Dependensi Kognitif Mahasiswa terhadap Artificial Intelligence (AI) dan Risiko Pelemahan Higher-Order Thinking Skills (HOTS)

Fitri Fitri, Nurul Aslamiah, Nurrauhil Aulia

Abstract


The rapid development of Artificial Intelligence (AI) in higher education has significantly enhanced learning processes by providing greater accessibility and instructional support. However, its increasing use has also raised concerns regarding students' cognitive dependency, which may weaken Higher-Order Thinking Skills (HOTS). This study aims to synthesize empirical evidence on the relationship between cognitive dependency on AI and the potential decline of HOTS among university students. A Systematic Literature Review (SLR) approach was employed following the PRISMA 2020 guidelines. Data were collected from articles indexed in Scopus, DOAJ, Google Scholar, SciSpace, and Elicit, published between 2016 and 2026. The findings indicate that AI functions as a form of cognitive scaffolding that effectively supports learning when used appropriately. Nevertheless, excessive reliance on AI may promote cognitive offloading, thereby reducing students' engagement in analysis, evaluation, and problem-solving, which are fundamental components of HOTS. The review also identifies several research gaps, including the limited availability of longitudinal studies, insufficient integration of supporting variables, and the absence of comprehensive instruments for measuring cognitive dependency. These findings underscore the importance of developing pedagogical models and AI literacy frameworks that promote the critical, ethical, and responsible use of AI while strengthening students' higher-order thinking skills.

Keywords


Artificial Intelligence; Dependensi Kognitif; Higher Order Thinking Skills; Cognitive Offoloading; Systenatic Literature Review.

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References


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