Optimizing Teaching Approaches in Adolescent Ethics Education via Generative Artificial Intelligence

Abstract

The utilization of generative artificial intelligence (GAI) tools like ChatGPT and DeepSeek is bringing about significant changes in educational practices and learning environments. This alteration underlines the necessity to look into how AI can enhance ethics education for the youth. This research reveals that the capabilities of GAI match up well with the requirements of youth ethics education in four principal ways: (1) crafting immersive, multi-sensory scenarios to boost student interest. By creating such scenarios, students can get more engaged and excited about learning. (2) Employing adaptive methods for precise interventions. This means being able to adjust the teaching approach according to each student's specific situation to make the intervention more effective. (3) Generating personalized content to customize the delivery of knowledge. Every student is different, and personalized content can better meet their individual learning needs. (4) Offering real-time analysis to improve teaching methods. With real-time analysis, teachers can quickly understand how students are doing and make timely adjustments. Based on these connections, this study puts forward a framework that incorporates GAI into crucial parts of the teaching process: integrating comprehensive learning data. This helps to have a more complete understanding of students' learning progress. Developing evidence-based strategies. So that teaching decisions are made with solid evidence. Creating differentiated content. To cater to the diverse needs of students. And assessing outcomes in multiple dimensions. This integration not only enhances the efficiency of moral education but also provides a scalable model for applying AI-driven teaching innovations across different subjects.