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AI literacy and school tier moderate educators’ ethical coping mechanisms through sedative and reverse Matthew effects
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  • Published: 16 May 2026

AI literacy and school tier moderate educators’ ethical coping mechanisms through sedative and reverse Matthew effects

  • Jun Wang  ORCID: orcid.org/0009-0009-3320-699X1,
  • Yang Hu2 &
  • Huilin Tang  ORCID: orcid.org/0009-0005-9339-83301,3 

Scientific Reports (2026) Cite this article

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We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors present which affect the content, and all legal disclaimers apply.

Subjects

  • Education
  • Information systems and information technology
  • Psychology
  • Science, technology and society

Abstract

The rapid penetration of artificial intelligence in education has triggered unprecedented ethical risk perception and response challenges for educators, but existing research lacks systematic exploration of deep ethical cognitive mechanisms. To address this, this study operationalizes macro level sociotechnical imaginaries into micro level psychological perceptions to construct and test a theoretical model that integrates dual-dimensional risk perception, AI Literacy, and situational factors. PLS-SEM analysis of 502 Chinese educators reveals that: both Inhibitory Ethical Risk and Promotional Professional Risk are significantly and positively associated with Defensive and Constructive Coping strategies simultaneously, challenging the traditional one dimensional risk hypothesis; AI Literacy significantly attenuated the positive association between Inhibitory Ethical Risk and Constructive Coping, supporting the hypothesis of the Literacy Sedative Effect; The strength of the positive association between Promotional Professional Risk and Constructive Coping in lower tier schools is 2.78 times stronger than that in first tier schools, providing empirical evidence for the Reverse Matthew Effect. This study proposes a dual-dimensional risk-coping framework, revealing the cognitive decoupling mechanism of AI Literacy and challenging the classical Matthew Effect, providing a new perspective for understanding individual behavior in disruptive technological change; at the same time, it also provides practical guidance for cultivating cautious and proactive adopters and developing differentiated AI Literacy training strategies.

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Acknowledgements

The author is grateful to his doctoral supervisors, Professor Martin Cortazzi and Professor Haomin Zhang, for their invaluable guidance and insightful comments on this manuscript.

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not for profit sectors.

Author information

Authors and Affiliations

  1. Faculty of Humanities and Social Sciences, City University of Macau, Macau SAR, China

    Jun Wang & Huilin Tang

  2. School of Foreign Languages and Foreign Trade, Guilin University of Aerospace Technology, Guilin, China

    Yang Hu

  3. Nanning Vocational and Technical University, Nanning, China

    Huilin Tang

Authors
  1. Jun Wang
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  2. Yang Hu
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  3. Huilin Tang
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Corresponding author

Correspondence to Huilin Tang.

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Competing interests

The authors declare no competing interests.

Ethics approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional research committee. The study (ref: FHSS250054) was reviewed and approved by the Faculty Ethics Committee, Faculty of Humanities and Social Sciences, City University of Macau, on 15 Aug 2025.

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Informed consent was obtained from all individual participants included in the study.

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Cite this article

Wang, J., Hu, Y. & Tang, H. AI literacy and school tier moderate educators’ ethical coping mechanisms through sedative and reverse Matthew effects. Sci Rep (2026). https://doi.org/10.1038/s41598-026-52376-z

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  • Received: 03 January 2026

  • Accepted: 05 May 2026

  • Published: 16 May 2026

  • DOI: https://doi.org/10.1038/s41598-026-52376-z

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Keywords

  • AI ethics
  • Dual-dimension risk–coping framework
  • AI literacy
  • Reverse Matthew Effect
  • Educators
  • PLS-SEM
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Digital transformation in education and the work environment

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