<![CDATA[The pedagogical approach to science education at SDN 1 Labuhan Ratu, Lampung province, Indonesia, has traditionally been rooted in didactic methods and rote memorization, a paradigm that has proven insufficient for cultivating higher-order cognitive skills and inquiry-based learning. This instructional framework has been directly correlated with suboptimal levels of scientific literacy among a cohort of 33 fourth-grade students. To address this gap, this study's primary objective was to design, develop, and validate an innovative AI-integrated Inquiry Social Complexity (ISC) learning module intended to elevate students' scientific literacy. The research methodology was grounded in the ADDIE developmental model (Analysis, Design, Development, Implementation, and Evaluation) to ensure a systematic and rigorous creation process. The integration of artificial intelligence was instrumental in personalizing learning trajectories, scaffolding complex inquiry tasks, and delivering instantaneous, needs-based feedback, thereby enriching the core ISC framework. The module’s efficacy was substantiated through a comprehensive validation process, which confirmed its validity, practicality, and effectiveness. Empirical data from its implementation revealed a statistically significant enhancement in students’ scientific literacy, evidenced by an average N-gain score of 0.73, which signifies a high level of effectiveness. This research provides a valuable contribution to educational discourse by demonstrating the synergistic potential of AI and social inquiry within primary science education. The resultant module offers a transformative pedagogical model that cultivates critical, reflective, and collaborative competencies. Its broad adoption is advocated for in curriculum reform efforts, particularly within resource-constrained educational environments where innovative and adaptable instructional solutions are of paramount importance.]]>
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