Teacher Competencies for Integrating Artificial Intelligence into Science Education, with Particular Emphasis on Climate Change Education

The integration of artificial intelligence (AI) into science education raises pedagogical, epistemological, and ethical challenges, particularly in climate change education. Although scholarship on AI in education is expanding rapidly, evidence on the competencies teachers need to integrate AI effectively remains fragmented. This scoping review will map and characterize the international literature, with particular attention to its application in climate change education.The review will follow the Joanna Briggs Institute methodology, will be reported in accordance with PRISMA-ScR, and will document the search using PRISMA-S. A core set of multidisciplinary, educational, technological, and regional databases will be searched, supplemented by institutional grey literature and additional sources contingent on the pilot search. Two team members will independently conduct the selection process. The lead reviewer will extract the data, and the second reviewer will verify a structured 25% sample; critical variables will also be checked across all sources. A third reviewer will be consulted only when disagreements cannot be resolved.The synthesis will combine descriptive and qualitative analyses using deductive and inductive coding. Expected outputs include an evidence map, a competency taxonomy, and a matrix linking competencies, practices, training needs, and institutional conditions. Separate analyses will focus on Chemistry, climate change education, and Latin American contexts.