Artificial Intelligence in Integrated Science Education: Opportunities, Challenges, and Future Directions

Abstract

Artificial Intelligence (AI) is increasingly transforming education by enabling personalized learning, intelligent assessment, virtual experimentation, and data-informed instructional support. This paper examines the opportunities, challenges, and future directions of AI integration in Integrated Science education. A structured literature review approach was adopted, using scholarly literature published between 2020 and 2026 and identified primarily through the Education Resources Information Center (ERIC) and the Directory of Open Access Journals (DOAJ), with Google Scholar used as a supplementary source. Relevant literature was screened using predefined eligibility criteria and synthesized thematically. The review indicates that AI can support personalized and adaptive learning, virtual laboratories, scientific inquiry, immediate feedback, intelligent assessment, and teacher decision-making. However, effective integration is constrained by inadequate digital infrastructure, limited teacher preparedness and AI literacy, data privacy and ethical concerns, unreliable AI-generated content, academic integrity issues, and learner overdependence on automated systems. The review further identifies limited interdisciplinary evidence specifically addressing AI in Integrated Science, particularly in developing and resource-constrained contexts. Future research should therefore emphasize human-centred AI integration, teacher professional development, context-sensitive and inclusive research, longitudinal empirical studies, and responsible and explainable AI. Overall, AI offers significant potential for strengthening Integrated Science education when implemented responsibly, equitably, and in alignment with curriculum objectives and human pedagogical judgement.