<![CDATA[The development of generative Artificial Intelligence (AI) has significantly transformed learning dynamics in Information Technology Education (ITE), particularly in programming activities and computational problem-solving. Although numerous studies highlight the efficiency and convenience offered by this technology, analyses concerning the transformation of students’ cognitive processes especially in relation to critical thinking remain relatively fragmented. This study aims to systematically synthesize scholarly findings on the impact of integrating generative AI into the cognitive structure of learning in ITE through a systematic literature review approach. Data sources were obtained from international and national databases covering the period 2018–2026 using structured selection criteria. The synthesis results indicate that generative AI functions as an accelerator at lower cognitive levels by reducing technical load; however, transformation at higher-order levels analysis, evaluation, and creation appears conditional. When employed as a reflective tool, AI can enhance self-regulation and critical thinking skills. Conversely, substitutive use may shift learning from a constructive process toward a merely verificative one, thereby diminishing the depth of cognitive engagement. The novelty of this study lies in integrating perspectives from cognitive taxonomy, cognitive load theory, and metacognition to comprehensively explain patterns of cognitive transformation within the context of Information Technology Education in Indonesia. These findings offer important implications for the design of AI-supported learning environments that are adaptive while remaining oriented toward strengthening higher-order thinking competencies.]]>
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