<![CDATA[This study aims to describe patterns, potentials-challenges, and formulate a synergy framework of active learning models and Generative Artificial Intelligence (GenAI) in science learning through a Systematic Literature Review (SLR) guided by PRISMA on empirical articles published between 2021–2025. A total of 12 articles that met the inclusion criteria were analyzed thematically. The review identified five main roles of GenAI, namely as a co-inquirer, co-reflector, co-designer/co-researcher, personal tutor, and cognitive scaffolding, which are integrated into various active learning models such as inquiry-based learning, problem-based learning, project-based learning, experiential learning, Collaborative Action Research, and self-directed learning. This integration contributes to the enhancement of conceptual understanding, higher-order thinking skills, reflection, and personalized learning, while also presenting challenges such as dependency, limitations of AI reasoning, bias, issues of work authenticity, and the need for pedagogical and ethical readiness. Based on these findings, a synergy framework was developed that emphasizes the integration of pedagogical dimensions, GenAI functions, ethical regulations, AI literacy, and data-driven evaluation loops as the foundation for the sustainable development of GenAI-assisted science learning practices.]]>
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