More Than Coding: A Mixed-Methods Systematic Review of the Multidimensional Landscape of Programming and AI in Primary Education

This dataset contains the structured data extracted for a systematic literature review examining the multidimensional impact of programming and artificial intelligence (AI) education in primary school (ages 6–12). The dataset includes detailed information on included studies, screening and eligibility criteria, and analytical coding across four dimensions: cognitive, social, socioemotional, and technical outcomes. Studies were identified through systematic searches in multiple academic databases and selected according to predefined inclusion and exclusion criteria. Data were extracted and synthesised using a mixed-methods approach to identify pedagogical practices, reported impacts, methodological patterns, and persistent research gaps. This dataset supports transparency and replicability and may be useful for researchers, educators, and policymakers interested in digital competence development, AI literacy, and curriculum integration in primary education.