#1043: AI and ethics in the learning sciences: A literature review of the ISLS proceedings

The rapid rise of artificial intelligence (AI) has increased research at the intersection of AI and education. AI technologies are rapidly embedded in everyday practices, including educational contexts, which raises questions about their ethical implications. This study examined how the learning sciences field has researched AI ethics by systematically reviewing the ISLS Annual Meeting proceedings (1995-2025). From an initial dataset of 7652 papers, 872 AI-related papers were identified, of which 53 focused on ethics. Findings reveal a recent surge in AI and AI ethics research. An analysis of 53 ethics papers found a tendency to use qualitative methods, focusing on learners in K-12 and higher education. Notably, studies predominantly frame ethics through learning theories rather than established AI ethics frameworks, highlighting principles like bias, equity, and agency. We point to how the field’s research on AI ethics can inform policy and practice insights and to further research.