<![CDATA[The growing adoption of artificial intelligence (AI) in education has created new opportunities to strengthen scientific literacy, yet most AI-supported approaches function as instructional tools rather than integrated pedagogical models. This study investigated the preliminary effectiveness of Deep-AI, an AI-integrated deep learning model designed to enhance Generation Z students’ scientific literacy through adaptive learning, scientific inquiry, and reflective learning processes. A quasi-experimental pretest–posttest design with replication across two cohorts was conducted involving 100 undergraduate students. Both cohorts participated in the same Deep-AI learning intervention, and scientific literacy was assessed before and after implementation. The findings demonstrated consistent improvements in students’ scientific literacy across both cohorts, with moderate learning gains and strong educational effects. Students also reported highly positive learning experiences, indicating that the model successfully promoted engagement, conceptual understanding, and evidence-based reasoning. Comparable outcomes between the two cohorts further suggest the consistency and robustness of the model across different learning groups. This study contributes an AI-integrated instructional framework that positions artificial intelligence as a cognitive learning partner, providing a promising pedagogical approach for fostering scientific literacy and higher-order thinking in higher education within the Smart Society 5.0 era.]]>
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