THE RELATIONSHIP BETWEEN COLLEGE STUDENTS’ EMPLOYABILITY AND DIGITAL LITERACY: ATTITUDE TOWARDS AI AS A MEDIATING VARIABLE
DOI:
https://doi.org/10.18623/rvd.v23.6117Palabras clave:
Digital Literacy, AI Attitude, Employability, Chain Mediation, Discipline HeterogeneityResumen
Background: With the acceleration of digital transformation, enterprises are in urgent need of compound talents with both digital skills and AI application capabilities. Although existing studies have confirmed that digital literacy is a core dimension of employability, the mediating mechanism of AI attitude (cognition/emotion/behavior) between the two has not been clarified, especially the lack of empirical tests for college students. Objective: To reveal the chain mediating role of AI attitude between digital literacy and employability, and to explore the moderating effect of subject background (liberal arts/science), so as to provide a theoretical basis for talent training in colleges and universities. Methods: A questionnaire survey was conducted on 1024 undergraduates from 10 universities across the country using stratified cluster sampling. Based on the scale data of digital literacy (4 dimensions), AI attitude (3 dimensions) and employability (4 dimensions), the mediating path was tested by structural equation modeling (SEM) and Bootstrap method. Results: Digital literacy significantly and positively predicted employability (β=0.45, p<0.001), among which human-computer collaboration ability contributed the most (β=0.28); AI attitude played a partial mediating role (indirect effect value 0.18, accounting for 40%), showing a chain path of "cognition→emotion→behavior"; the contribution rate of the emotional attitude path of liberal arts students (58%) was significantly higher than that of science and engineering (32%), highlighting the heterogeneity of disciplines. Conclusion: For the first time, the three-dimensional mediating mechanism of AI attitude between digital literacy and employability was empirically verified, providing theoretical support for the design of "literacy-attitude-ability" integrated courses by discipline in colleges and universities (such as adding AI ethics debates to liberal arts and strengthening project practice in science and engineering), helping to break the bottleneck of talent training in digital transformation.
Citas
Aguilar SJ, Galperin H, Baek C, Gonzalez E. (2021). When does AI anxiety boost learning? A threshold model of emotional resistance and skill adoption. Computers & Education, 176, 104326. https://doi.org/10.1016/j.compedu.2021.104326
Bandura A. (2022). Social cognitive theory in the digital age: Toward a unified model of self-efficacy across virtual and real-world domains. Journal of Applied Psychology, 107(3), 487–504. https://doi.org/10.1037/apl0000992
Becker GS. (2021). Human capital: A theoretical and empirical analysis with special reference to education (4th ed.). University of Chicago Press.
Binkley M, Erstad O, Herman J. (2023). Defining twenty-first century skills: Updating digital literacies for workforce readiness. Assessment and Teaching of 21st Century Skills, 17(2), 45–68. https://doi.org/10.1007/s10798-023-09806-y
Carretero S, Vuorikari R, Punie Y. (2022). DigComp 2.3: The digital competence framework for citizens. Publications Office of the European Union. https://doi.org/10.2760/115300
Chen Y, Liu X. (2024). Digital literacy disparity between STEM and humanities students: Evidence from Chinese universities. Computers & Education, 198, 104782. https://doi.org/10.1016/j.compedu.2024.104782
Davis K, Lee S. (2024). Emotional pathways to AI adoption: How anxiety shapes technology use in college-to-work transition. Technology, Mind, and Behavior, 5(1), 112–130. https://doi.org/10.1037/tmb0000119
Hobfoll SE, Halbesleben J, Neveu JP, Westman M. (2023). Conservation of resources in the organizational context: The reality of resources and their consequences. Annual Review of Organizational Psychology and Organizational Behavior, 10, 103–128. https://doi.org/10.1146/annurev-orgpsych-120920-054515
Kim Y, Park J. (2025). Learning by creating: The impact of generative AI projects on employability development. Computers in Human Behavior, 158, 107823. https://doi.org/10.1016/j.chb.2025.107823
McKinsey Global Institute. (2024). Generative AI and the future of work in America. McKinsey & Company.
OECD. (2023). Digital skills for the next generation: Global assessment framework. OECD Publishing. https://doi.org/10.1787/9e5e8b2d-en
Taherdoost H. (2020). Critical success factors and role of artificial intelligence in digital transformation. Journal of Digital Technologies, 1(2), 1–21. https://doi.org/10.33002/jdt00100201
Wu J, Huang L, Zhao Q. (2023). Mediating role of AI attitudes in digital literacy-employment linkage: A meta-analytic review. Journal of Vocational Behavior, 145, 103901. https://doi.org/10.1016/j.jvb.2023.103901
Zhang L, Li M, Sun H. (2024). Digital literacy disparities in Chinese universities: Evidence from a nationwide survey. Higher Education, 87(4), 789–815. https://doi.org/10.1007/s10734-023-01140-7
Zhang R, Li M. (2023). Rethinking the digital competence-employment relationship: The neglected role of emotional resistance. Technological Forecasting and Social Change, 194, 122701. https://doi.org/10.1016/j.techfore.2023.122701
Descargas
Publicado
Cómo citar
Número
Sección
Licencia
I (we) submit this article which is original and unpublished, of my (our) own authorship, to the evaluation of the Veredas do Direito Journal, and agree that the related copyrights will become exclusive property of the Journal, being prohibited any partial or total copy in any other part or other printed or online communication vehicle dissociated from the Veredas do Direito Journal, without the necessary and prior authorization that should be requested in writing to Editor in Chief. I (we) also declare that there is no conflict of interest between the articles theme, the author (s) and enterprises, institutions or individuals.
I (we) recognize that the Veredas do Direito Journal is licensed under a CREATIVE COMMONS LICENSE.
Licença Creative Commons Attribution 3.0


