Role of AI-Driven Teaching in Enhancing Classroom Decision-Making Skills of Prospective Teachers

Abstract

The world of artificial intelligence (AI) is quickly changing the way education is conducted by endorsing data-driven teaching, individualized learning, and responsive teaching methods. The capability of AI-based teaching tools to empower pedagogical skills in teacher education means that would allow future teachers to process situations in the classroom and make quality teaching decisions. The current paper examined the idea of AI-driven instruction on development of classroom decision-making skills among future educators. The research design adopted was experimental research design including a pre-test and post-test control group. It was decided to select 120 future teachers who are undertaking a Bachelor of Education program and allocate them to experimental and control groups randomly. Experimental group has engaged in AI-based teaching practices, such as intelligent teaching simulations, automated teaching feedback systems, and AI-assisted lesson planning tools, and the control group was provided with traditional teacher training. The scales to collect data were a Classroom Decision-Making Skills Scale and were analyzed with the help of descriptive statistics and t-tests. The findings indicated that the prospective teacher decision-making skills in the classroom were greatly enhanced when exposed to AI-driven teaching than when they were on the traditional training group. The results indicate that AI-assisted learning for instruction can encourage reflective thinking, pedagogical reasoning and adaptive methods of instruction in pre-teachers. The research points out that AI-based teaching technologies should be included into the teacher education programs to equip future teachers to work in data-informed and technology-enhanced classrooms.