Promoting inclusive AI and technology in K-12 education: A review of context, instructional strategies, and learning outcomes

As artificial intelligence (AI) becomes increasingly integrated into K–12 education, concerns about equity and access have grown. This scoping review explores how inclusive AI curricula are designed, implemented, and evaluated in educational settings. Guided by three research questions, we analyzed 17 empirical studies published between 2013 and 2024, focusing on (1) the contexts and characteristics of inclusive AI curricula, (2) instructional strategies that promote broader participation, and (3) learning outcomes associated with these approaches. The findings reveal five key instructional principles (identity, technology, design, content development, and sense of belonging) alongside cognitive and affective learning outcomes such as improved content knowledge, confidence, and collaboration skills. However, the review also identified gaps in access, alignment with standards, and the consistent reporting of learning outcomes. This study offers a synthesized framework to guide educators and researchers in designing inclusive, equitable, and pedagogically sound AI-integrated learning experiences for diverse student populations.