Scientific practices for understanding, applying and creating with artificial intelligence in K‐12 education: A scoping review

Abstract This scoping review examines the integration of artificial intelligence (AI) tools into scientific education practices in school settings. Following the PRISMA statement guidelines, a literature search was conducted in the Web of Science and Scopus databases, identifying 2892 articles published between 2020 and 2024. After applying the eligibility criteria, 75 primary studies with empirical data demonstrating the outcomes of school‐based scientific practices using AI tools were selected. The studies were coded based on the type of AI, the type of scientific practice, AI competencies, and other contextual and pedagogical aspects. The results indicate that the most frequently used tools by students are computer vision, natural language processing and data mining. Most studies focus on secondary education levels, combining strategies such as project‐based learning, scientific inquiry and the STEM approach. Although the evidence suggests that these tools enhance scientific skills like data interpretation and computational thinking, limitations were identified, including the use of low‐reliability or paid software and a lack of representation of ethical competencies. Finally, the review highlights the need to strengthen interdisciplinary collaboration and the design of curricular programmes that integrate AI through an ethical framework. The findings are discussed to provide guidance for pedagogy, public policies and future research. Context and implications Rationale for this study: This study was conducted to examine current evidence on how AI tools are being integrated into K‐12 scientific practices. Why the new findings matter: The findings presented are relevant for analysing current trends, identifying research gaps and exploring opportunities to update interdisciplinary pedagogical frameworks and digital literacy curriculum policies. Implications for educational practitioners, policy makers and researchers: For education practitioners, this study provides a planning model with practical examples for integrating AI into K‐12 scientific practices. For policy makers, it highlights the urgency of updating curricular frameworks and public education policies to ensure equitable access to trustworthy technologies, as well as initial and ongoing teacher training in AI, while fostering interdisciplinary collaboration, particularly between science and mathematics. For researchers, there is a clear need to expand empirical studies that examine scientific practices in virtual and hybrid modalities, in underexplored levels such as elementary education, and that take into account ethical competencies in the use of AI.