Exploratory Study on Designing Elementary Moral Education Classes Using Artificial Intelligence (AI)

This study is an exploratory investigation into the instructional design of elementary moral education using artificial intelligence (AI), examining the potential of AI to enhance the effectiveness of moral education and its applicability in classroom settings. The study proposes three instructional models: the “AI-Based Problem Situation Exploration Model”, the “AI Motivation-Driven Practice Model”, and the “AI-Supported Reflective Enhancement Model”. First, the AI-Based Problem Situation Exploration Model utilizes AI to present realistic problems and simulations, fostering students’ critical thinking skills. Second, the Emotional Empathy Role-Play Model leverages AI to analyze emotional data, enhancing empathy through role-playing activities that allow students to experience others’ perspectives. Third, the AI Motivation-Driven Practice Model employs AI to spark students’ interest and connect motivation to practical activities, encouraging various application of moral values in real-life contexts. These models offer personalized learning experiences, safe virtual environments, and real-time feedback, which together overcome the theory-centric limitations of traditional moral education and emphasize practical outcomes. However, challenges such as the lack of empirical research and validation, technical limitations, ethical risks including data bias and privacy concerns, and the need for enhanced teacher competency are identified as key issues. To maximize the AI’s potential, the mediating role of teachers and their continued professional development are deemed essential. This study underscores that AI can function not merely as a tool but as a collaborator with teachers harmonizing with the goals of moral education, supporting teachers and elementary students in navigating the opportunities and challenges of the technological era.