The rapid rise of generative artificial intelligence (GenAI) tools such as ChatGPT is transforming the landscape of higher education. Beyond their immediate use in writing support and tutoring, these tools are driving a more profound transformation in pedagogy, curriculum design, and the foundational structures of learning itself. Drawing on a triangulated mixed-methods design, this study integrates a scoping review, bibliometric mapping (VOSviewer, n=209 records), a systematic literature review of 36 peer-reviewed articles (2023–2025), and ten semi-structured interviews with academic leaders and educators across five institutions in Australia and Indonesia. The central aim of the study is to develop and propose an AI-Augmented Learning System framework that conceptualises GenAI not merely as an instructional tool but as a catalyst for curricular and pedagogical reconfiguration. Thematic patterns reveal five interrelated system shifts: from static curricula to dynamic AI-integrated design; from teacher-centred delivery to AI-augmented facilitation; from knowledge transmission to capability development; from local experimentation to institutional governance; and from fragmented implementations to ecosystemic integration. These shifts are interpreted through established educational theories including constructivism, connectivism, TPACK, the SAMR model, and constructive alignment to clarify the pedagogical mechanisms through which GenAI is reshaping curriculum and teaching, and to surface implications for learning analytics and educational innovation. Given the bounded empirical base, the proposed framework is offered as an analytical heuristic and starting point for institutional dialogue rather than a prescriptive blueprint, providing a foundation for further empirical validation across diverse higher education contexts.
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