This systematic literature review (SLR) synthesizes research published between 2020 and 2025 to examine the utilization of Artificial Intelligence (AI) to explore and enhance Computational Thinking (CT) skills in primary school students. The review analyzed empirical and systematic review studies focusing on various AI methodologies, including Generative AI (e.g., ChatGPT), Explainable AI (XAI), adaptive learning systems, and interdisciplinary robotics platforms. Findings consistently demonstrate a positive, moderate-to-significant impact of AI-based interventions on core CT components such as problem decomposition and algorithmic thinking, alongside crucial 21st-century skills like Critical Thinking, Communication, Collaboration, and Creativity (4Cs). The most effective approaches are characterized by personalized and project-based learning. However, the review identifies significant implementation challenges, including the imperative need for substantial investment in equitable technological infrastructure, the scarcity of comprehensive teacher training programs focusing on both AI literacy and CT pedagogy, and the complexity of ethical issues surrounding data privacy and algorithmic bias. A critical research gap persists in the lack of long-term longitudinal studies and standardized, validated CT assessment tools for this age group. The conclusion advocates for policy actions to establish clear ethical guidelines, support scalable teacher professional development, and prioritize research into sustained impact and reliable assessment to ensure the responsible and equitable integration of AI for fostering computational thinkers.
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