Pedagogical partnerships with generative AI in higher education: how dual cognitive pathways paradoxically enable transformative learning.

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Title: Pedagogical partnerships with generative AI in higher education: how dual cognitive pathways paradoxically enable transformative learning.
Authors: Wang, Shaofeng1,2 (AUTHOR) vipwhsl@hotmail.com, Zhang, Hao3 (AUTHOR) zhanghao08042022@163.com
Source: International Journal of Educational Technology in Higher Education. 3/25/2026, Vol. 23 Issue 1, p1-30. 30p.
Subject Terms: *Transformative learning, *Generative artificial intelligence, *Cognitive psychology, *Partnerships in education, *Higher education, Human-artificial intelligence interaction
Abstract: The rapid integration of generative artificial intelligence (GenAI) into higher education has precipitated a critical tension between the pursuit of efficiency and the imperative for deep, transformative learning. While GenAI offers unprecedented speed in knowledge processing, it raises concerns that efficiency-driven motivations may erode the cognitive struggle essential for intellectual growth. This study investigates how Human-GenAI pedagogical partnerships influence transformative learning through the dual cognitive pathways of vigilance and offloading, moderated by efficiency orientation. Employing a rigorous mixed-methods design across three cultural contexts (China, Europe, and the United States, N = 912), we combine structural equation modeling, importance–performance map analysis (IPMA), fuzzy-set qualitative comparative analysis (fsQCA), and semi-structured interviews to unpack these complex dynamics. The findings reveal a counterintuitive paradox: pedagogical partnerships simultaneously activate cognitive vigilance (critical evaluation) and cognitive offloading (strategic delegation). Contrary to traditional assumptions that delegation diminishes learning depth, our results indicate that strategic cognitive offloading—when exceeding specific thresholds—liberates mental resources for higher-order reflection, thereby enhancing transformative learning experiences. Furthermore, efficiency orientation acts not as a barrier but as an amplifier, strengthening both vigilance and offloading behaviors through mechanisms of pragmatic risk management. These findings reconceptualize student-AI dynamics from a zero-sum resource competition to a synergistic collaboration, offering a nuanced framework for educators to integrate GenAI in ways that preserve human agency and foster quality education in the digital age. [ABSTRACT FROM AUTHOR]
Copyright of International Journal of Educational Technology in Higher Education is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Pedagogical partnerships with generative AI in higher education: how dual cognitive pathways paradoxically enable transformative learning.
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  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Educational+Technology+in+Higher+Education%22">International Journal of Educational Technology in Higher Education</searchLink>. 3/25/2026, Vol. 23 Issue 1, p1-30. 30p.
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  Data: *<searchLink fieldCode="DE" term="%22Transformative+learning%22">Transformative learning</searchLink><br />*<searchLink fieldCode="DE" term="%22Generative+artificial+intelligence%22">Generative artificial intelligence</searchLink><br />*<searchLink fieldCode="DE" term="%22Cognitive+psychology%22">Cognitive psychology</searchLink><br />*<searchLink fieldCode="DE" term="%22Partnerships+in+education%22">Partnerships in education</searchLink><br />*<searchLink fieldCode="DE" term="%22Higher+education%22">Higher education</searchLink><br /><searchLink fieldCode="DE" term="%22Human-artificial+intelligence+interaction%22">Human-artificial intelligence interaction</searchLink>
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  Data: The rapid integration of generative artificial intelligence (GenAI) into higher education has precipitated a critical tension between the pursuit of efficiency and the imperative for deep, transformative learning. While GenAI offers unprecedented speed in knowledge processing, it raises concerns that efficiency-driven motivations may erode the cognitive struggle essential for intellectual growth. This study investigates how Human-GenAI pedagogical partnerships influence transformative learning through the dual cognitive pathways of vigilance and offloading, moderated by efficiency orientation. Employing a rigorous mixed-methods design across three cultural contexts (China, Europe, and the United States, N = 912), we combine structural equation modeling, importance–performance map analysis (IPMA), fuzzy-set qualitative comparative analysis (fsQCA), and semi-structured interviews to unpack these complex dynamics. The findings reveal a counterintuitive paradox: pedagogical partnerships simultaneously activate cognitive vigilance (critical evaluation) and cognitive offloading (strategic delegation). Contrary to traditional assumptions that delegation diminishes learning depth, our results indicate that strategic cognitive offloading—when exceeding specific thresholds—liberates mental resources for higher-order reflection, thereby enhancing transformative learning experiences. Furthermore, efficiency orientation acts not as a barrier but as an amplifier, strengthening both vigilance and offloading behaviors through mechanisms of pragmatic risk management. These findings reconceptualize student-AI dynamics from a zero-sum resource competition to a synergistic collaboration, offering a nuanced framework for educators to integrate GenAI in ways that preserve human agency and foster quality education in the digital age. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of International Journal of Educational Technology in Higher Education is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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              Text: 3/25/2026
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