Integrating Programming an AI in Primary Education: A Systematic Review of Opportunities, Challenges, and SDG 4 Contributions
Description
This dataset supports the systematic review reported in the manuscript entitled “Integrating Programming and AI in Primary Education: A Systematic Review of Opportunities, Challenges, and SDG 4 Contributions.” It comprises comprehensive tables that document the key characteristics of empirical studies and international policy reports published between 2021 and 2025, focused on the implementation of programming and artificial intelligence (AI) in primary education. The dataset includes details such as study titles, objectives, methodologies, sample characteristics, countries of implementation, thematic areas analyzed (including cognitive and socioemotional development, equity and inclusion, teacher training, curriculum integration, and digital safety/privacy), as well as explicit links to Sustainable Development Goal 4 (SDG 4) targets related to quality education, equity, and relevance. Data was extracted through a rigorous screening and coding process, using predefined inclusion and exclusion criteria, guided by PRISMA standards for systematic reviews. This structured approach ensures transparency and reproducibility. This dataset may be valuable for researchers conducting further meta-analyses or comparative studies on digital education, computational thinking, and AI in school settings. It also serves as a reference for policymakers and educators interested in understanding global trends and evidence-based practices to foster innovation and inclusion through digital education from the earliest years of schooling.
Files
Steps to reproduce
This dataset was created through a systematic review of the literature following established protocols to ensure rigor, transparency, and reproducibility. The process included the following steps: Definition of research questions and eligibility criteria: We established clear inclusion and exclusion criteria focusing on empirical studies and policy documents published between 2021 and 2025, related to programming and artificial intelligence (AI) in primary education and their contribution to Sustainable Development Goal 4 (SDG 4). Literature search: Comprehensive searches were conducted in multiple academic databases (e.g., Scopus, Web of Science, ERIC) and institutional repositories, using a combination of keywords related to programming, AI, primary education, and SDG 4. Screening and selection: Titles, abstracts, and full texts were screened independently by two reviewers according to the eligibility criteria, with discrepancies resolved through discussion. Data extraction: Relevant information was systematically extracted from each included study using a predefined data extraction form, covering study characteristics, methodologies, outcomes, and SDG 4-related contributions. Data coding and synthesis: Extracted data were coded according to thematic categories such as cognitive development, socioemotional skills, equity, teacher training, curriculum integration, and digital safety. The data were then synthesized narratively and in tabular form to identify patterns, gaps, and implications. Quality assurance: The review process adhered to PRISMA guidelines to ensure methodological rigor and reproducibility. No software specific to meta-analysis was used, but standard spreadsheet tools (Microsoft Excel) supported data organization and analysis.
Institutions
- ISCTE-Instituto Universitario de Lisboa Escola de Tecnologias e Arquitectura