Assessing future teachers’ readiness in an ai-driven classroom

The integration of Artificial Intelligence (AI) in education is rapidly advancing, offering personalized learning experiences and enhancing teacher effectiveness. However, there is a critical need to assess future teachers' readiness for AI-driven classrooms. This study aimed to determine the Future Teachers’ Readiness in an AI-Driven Classroom (ADC). Using a descriptive-correlational research design, and purposive sampling, data were collected from Teacher Education students. The researchers utilized an adapted research instrument based on the Meta AI Literacy Scale. The analysis involved utilizing descriptive statistics such as the mean and standard deviation, along with inferential statistics such as the Spearman rho-rank order correlation. Results indicated that future teachers demonstrated a strong grasp of AI ethics but showed lower readiness in using and applying AI tools and AI problem-solving. A moderate positive correlation was found between AI literacy and AI self-management. In conclusion, the study revealed that while future teachers displayed a solid understanding of AI ethics, there was a need for further development in utilizing AI tools and problem-solving skills. Recommendations included tailored training programs focusing on practical AI applications, problem-solving strategies, and building AI self-management skills to bridge identified gaps. By addressing these areas, teacher training programs could better prepare future educators to effectively leverage AI tools, ensuring a smooth transition to AI-Driven Classrooms (ADC) and enhancing the overall learning experience for students and teachers alike.