Personalised learning and artificial intelligence in science education: current state and future perspectives

Abstract

This paper presents a comprehensive examination of the integration of artificial intelligence (AI) in science education and its impact on personalised learning. The research explores current applications, challenges, and future perspectives of AI technologies in educational settings. Through a systematic literature review, we identify the advantages of AI, such as enhanced individualised instruction, data-informed insights, and increased student engagement. The study combines quantitative and qualitative analyses, case studies, expert interviews, and technology assessments to offer a multidimensional understanding of AI's role in personalising science education. Despite the potential benefits, the research highlights barriers, including financial costs, infrastructure requirements, data privacy, and the need for teacher training. The future of AI in education suggests a trajectory towards advanced personalisation capabilities through adaptable learning systems, virtual tutors, and immersive learning environments. We underscore the importance of addressing the identified challenges to fully realise the transformative power of AI in science education. The findings illustrate that, with thoughtful implementation, AI holds promise for tailoring science learning experiences, making them more effective, inclusive, and engaging for students of varied needs and abilities.