AI-INTEGRATED COMPETENCY FRAMEWORK FOR TEACHERS: PROFESSIONAL DEVELOPMENT AND UPHOLDING ETHICAL STANDARDS

AI-INTEGRATED COMPETENCY FRAMEWORK FOR TEACHERS: PROFESSIONAL DEVELOPMENT AND UPHOLDING ETHICAL STANDARDS

Tran Xuan Quang quangtx@vnu.edu.vn VNU University of Education, Vietnam National University, Hanoi 144 Xuan Thuy, Cau Giay, Hanoi, Vietna
Van Thi Hong Hanh hanhvth1508@gmail.com VNU University of Education, Vietnam National University, Hanoi 144 Xuan Thuy, Cau Giay, Hanoi, Vietna
Le Thai Hung* hunglethai82@gmail.com VNU University of Education, Vietnam National University, Hanoi 144 Xuan Thuy, Cau Giay, Hanoi, Vietna
Nguyen Thi Phuong Vy phuongvynt.95@gmail.com International Doctoral Program In Integrative STEM Education, National Taiwan Normal University
Summary: 
The significant transformations in modern education not only provide opportunities to enhance teaching quality but also pose numerous challenges, requiring teachers to continuously improve their knowledge and technological skills. Using a synthesis and analysis of existing literature, this paper examines the development of artificial intelligence (AI) in education and assesses its impact on teacher training and competency development. By consolidating various AI training models and application skills implemented globally, the paper proposes an AI competency framework for teachers, emphasizing adherence to professional ethical standards, including data security, student privacy, fairness in assessment, and transparency in the use of learning data. Additionally, the paper offers an in-depth analysis of the challenges and successes in integrating AI into education, providing recommendations to enhance the effectiveness, sustainability, and humanity of AI applications in teacher training. Through these insights, this study aims to contribute to the development of a digitalized educational environment that is both modern and rooted in core ethical values.
Keywords: 
Artificial intelligence
AI competency framework
AI in education
Professional ethics
teaching quality.
Refers: 

[1] Anderson, L. W., & Krathwohl, D. R. (Eds.). (2001). A taxonomy for learning, teaching, and assessing: A revision of Bloom’s taxonomy of educational objectives.

[2] Axelsen, M., & Bonner, S. (2023). We don’t teach students to use a slide rule in a world of calculators. Times Higher Education.

[3] Ayanwale, M. A. (2023). Evidence from Lesotho Secondary Schools on Students’ Intention to Engage in Artificial Intelligence Learning, 1-6.

[4] Bloom, B. S. (1971). Taxonomy of educational objectives: The classification of educational goals: By a committee of college and university examiners. David McKay.

[5] Bộ Giáo dục và Đào tạo. (2008). Quy định Đạo đức nhà giáo.

[6] Bye, R. T. (2018). A flipped classroom approach for teaching a master’s course on artificial intelligence. Computers Supported Education: 9th International Conference, CSEDU 2017, Porto, Portugal, Revised Selected Papers, 9.

[7] Celik, I., Dindar, M., Muukkonen, H., & Järvelä, S. (2022). The promises and challenges of artificial intelligence for teachers: A systematic review of research. TechTrends, 66(4), 616-630.

[8] Coursera. (2025). Artificial intelligence in education for teachers. Retrieved January 29, 2025.

[9] Department of Education. (2023). Australian framework for generative artificial intelligence in schools. Australia: Department of Education.

[10] Ding, A.-C. E., Shi, L., Yang, H., & Choi, I. (2024). Enhancing teacher AI literacy and integration through different types of cases in teacher professional development. Education Open, 6, 100178.

[11] Elements of AI. (2025). Learn the basics of artificial intelligence for free. Retrieved 20.01.2025.

[12] Hrastinski, S., Olofsson, A. D., Arkenback, C., Ekström, S., Ericsson, E., Fransson, G., ... & Utterberg, M. (2019). Critical imaginaries and reflections on artificial intelligence and robots in postdigital K-12 education. Postdigital Science and Education, 1, 427-445.

[13] Huang, A. Y., Lu, O. H., & Yang, S. J. (2023). Effects of Artificial Intelligence–Enabled Personalized Recommendations on Learners’ Learning Engagement, Motivation, and Outcomes in a Flipped Classroom. Computers & Education, 194, 104684.

[14] Kim, K., & Kwon, K. (2023). Exploring the AI competencies of elementary school teachers in South Korea. Computers and Education: Artificial Intelligence, 4, 100137.

[15] Li, B., & Peng, M. (2022). Integration of an AI-Based Platform and Flipped Classroom Instructional Model. Scientific Programming, 2022(1), 2536382.

[16] Microsoft. (n.d.). AI in education. Retrieved 29.01.2025, from https://www.microsoft.com/vi-vn/ education/ai-in-education

[17] Moorhouse, B. L., Kohnke, L., & Chiu, T. K. (2024). Developing a Context-and Subject-Specific Professional Digital Competence Framework for Beginning English Language Teachers in Hong Kong. The Asia-Pacific Education Researcher, 33(5), 1105-1115.

[18] Moorhouse, B. L., Wan, Y., Wu, C., Kohnke, L., Ho, T. Y., & Kwong, T. (2024). Developing language teachers’ professional generative AI competence: An intervention study in an initial language teacher education course. System, 125, 103399.

[19] Ng, D. T. K., Leung, J. K. L., Chu, S. K. W., & Qiao, M. S. (2021). Conceptualizing AI literacy: An exploratory review. Computers and Education: Artificial Intelligence, 2, 100041.

[20] Ng, D. T. K., Lee, M., Tan, R. J. Y., Hu, X., Downie, J. S., & Chu, S. K. W. (2023). A review of AI teaching and learning from 2000 to 2020. Education and Information Technologies, 28(7), 8445-8501.

[21] UNESCO. (2018). UNESCO ICT competency framework for teachers (Version 3.0).

[22] U.S. Department of Education, Office of Educational Technology. (2023). Artificial intelligence and future of teaching and learning: Insights and recommendations.

[23] Vazhayil, A., Shetty, R., Bhavani, R. R., & Akshay, N. (2019, December). Focusing on teacher education to introduce AI in schools: Perspectives and illustrative findings. In 2019 IEEE tenth international conference on Technology for Education (T4E), 71-77.

Articles in Issue