Integration of Artificial Intelligence to Support Inquiry-Based Science Teaching and Learning: A Systematic Literature Review

Abstract

The integration of artificial intelligence (AI) applications into science education can serve as an effective teaching aid to develop 21st-century skills among science students. The use of AI  in science education is driven by the need to enhance student engagement, personalised learning, and address persistent conceptual misunderstandings.This study aims to review the strategies employed by teachers in conducting AI-assisted teaching and learning in science education to provide authentic learning experiences while fostering skills such as creativity, collaboration, communication, and critical thinking among primary and secondary school students worldwide. This literature review follows the PRISMA model, analysing 20 articles to address the research questions. The selected articles focus on empirical studies published between 2019 and 2024, sourced from databases such as Scopus, Web of Science (WoS), and ERIC. The findings indicate that AI has the potential to enhance digital-assisted science learning without disregarding the concept of inquiry-based learning, which forms the foundation of modern science education.