https://so03.tci-thaijo.org/index.php/saketreview/issue/feed 2026-02-17T19:58:54+07:00 พระอธิการนัฐวุฒิ สิริจนฺโท,ดร. roietjournal@gmail.com Open Journal Systems <p>The Journal of Graduate Saket Review is an academic journal published 3 issues per year 1st issue Jan-uary-April, 2nd issue May-August, 3rd issue September-Decembe (2024 onwards). It aims to promote research and disseminate academic and research articles for researchers, academicians, lecturers and graduate students. The Journal focuses on Buddhism, Liberal Arts Political Science and Public Administration and Interdisciplinary of Humanities and Social Sciences</p> https://so03.tci-thaijo.org/index.php/saketreview/article/view/296339 2026-02-13T06:23:57+07:00 Supaphorn Akkapin supaphorn.a@mail.rmutk.ac.th Boonchuay Srithammasak supaphorn.a@mail.rmutk.ac.th Bingquan Wang supaphorn.a@mail.rmutk.ac.th Zhenyun Peng supaphorn.a@mail.rmutk.ac.th Jingxi Wang supaphorn.a@mail.rmutk.ac.th

<p> </p> <p>The rapid integration of generative artificial intelligence (generative AI) into higher education marks a structural epistemic shift rather than the mere introduction of another digital tool. Systems such as ChatGPT now take over parts of the thinking and writing once undertaken by students and academics, compelling universities to reconsider which forms of intellectual capability they must protect and cultivate over the long term. Meta-analyses and systematic reviews indicate that when instructors intentionally design learning activities and assessments, generative AI can enhance student achievement, higher-order thinking, and motivation to learn, while recent work such as the Massachusetts Institute of Technology (MIT)’s Your Brain on ChatGPT project warns that when students offload too much deep thinking to AI, they may accumulate “cognitive debt” that undermines authorship, stylistic distinctiveness, and the ability to remember and defend their own arguments.</p> <p> This article argues that the appropriate response is neither to ban AI nor to embrace it uncritically, but to design AI-augmented liberal education with a clear underlying architecture, developing a four-layer framework that identifies (1) foundational literacies, (2) disciplinary knowledge and practice, (3) critical AI literacy, and (4) ethical, civic, and epistemic reflexivity as domains that must be strengthened rather than replaced by automation. The framework is translated into conceptual diagrams, design tables, and an example of a human–AI co-learning loop for academic writing, linking each layer to concrete decisions about course design, assessment tasks, and grading criteria, and offering guidance for instructors and curriculum leaders on designing AI-resilient assessments, setting course-level AI policies, and organizing faculty development so that graduates can learn to think with, against, and beyond machines rather than being quietly displaced by them.</p>

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