AI Readiness in Education: A Review of Conceptual Foundations, Pedagogical Dimensions, and Ethical Considerations

Authors

  • Chenshuo Dong
  • Jose Ma W. Gopez

DOI:

https://doi.org/10.54097/6farb504

Keywords:

AI Readiness, Artificial Intelligence in Education, Technology Self-Efficacy, Ethical Awareness, Student Interaction, Vocational Education

Abstract

The rapid integration of artificial intelligence (AI) into educational systems has intensified scholarly interest in understanding educators’ preparedness to adopt AI technologies effectively and responsibly. This review paper synthesizes existing literature on AI readiness in education, conceptualizing it as a multidimensional construct encompassing technology self-efficacy, pedagogical capacity for student interaction, and ethical awareness. Drawing on international and Chinese studies, with particular attention to higher education and vocational training contexts, the review highlights how individual, institutional, and socio-demographic factors shape teachers’ readiness for AI integration. The analysis reveals that while research on AI acceptance and intention is expanding, empirical studies employing holistic and validated readiness frameworks-especially in non-Western and vocational settings-remain limited. By integrating fragmented strands of research, this review advances a more comprehensive and context-sensitive understanding of AI readiness and identifies directions for future research and policy development aimed at supporting responsible, human-centered AI adoption in education.

Downloads

Download data is not yet available.

References

[1] Y.-C. Hsu, Y.-H. Ching, and S. Grabowski, “Web 2.0 applications and practices for learning through collaboration,” Educational Technology Research and Development, vol. 67, no. 2, pp. 355–380, 2019.

[2] R. Baguma, P. Ssentamu, and J. M. Nalubega, “Institutional readiness for artificial intelligence adoption in higher education,” International Journal of Educational Technology in Higher Education, vol. 20, no. 1, pp. 1–18, 2023.

[3] P. A. Ertmer and A. T. Ottenbreit-Leftwich, “Teacher technology change: How knowledge, confidence, beliefs, and culture intersect,” Journal of Research on Technology in Education, vol. 42, no. 3, pp. 255–284, 2010.

[4] Y. Zhao, “Artificial intelligence and China’s educational modernization strategy,” Educational Research, vol. 46, no. 1, pp. 3–15, 2025.

[5] L. Xu, “Teachers’ acceptance of artificial intelligence in Chinese higher education,” Computers & Education: Artificial Intelligence, vol. 6, pp. 100–112, 2025.

[6] A. Bandura, Self-Efficacy: The Exercise of Control. New York, NY, USA: W. H. Freeman, 1997.

[7] T. Nguyen and T. Huynh, “Teachers’ technological self-efficacy and AI-supported pedagogy,” Education and Information Technologies, vol. 28, no. 4, pp. 4871–4890, 2023.

[8] Q. Wu, X. Zhang, and Y. Chen, “Barriers to AI adoption among teachers: A self-efficacy perspective,” Computers in Human Behavior, vol. 129, 107118, 2022.

[9] Y. Chen, H. Li, and F. Xu, “Interpreting AI-generated analytics for instructional decision-making,” British Journal of Educational Technology, vol. 53, no. 6, pp. 1832–1848, 2022.

[10] V. Venkatesh, M. G. Morris, G. B. Davis, and F. D. Davis, “User acceptance of information technology: Toward a unified view,” MIS Quarterly, vol. 27, no. 3, pp. 425–478, 2003.

[11] D. Smutny and M. Schlegel, “Demographic differences in teachers’ digital and AI competencies,” Teaching and Teacher Education, vol. 124, 104118, 2024.

[12] S. Jackman, A. Rogers, and M. Chen, “AI-driven personalization and student engagement,” Computers & Education, vol. 198, 104123, 2025.

[13] Y. Chen, Q. Yang, and L. Zhao, “Adaptive learning systems and AI-supported feedback,” Educational Technology & Society, vol. 26, no. 1, pp. 45–58, 2023.

[14] Y. Zhou and H. Li, “Artificial intelligence, large-class teaching, and teacher workload in China,” Asia-Pacific Education Review, vol. 24, no. 2, pp. 289–302, 2023.

[15] J. Lin, M. Wang, and C. Chan, “Student-centered pedagogy in AI-enhanced classrooms,” Interactive Learning Environments, vol. 32, no. 1, pp. 1–16, 2024.

[16] M. Ramazanoglu and A. Akin, “Developing the Responsible AI Awareness Scale for educators,” Education and Information Technologies, vol. 29, no. 2, pp. 1567–1585, 2024.

[17] X. Guo, L. Sun, and Y. Li, “Ethical risks of artificial intelligence in education,” AI & Society, vol. 39, no. 1, pp. 211–223, 2024.

[18] J. Bautista, R. Borges, and S. Choi, “Responsible AI literacy for teachers,” Computers & Education: Artificial Intelligence, vol. 5, 100109, 2024.

[19] H. Zhang and Y. Liu, “Ethical governance of artificial intelligence in education,” Journal of Educational Administration, vol. 61, no. 3, pp. 367–382, 2023.

[20] M. Alaidarous and K. Al-Saadi, “Surveillance, data ethics, and artificial intelligence in education,” Educational Philosophy and Theory, vol. 56, no. 4, pp. 389–403, 2024.

[21] P. Mishra, T. Henriksen, and D. Boltz, “Bias and misuse in educational AI systems,” Educational Technology Research and Development, vol. 72, no. 1, pp. 95–112, 2024.

Downloads

Published

11-02-2026

Issue

Section

Articles