The Influence of AI Literacy on Teacher Performance and Critical Thinking: A Case Study in Rural Schools, Indonesia

Yosi Oktavia, Yunia Wardi, Eka Fauzihardani, Rosyeni Rasyid

Abstract


This study aims to examine the effect of artificial intelligence (AI) literacy on teacher performance, with critical thinking as a mediating factor, among private Vocational High School (SMK) teachers in rural Sukabumi Regency, Indonesia. AI literacy is regarded as an essential skill for navigating technological advances in education, yet its effectiveness in enhancing teacher performance requires reinforcement through cognitive competencies such as critical thinking. Employing a quantitative approach with a census of 82 teachers and analyzed using Structural Equation Modeling Partial Least Squares (SEM-PLS), the results indicate that AI literacy does not have a significant direct effect on teacher performance but does have a positive impact on critical thinking. These findings underscore that technological proficiency alone is insufficient without deep critical thinking skills in its application. This study offers practical implications for designing teacher training programs that integrate both technological and cognitive-reflective components to improve educational quality in rural areas.

Keywords


AI Literacy; Critical Thinking; Teacher Performance; Rural Education; Vocational High School

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References


J. Ahn and A. J. Bowers, “Do teacher beliefs mediate leadership and teacher behaviors? Testing teacher self-efficacy’s mediation role between leadership for learning and teacher outcomes,” Journal of Educational Administration, vol. 62, no. 2, pp. 197–222, 2024, doi: 10.1108/JEA-12-2022-0227.

H. Du, Y. Sun, H. Jiang, A. Y. M. A. Islam, and X. Gu, “Exploring the effects of AI literacy in teacher learning: an empirical study,” Humanit Soc Sci Commun, vol. 11, no. 1, 2024, doi: 10.1057/s41599-024-03101-6.

H.-L. W. Pan, “Learner-Centered Teaching Catalyzed by Teacher Learning Communities: The Mediating Role of Teacher Self-Efficacy and Collaborative Professional Learning,” Sustainability, vol. 15, no. 6, p. 4850, 2023, doi: 10.3390/su15064850.

N. Yao and Q. Wang, “Factors influencing pre-service special education teachers’ intention toward AI in education: Digital literacy, teacher self-efficacy, perceived ease of use, and perceived usefulness,” Heliyon, vol. 10, no. 14, p. e34894, 2024, doi: 10.1016/j.heliyon.2024.e34894.

L. Sharma and M. Srivastava, “Teachers’ motivation to adopt technology in higher education,” Journal of Applied Research in Higher Education, vol. 12, no. 4, pp. 673–692, 2020, doi: 10.1108/JARHE-07-2018-0156.

S. M. M. Loyens, J. E. van Meerten, L. Schaap, and L. Wijnia, Situating Higher-Order, Critical, and Critical-Analytic Thinking in Problem- and Project-Based Learning Environments: A Systematic Review, vol. 35, no. 2. Springer US, 2023. doi: 10.1007/s10648-023-09757-x.

B. G. Acosta-Enriquez et al., “The mediating role of academic stress, critical thinking and performance expectations in the influence of academic self-efficacy on AI dependence: Case study in college students,” Computers and Education: Artificial Intelligence, vol. 8, no. November 2024, 2025, doi: 10.1016/j.caeai.2025.100381.

M. Deng, J. Ma, X. Lv, and X. Ren, “Academic performance and parenting styles differentially predict critical thinking skills and dispositions among primary students: Cross-sectional and cross-lagged evidence,” Think Skills Creat, vol. 50, no. August, p. 101384, 2023, doi: 10.1016/j.tsc.2023.101384.

N. Imjai, W. Promma, B. Usman, and S. Aujirapongpan, “The intertwined effects of digital literacy, agile mindset on design thinking skill and management control competency: Insights from Thai young accountants,” International Journal of Information Management Data Insights, vol. 4, no. 2, p. 100244, 2024, doi: 10.1016/j.jjimei.2024.100244.

L. Fu, “The role of STEM teachers’ emotional intelligence and psychological well-being in predicting their artificial intelligence literacy,” Acta Psychol (Amst), vol. 253, no. January, 2025, doi: 10.1016/j.actpsy.2025.104708.

V. G. Méndez, D. M. Suelves, C. G. Méndez, and J. A. R. L. Mas, “Future teachers facing the use of technology for inclusion: A view from the digital competence,” Educ Inf Technol (Dordr), vol. 28, no. 8, pp. 9305–9323, 2023, doi: 10.1007/s10639-022-11105-5.

D. T. K. Ng, J. K. L. Leung, S. K. W. Chu, and M. S. Qiao, “Conceptualizing AI literacy: An exploratory review,” Computers and Education: Artificial Intelligence, vol. 2, p. 100041, 2021, doi: 10.1016/j.caeai.2021.100041.

W. Hammad, Y. Y. Hilal, and M. Ş. Bellibaş, “Exploring the link between principal instructional leadership and differentiated instruction in an understudied context: the role of teacher collaboration and self-efficacy,” International Journal of Educational Management, vol. 38, no. 4, pp. 1184–1203, 2024, doi: 10.1108/IJEM-09-2023-0441.

C. N. Prilop, T. Rotsaert, and R. Vanderlinde, “Fostering pre-service teachers’ classroom management knowledge, self-efficacy, and professional vision: The effect of different expert feedback and pre-service teachers’ feedback perceptions during online video analysis,” Teach Teach Educ, vol. 157, no. January, p. 104949, 2025, doi: 10.1016/j.tate.2025.104949.

S. Smith, V. Ward, and J. Kabele, Critically evaluating collaborative research: Why is it difficult to extend truth tests to reality tests?, vol. 53, no. 3. 2014. doi: 10.1177/0539018414525292.

L. Kim, N. Imjai, A. Kaewjomnong, K. Dowpiset, and S. Aujirapongpan, “Does experiential learning matter to strategic intuition skills of MBA students? Implications of diagnostic capabilities and critical thinking skills,” International Journal of Management Education, vol. 23, no. 2, 2025, doi: 10.1016/j.ijme.2025.101138.

A. Sellami, M. E. Santhosh, J. Bhadra, and Z. Ahmad, “High school teachers’ perceptions of technology integration in instruction,” On the Horizon, vol. 32, no. 4, pp. 188–205, 2024, doi: 10.1108/OTH-10-2023-0032.

A. Bewersdorff, M. Hornberger, C. Nerdel, and D. S. Schiff, “AI advocates and cautious critics: How AI attitudes, AI interest, use of AI, and AI literacy build university students’ AI self-efficacy,” Computers and Education: Artificial Intelligence, vol. 8, no. October 2024, p. 100340, 2025, doi: 10.1016/j.caeai.2024.100340.




DOI: http://dx.doi.org/10.52155/ijpsat.v50.1.7178

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