What question did this study set out to answer?

This review aims to examine how generative AI integrates into higher education, focusing on its influence on cognitive development and pedagogy.

April 12, 2026Open Access

Double Intelligence: Repositioning Human Intelligence in the Age of Generative AI for Teaching, Learning, and Assessment Across Diverse Higher Education Contexts – A Narrative Review

Key Points

This review aims to examine how generative AI integrates into higher education, focusing on its influence on cognitive development and pedagogy.
Conducted a narrative review of literature from 2020 to 2025.
Systematic search across databases like Scopus and Google Scholar using structured keywords.
Thematic synthesis of selected studies to analyze cognitive, pedagogical, and ethical dimensions.
Ensured methodological rigour through triangulation and reflexive researcher considerations.
AI shifts the focus of human intelligence from knowledge retention to orchestration.
Enhances metacognitive regulation and supports hybrid learning paradigms.
Identified challenges include cognitive offloading and inequitable access to AI tools.
Concludes that AI can strengthen intellectual development when used in scaffolded and ethically guided environments.

Abstract

This narrative review critically examines the integration of generative artificial intelligence (AI) in higher education, addressing a knowledge gap in understanding how AI-mediated learning aligns with sociocultural perspectives of cognitive development. Despite widespread adoption of tools such as ChatGPT, existing literature largely focuses on technological capabilities or individual cognitive outcomes, overlooking the interplay between human intelligence, pedagogical practices, and collaborative knowledge construction. Anchored in Vygotsky’s Sociocultural Theory, the review explores AI as a mediational tool shaping cognitive reconfiguration, hybrid intelligence, pedagogical transformation, assessment innovation, and ethical repositioning in diverse higher education contexts. A systematic search across Scopus, Web of Science, ERIC, and Google Scholar, covering 2020–2025, employed structured keywords related to AI, higher education, and cognitive development. Selected studies underwent thematic synthesis, examining cognitive, pedagogical, assessment, ethical, and epistemological dimensions, with rigour ensured through cross-validation, triangulation, and reflexive consideration of researcher positionality. Findings indicate that AI reorients human intelligence from knowledge retention to orchestration, enhances metacognitive regulation, and supports hybrid learning, while challenges include cognitive offloading, inequitable access, and unstructured reliance that may undermine deep engagement. The review concludes that AI strengthens intellectual development when embedded in scaffolded, ethically guided, and collaborative environments. Policy implications emphasise equitable access, AI literacy, and process-oriented assessment, whereas pedagogical practice should prioritise cognitive coaching and reflective engagement. The study contributes to the body of knowledge by synthesising theoretical and empirical insights to guide AI-mediated higher education that preserves intellectual agency, fosters responsible AI adoption, and advances context-sensitive learning strategies.

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