Preservice Chemistry Teachers' Views on the Use of Artificial Intelligence in the Classroom - Dimas Gilang Ramadhani; Sri Susilogati Sumarti; Harjono Harjono; Ella Kusumastuti (The Faculty of Teacher Training and Education (FKIP), Universitas Sebelas Maret, Indonesia, 2025)
As Artificial Intelligence (AI) becomes increasingly integrated into education, understanding how future educators perceive its use is essential. This study explores the perceptions of 150 preservice chemistry teachers in Indonesia regarding the integration of AI in chemistry education. Participants completed a validated 12-item Likert-scale survey covering four dimensions: Pedagogical Benefit, Technical Benefit, Risk to Student, and Risk to Teacher. The data were analyzed using descriptive statistics, correlation, regression, clustering, and Principal Component Analysis (PCA). Results indicate that participants perceived AI as highly beneficial, particularly for simplifying material preparation and supporting understanding of abstract concepts. However, concerns also emerged, especially around potential declines in student motivation, critical thinking, and the teachers’ readiness to use AI effectively. Correlation analysis revealed that benefit and risk perceptions were evaluated independently. Regression models identified “real-life connection” and “AI knowledge gap” as significant benefit and risk perception predictors. Cluster analysis grouped respondents into three profiles: Cautious Adopters, Enthusiastic Supporters, and Selective Optimists, each reflecting different levels of acceptance and concern. These findings underscore the need for differentiated teacher training programs that address technical competence and pedagogical reflection. Limitations include the reliance on self-report data and a single-country sample. The study emphasizes the importance of preparing educators to critically and effectively integrate AI into science instruction.