Abstract Artificial intelligence (AI) is rapidly being integrated into education amid growing enthusiasm and considerable uncertainty. While proponents highlight its potential for personalization and adaptive instruction, the empirical evidence for its educational benefits remains contested, and the conditions under which AI genuinely supports learning are not yet well understood. However, the rapid adoption of AI has outpaced the development of ethical standards, leaving educators and students with limited, abstract guidance for responsible use. This gap risks issues such as bias, privacy violations, and inequitable learning environments. To address this, we developed a comprehensive framework and actionable guidelines for ethical AI use in classrooms. A systematic literature review (2014–2023) identified key ethical principles and stakeholders, which were refined through three rounds of expert validation. Focus group interviews with teachers and students were then conducted to ensure clarity and practical relevance. The final framework comprises 11 ethical principles and six stakeholder groups, translated into 66 concrete guidelines tailored to classroom contexts. These guidelines support teachers and students in making informed decisions before, during, and after AI integration. By linking theoretical ethics with real-world practice, this study provides a structured foundation to promote safer, fairer, and more sustainable AI-enhanced education.
Go et al. (2026) studied this question.