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Rewriting the Curriculum: A Systematic Review of Generative AI-Driven Pedagogical Change and Emerging Systems of Learning in Higher Education

● high · 2026-08-16 · generative-ai, higher-ed, curriculum-design, instructional-design, pedagogical-innovation, meta-analysis-systematic-review

Synthesis: Sabani et al. (2026) examine how Generative AI is driving a more profound transformation of Higher Ed pedagogy and curriculum beyond Writing Education support, proposing an AI-Augmented Learning System framework that treats GenAI as a catalyst for curricular reconfiguration. Using a triangulated mixed-methods design — a scoping review, bibliometric mapping (VOSviewer, n=209), a systematic review of 36 peer-reviewed articles (2023–2025), and ten interviews with academic leaders across five institutions in Australia and Indonesia — they identify five interrelated system shifts: from static to dynamic AI-integrated curricula, teacher-centred to AI-augmented facilitation, knowledge transmission to capability development, local experimentation to institutional Governance, and fragmented to ecosystemic integration. Interpreted through constructivism, connectivism, TPACK, the SAMR model and constructive alignment, the framework is offered as an analytical heuristic rather than a prescriptive blueprint.

Key Findings

Five system shifts. GenAI reconfigures higher education along five interrelated axes: (1) static curricula → dynamic AI-integrated design; (2) teacher-centred delivery → AI-augmented facilitation; (3) knowledge transmission → capability development; (4) local experimentation → institutional governance; and (5) fragmented implementations → ecosystemic integration. These shifts move GenAI from a supplementary writing/tutoring tool to a structural force reshaping curriculum and the "foundational structures of learning itself."

AI-Augmented Learning System framework. The framework conceptualises GenAI not merely as an instructional tool but as a catalyst for curricular and pedagogical reconfiguration, giving structure to the otherwise diffuse discourse on Generative AI in Higher Ed. It positions learners as more active participants — co-designers of learning within AI-integrated environments — and reframes the institution's role from running isolated experiments to governing an integrated system.

Mixed-methods triangulation. The evidence base combines a scoping review, VOSviewer bibliometric mapping of 209 records, a PRISMA-style systematic review of 36 peer-reviewed articles (2023–2025), and ten semi-structured interviews with academic leaders and educators at five institutions across Australia and Indonesia.

Theoretical anchoring. The five shifts are mapped onto established lenses — constructivism, connectivism, TPACK, SAMR, and constructive alignment — clarifying the pedagogical mechanisms through which GenAI reshapes curriculum and teaching, with implications for Learning Analytics and educational innovation.

Caveat. Given the bounded empirical base, the authors position the framework as a starting point for institutional dialogue pending further empirical validation across diverse contexts.

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Citation

Sabani, A., Farah, M. H., Catyanadika, P. E., Dewi, D. R. S., & Tawani, V. (2026). Rewriting the Curriculum: A Systematic Review of Generative AI-Driven Pedagogical Change and Emerging Systems of Learning in Higher Education. Computers and Education: Artificial Intelligence, 100667. https://doi.org/10.1016/j.caeai.2026.100667