Preparing pre-service teachers for responsible generative AI use: Curriculum implications for ethics, privacy, and AI literacy
Abstract
This study investigated what pre-service teachers should learn about generative artificial intelligence (GenAI) by backtracking from anticipated classroom dilemmas to teacher-education design needs. Through qualitative interviews with 17 pre-service teachers at a Hong Kong university, the research explored perspectives on integrating AI into education, focusing on ethical concerns and pedagogical strategies. Grounded in the interpretivist paradigm, it revealed concerns about academic integrity, privacy and the challenge of maintaining essential human skills in a GenAI-driven educational environment. Although pre-service teachers recognised GenAI's potential to enhance teaching and learning, they expressed concern about over-reliance on GenAI tools, lack of data privacy and inequitable access. The participants emphasised the need for comprehensive AI literacy training in teacher-education programmes and strategies to promote critical thinking while leveraging AI's benefits. The research suggested that teacher-preparation programmes must address these challenges by incorporating technical knowledge, pedagogical strategies for AI integration and information about the ethical challenges posed by AI use. The findings contribute to teacher-education curriculum design by identifying how GenAI literacy can be embedded across coursework, assessment training, practicum preparation and ethical decision-making.
Identifier Metadata
| Identifier | 110.0939/CON.2026.00910 |
| Canonical | mdoi:110.0939/CON.2026.00910 |
| Resolver URL | https://mdoi.org/110.0939/CON.2026.00910 |
| Resource URL | Open resource |
| Document URL | Open document |
| Content Type | Article |
| Authors | Lucas Kohnke, Di Zou, Chun Lai, Mingyue Michelle Gu Keywords: |
| Year | 2026 |
| Depositor | Convergence Chronicles Organisation |
| Prefix | 110.0939 |
| Registered | Aug. 1, 2026 |
| Updated | Aug. 1, 2026 |
| Status | Active |
| Visibility | Public |
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