AI Integration In STEM Learning In Inclusive Schools In Indonesia From Teachers Experiences And Perspectives

The integration of Artificial Intelligence (AI) in STEM learning within inclusive schools presents a significant opportunity to enhance personalized, adaptive, and equitable learning experiences for diverse learners. However, its successful implementation is constrained by complex pedagogical, technological, and human factors, where teacher perception plays a decisive role. This research aims to analyze the influence of AI integration and teachers’ professional experience on teacher perceptions regarding the use of AI in inclusive STEM education in Indonesia, a context characterized by heterogeneous student needs and varying levels of technological readiness. Employing a quantitative approach with an explanatory survey design, the study involved 1,000 teachers from inclusive primary and secondary schools selected through purposive sampling. Data were collected using a structured questionnaire based on a five-point Likert scale and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The measurement model evaluation confirmed strong psychometric properties, with all indicators meeting validity and reliability criteria (outer loading > 0.70, composite reliability > 0.90, and average variance extracted > 0.50). Structural model results demonstrated that AI integration (β = 0.399, p < 0.001) and teachers’ experience (β = 0.512, p < 0.001) significantly influenced teacher perceptions, with teachers’ experience emerging as the more dominant predictor. The model exhibited moderate explanatory power (R² = 0.449) and excellent goodness of fit (SRMR = 0.045). Furthermore, PLS-Predict analysis indicated high out-of-sample predictive capability, confirming the robustness of the proposed model. These findings underscore that teachers’ lived pedagogical experiences, rather than technological availability alone, are central in shaping constructive perceptions of AI use. Consequently, this study recommends a strategic policy shift from infrastructure-centered initiatives toward sustained, experiential, and inclusive professional development programs to empower teachers in leveraging AI for effective and equitable STEM learning in inclusive educational settings.