consideration is needed when using LLMs in the 12- to 18-year-old age group. Using technology acceptance model, AI ethical principles were also examined to determine technology acceptance, and it was found that usefulness, justice and fairness, privacy, and data protection directly impact attitudes toward ChatGPT. It has also become clear that students feel uneasy about using their personal information for learning ChatGPT, even if they have consented to the use of their personal information. This result suggests that AI developers and providers need to handle personal information carefully to foster a positive AI attitude.

Identifier Metadata

Identifier 110.1129/CON.2026.01100
Canonical mdoi:110.1129/CON.2026.01100
Resolver URL https://mdoi.org/110.1129/CON.2026.01100
Resource URL Open resource
Content Type Article
Authors Yusuke Kajiwara, Kouhei Kawabata
Year 2024
Depositor Convergence Chronicles Organisation
Prefix 110.1129
Registered Aug. 17, 2026
Updated Aug. 17, 2026
Status Active
Visibility Public

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mdoi:110.1129/CON.2026.01100

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