Pre-service teachers preparedness for AI-integrated education: An investigation from perceptions, capabilities, and teachers’ identity changes
Lihang Guan, Yue Zhang, Mingyue Gu
Abstract
Artificial intelligence (AI) has provided numerous learning benefits due to and beyond its personalization capabilities. AI significantly alters the interaction dynamics among students, teachers, and technology, necessitating the collaborative integration of AI in education instead of mere mechanical use. This study investigates pre-service teachers' perceptions and capabilities within the framework of social cognitive theory, focusing on their attitudes, intentions, self-efficacy, and AI literacy for effective AI integration. We discuss how these perceptions and capabilities help pre-service teachers prepare for the changing identities of being a teacher in AI-integrated education. Thematic analysis of qualitative interviews with a sample of 24 pre-service teachers suggests that (1) these pre-service teachers only use AI when warranted, (2) they need more understanding regarding AI fundamentals and ethics for AI's integration into education, and (3) they mechanically view AI as a tool to be utilized, rather than a dynamic collaborator in education. The findings indicate a need for more awareness of the possible changes in teachers' functions and roles in collaborative AI-integrated education, leading to specific teacher-training demands that aid them in success in AI-integrated education.