From Tool-Centric to Cognitive Collaboration: Reconfiguring Generative AI in Education from a Cognitive Deficits Perspective

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Publication Details

Journal
Education Journal
Published
2026-09-18
DOI
https://doi.org/10.11648/j.edu.20261505.12
Primary Topic
Artificial Intelligence in Education
Type
article
Field-Weighted Citation Impact
0.00
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article

From Tool-Centric to Cognitive Collaboration: Reconfiguring Generative AI in Education from a Cognitive Deficits Perspective

Kaidan Deng, Yantian Xu
Education Journal
Artificial Intelligence in Education
article

From Tool-Centric to Cognitive Collaboration: Reconfiguring Generative AI in Education from a Cognitive Deficits Perspective

Kaidan Deng, Yantian Xu
article en

Abstract

Generative Artificial Intelligence (AIGC) is driving widespread transformation in the field of education. However, current applications largely remain at the superficial level of "mechanical adoption of technology," failing to address the core educational objectives of cultivating students' deeper cognitive abilities, such as critical thinking and metacognition. This phenomenon reveals that the educational application of AIGC is facing a profound predicament, rooted in the field's widespread neglect of AIGC's fundamental cognitive deficiencies in causal reasoning, contextual understanding, and symbolic grounding, which has led to a structural contradiction between technological application and educational objectives. To resolve this predicament, this study combines critical analysis with theoretical construction. It first systematically analyzes the educational implications of AIGC's cognitive deficiencies and then proposes a systematic path for reconfiguration. At the theoretical level, this study constructs a "Human-Centered Three-Tiered Collaborative Cognitive Development Framework for AIGC." Through the interplay of metacognitive design, cognitive collaboration, and continuous reflection, it redefines AIGC as "a controlled collaborator under the guidance of educational objectives." At the technical level, addressing the three major cognitive deficiencies, this study proposes a dual-track evolutionary approach that combines "innovations in educational methodology" with "advancements in algorithmic frameworks" aiming to drive AIGC's evolution toward an "educational world model" that embodies educational logic. This study aims to transcend the limitations of instrumental rationality and provide a systematic solution—combining theoretical foresight with practical guidance—for constructing a new paradigm of intelligent education that prioritizes human development and leverages technology appropriately. Future research will validate the effectiveness of this approach through practical application and continue to focus on the dynamic adaptation between technological evolution and the essence of education.

Education JournalVol. 15(5)
Nanjing Normal University (CN)
Quality Education
Openalex Percentile: Top 4%
Artificial Intelligence in Education
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