AI INTEGRATION IN MICROTEACHING: A TECHNOLOGICAL PEDAGOGICAL CONTENT KNOWLEDGE APPROACH TO IMPROVE THE QUALITY OF PROSPECTIVE MADRASAH IBTIDAIYAH TEACHERS - Nafia Wafiqni; Neli Rahmaniah; Tri Suryaningsih (JMIE (Journal of Madrasah Ibtidaiyah Education), 2026)
The advancement of Artificial Intelligence (AI) technology in education has created significant opportunities to enhance teaching quality, including in microteaching practices for prospective Madrasah Ibtidaiyah (MI) teachers. However, the implementation of AI in instructional practices still faces several challenges, such as limited technological literacy, gaps in curriculum integration, and difficulties in designing AI-based learning tools. This study aims to analyze the level of understanding of prospective MI teachers regarding AI technology in microteaching, examine AI integration through the Technological Pedagogical and Content Knowledge (TPACK) framework, identify implementation challenges, and evaluate the effectiveness of AI in improving teaching quality. This research employed a mixed methods approach with a sequential explanatory design. Quantitative data were collected through surveys and pretest–posttest instruments, while qualitative data were obtained through interviews and observations of AI-based microteaching practices. Data analysis included descriptive and inferential statistics to measure the effectiveness of AI, as well as thematic analysis to map implementation challenges. The findings indicate that students began to integrate AI across the stages of lesson planning, implementation, and evaluation, reflecting the initial development of TPACK components, particularly Technological Knowledge (TK) and Technological Pedagogical Knowledge (TPK). Identified challenges include low levels of technological literacy, limited pedagogical readiness, technical constraints, anxiety toward AI usage, and concerns regarding academic ethics. The Wilcoxon test results show a significant improvement in microteaching scores from 2.46 to 4.46 (p = 0.003), confirming the effectiveness of AI integration in enhancing the teaching quality of prospective MI teachers.