Artificial Intelligence Literacy as a Catalyst for Overcoming Student Resistance to Digital Transformation in Higher Education

This study investigates how students’ resistance to change and AI literacy influence their attitudes toward artificial intelligence (AI) in higher education. With the aim of contributing to overcoming psychological barriers encountered in the digital transformation process, this study examines the mediating role of AI literacy in the negative effect of resistance to change on students’ attitudes toward AI. Using a quantitative, cross-sectional research design, data were collected from 564 university students in Türkiye through a structured questionnaire. To test the proposed hypotheses, the research utilized Structural Equation Modeling (SEM) alongside Hayes’ PROCESS Model 4 for mediation analysis. The findings reveal that increased resistance to change significantly and negatively impacts both AI literacy and attitudes toward AI. Furthermore, AI literacy has a positive effect on students’ attitudes toward AI and partially mediates the relationship between resistance to change and attitude. An original contribution is offered by empirically establishing an integrated RTC→AIL→AIA pathway and by specifying AIL as a developable competence that converts resistance-related ambiguity into perceived control, thereby clarifying how attitudes are improved through knowledge-based mechanisms. The results show that knowledge-based trust and cognitive preparation significantly contribute to the strengthening of positive attitudes towards AI. This research contributes to the literature by presenting an integrated conceptual framework linking resistance to change, AI literacy, and attitude toward AI. In practical terms, design-addressable implications are specified for educational programming, indicating that embedding ethics–privacy–bias content and explainability-oriented feedback can translate the mediation mechanism into routine practice and help reduce resistance-related frictions. It emphasizes that addressing cognitive competencies is essential in promoting sustainable learning behaviors in digitally transforming educational environments.

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Publication Details

Journal
Üniversite Araştırmaları Dergisi
Published
2025-12-24
DOI
https://doi.org/10.32329/uad.1743237
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
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article

Artificial Intelligence Literacy as a Catalyst for Overcoming Student Resistance to Digital Transformation in Higher Education

Cemil Gündüz, Üzeyir Fidan, Ali Erbey
Üniversite Araştırmaları Dergisi
Ethics and Social Impacts of AI
article

Artificial Intelligence Literacy as a Catalyst for Overcoming Student Resistance to Digital Transformation in Higher Education

Cemil Gündüz, Üzeyir Fidan, Ali Erbey
article en

Abstract

This study investigates how students’ resistance to change and AI literacy influence their attitudes toward artificial intelligence (AI) in higher education. With the aim of contributing to overcoming psychological barriers encountered in the digital transformation process, this study examines the mediating role of AI literacy in the negative effect of resistance to change on students’ attitudes toward AI. Using a quantitative, cross-sectional research design, data were collected from 564 university students in Türkiye through a structured questionnaire. To test the proposed hypotheses, the research utilized Structural Equation Modeling (SEM) alongside Hayes’ PROCESS Model 4 for mediation analysis. The findings reveal that increased resistance to change significantly and negatively impacts both AI literacy and attitudes toward AI. Furthermore, AI literacy has a positive effect on students’ attitudes toward AI and partially mediates the relationship between resistance to change and attitude. An original contribution is offered by empirically establishing an integrated RTC→AIL→AIA pathway and by specifying AIL as a developable competence that converts resistance-related ambiguity into perceived control, thereby clarifying how attitudes are improved through knowledge-based mechanisms. The results show that knowledge-based trust and cognitive preparation significantly contribute to the strengthening of positive attitudes towards AI. This research contributes to the literature by presenting an integrated conceptual framework linking resistance to change, AI literacy, and attitude toward AI. In practical terms, design-addressable implications are specified for educational programming, indicating that embedding ethics–privacy–bias content and explainability-oriented feedback can translate the mediation mechanism into routine practice and help reduce resistance-related frictions. It emphasizes that addressing cognitive competencies is essential in promoting sustainable learning behaviors in digitally transforming educational environments.

Üniversite Araştırmaları DergisiVol. 8(4)
Usak University (TR)
Quality Education
Openalex Percentile: Top 24%
Ethics and Social Impacts of AI
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