An Overview of Artificial Intelligence-Enhanced Teaching Methods

Abstract

This study dichotomizes AI's profound impact on traditional teaching, defines its role, and explores AI-enhanced methods. It critiques lecture-based and textbook learning for lacking personalization and prompt feedback. It details AI integration, emphasizing personalized learning, immersive tech like virtual and augmented reality, and key components: machine learning and natural language processing. Use cases demonstrate personalized learning paths and real-time feedback. The study further dives into AI-enhanced teaching: adaptive learning, intelligent tutoring, gamification, chatbots, and assessment automation, highlighting their transformative potential. It finally addresses challenges and ethics and projects AI's future contributions in research and curriculum development, urging adoption for future learners' benefit.