Integrating AI into Pedagogy: Exploring AI-Enhanced Approaches for Student-Centered Learning
Manisha Mittal, Abhishek Tripathi, Ravinder Kaur, Deena Nath Gupta, Kamal Sardana, Shivam Pandey
Abstract
New pedagogical frameworks and cutting-edge research techniques targeted at improving the learning process are being made possible by emerging artificial intelligence technology in education. These technologies include artificial intelligence-powered analytics tools, adaptive learning platforms, and intelligent tutoring systems. Give real-time feedback and individualized learning pathways. Frameworks for teaching are advancing to incorporate these artificial intelligence features, placing a focus on individualized, student-centered education strategies that take into account each person's unique demands and learning preferences. Methods of research in this area include a range of methodologies, such as longitudinal research, experimental studies, and large data analytics, to evaluate how well artificial intelligence interventions work and how they affect learning results. By Examining how artificial intelligence might change conventional educational models, scholars and Teachers are trying to make learning more dynamic, interesting, and successful. The study's ramifications include helping to improve teaching strategies and learning results by supporting the creation of professional development programs for artificial intelligence teachers. These five elements are combined in the suggested “Holistic Framework for Teaching and Learning in Emerging AI Courses” to give educators useful advice in the global context of AI education.