Artificial intelligence in science education: A systematic review of applications, impacts, and challenges

Abstract

This systematic review investigates the incorporation of artificial intelligence (AI) into science education by analyzing 17 studies published from 2020 to 2024. The paper examines the utilization of AI in different scientific fields and educational settings and assesses its influence on the methods of teaching and learning. The findings demonstrate a diverse range of AI applications, including chatbots, intelligent tutoring systems, and AI-enhanced textbooks. These apps serve many functions, from being educational tools to assisting in assessments. The investigation demonstrates the favorable impact of AI on student performance, motivation, and engagement in science education, particularly in the areas of personalized learning and the development of self-regulated learning skills. Additionally, issues related to technological infrastructure, obstacles to the sensitivity and reliability of AI systems, and ethical issues were also examined. The study emphasizes the importance of teacher preparation in achieving the successful integration of AI and expresses the necessity of comprehensive professional development. Potential areas for future research encompass investigating the enduring consequences of AI utilization, exploring its applicability in diverse educational settings, and fostering the growth of AI literacy. The study’s findings indicate that while AI has the potential to greatly improve science education, its successful application necessitates thoughtful evaluation of technological, pedagogical, ethical, and social elements to ensure fair and efficient integration across all educational levels.

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