EFL Instructors’ AI Competency: Scale Development and Validation

Golnazari, Ali; Farahian, Majid

doi:10.22080/iselt.2026.30020.1120

EFL Instructors’ AI Competency: Scale Development and Validation

Document Type : Original Article

Authors

Department of Foreign Languages Teaching, Ker.C., Islamic Azad University, Kermanshah, Iran

10.22080/iselt.2026.30020.1120

Abstract

The rapid integration of Artificial Intelligence (AI) into language education means that Teaching English as a Foreign Language (TEFL) instructors require specific competencies in AI in addition to generic digital literacy competencies. However, there is a significant gap with respect to validated tools that assess these AI competencies, especially in low-resource contexts. As such, the purpose of this study was to develop and validate a questionnaire to measure AI competencies in Iranian TEFL instructors. The item pool was developed with consideration of a comprehensive literature review. After a pilot study, a 24-item instrument was given to a sample of 265 instructors. Exploratory Factor Analysis (EFA) showed a solid five-factor structure comprised of Professional Development and Willingness to Learn, Ethical, Privacy and Bias Awareness, Technical Proficiency in AI Tools, AI Knowledge and Awareness, and Pedagogical Integration of AI, which explained 70.14% of total variance. The questionnaire demonstrated high reliability, with a Cronbach’s alpha of .93 for the whole scale for the subscales. Overall, the results provide a sophisticated understanding of the construct, offering policymakers and teacher trainers a diagnostic tool that can lead to planned professional development to help effectively, ethically, and pedagogically integrate AI into English as a Foreign language (EFL) education practices.

Keywords

Main Subjects

Copyright © 2026 The Author(s). Published by the Faculty of Persian Literature and Foreign Languages at the University of Mazandaran. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) license.

References

Akgün, S. and Greenhow, C. (2021). Artificial intelligence in education: addressing ethical challenges in k-12 settings. AI and Ethics, 2(3), 431-440. https://doi.org/10.1007/s43681-021-00096-7

Aldboush, H. and Ferdous, M. (2023). Building trust in fintech: an analysis of ethical and privacy considerations in the intersection of big data, AI, and customer trust. International Journal of Financial Studies, 11(3), 90. https://doi.org/10.3390/ijfs11030090

Al-Hwsali, A., Alsaadi, B., Abdi, N., Khatab, S., Alzubaidi, M., Solaiman, B., & Househ, M. (2023). Scoping review: Legal and ethical principles of artificial intelligence in public health. Studies in Health Technology and Informatics, 302, 97–106. https://doi.org/10.3233/shti230579

Alnasib, B. (2023). Factors affecting faculty members’ readiness to integrate artificial intelligence into their teaching practices: a study from the Saudi higher education context. International Journal of Learning Teaching and Educational Research, 22(8), 465-491. https://doi.org/10.26803/ijlter.22.8.24

Busso, A., & Sanchez, B. (2024). Advancing communicative competence in the digital age: A case for AI tools in Japanese university EFL programs. Technology in Language Teaching & Learning, 6(3), 1–17. https://doi.org/10.29140/tltl.v6n3.1211

Casal-Otero, L., Català, A., Fernández-Morante, C., Taberna, J., García-Soidán, P., & Rodríguez-Malvar, M. (2023). AI literacy in K-12: A systematic literature review. International Journal of STEM Education, 10(1), 29. https://doi.org/10.1186/s40594-023-00418-7

Chen, X., Zou, D., Xie, H., & Wang, F. L. (2023). Past, present, and future of smart learning: A topic-based bibliometric analysis. International Journal of Educational Technology in Higher Education, 20(1), 15. https://doi.org/10.1186/s41239-023-00384-8

Chiu, T. K. F., Ahmad, Z., Ismailov, M., & Sanusi, I. T. (2024). What are artificial intelligence literacy and competency? A comprehensive framework to support them. Computers and Education Open, 6, 100171.

Cioci, G. (2024). AI in the class: Uses, doubts, challenges and perceptions of a sample of teachers from different nationalities. Education Sciences and Society, (2), 38-55. https://doi.org/10.3280/css2-2024oa18439

Curran, P. J., West, S. G., & Finch, J. F. (1996). The robustness of test statistics to nonnormality and specification error in confirmatory factor analysis. Psychological Methods, 1(1), 16–29.

Eldin, A. H. (2024). Using artificial intelligence in EFL teacher education programs. Sustainability Education Globe, 2(1), 26–35. https://doi.org/10.21608/seg.2024.272816.1004

Er, E., Akçapınar, G., Khalil, M., Noroozi, O., & Banihashem, S. K. (2024). Assessing student perceptions and use of instructor versus ai‐generated feedback. British Journal of Educational Technology, 56(3), 1074-1091.

Feretzakis, G., Αnastasiou, Α., Pitoglou, S., Paxinou, E., Gkoulalas-Divanis, A., Kalodanis, K., & Verykios, V. (2024). Securing a generative ai-powered healthcare chatbot. Studies in Health Technology and Informatics, 302, 97-106.

Ferrari, A. (2012). Digital competence in practice: An analysis of frameworks. Publications Office of the European Union. https://data.europa.eu/doi/10.2791/82116

González-Prida, V., Chuquin-Berrios, J. G., Moreno Menéndez, F. M., Sandoval-Trigos, J. C., Pariona-Amaya, D., & Gómez-Bernaola, K. O. (2024). Digital competencies as predictors of academic self-efficacy: Correlations and implications for educational development. Societies, 14(11), 226. https://doi.org/10.3390/soc14110226

Güneyli, A., Burgul, N., Dericioğlu, S., Cenkova, N., Becan, S., Şimşek, Ş., & Güneralp, H. (2024). Exploring teacher awareness of artificial intelligence in education: a case study from northern Cyprus. European Journal of Investigation in Health Psychology and Education, 14(8), 2358-2376.

Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2019). Multivariate data analysis (8th ed.). Cengage Learning.

Jeon, J., & Lee, S. (2023). Large language models in education: A focus on the complementary relationship between human teachers and ChatGPT. Education and Information Technologies, 28(12), 15873–15892. https://doi.org/10.1007/s10639-023-11834-1

Jobin, A., Ienca, M., & Vayena, E. (2019). The global landscape of ai ethics guidelines. Nature Machine Intelligence, 1(9), 389-399. https://doi.org/10.1038/s42256-019-0088-2

Kaiser, H. F. (1974). An index of factorial simplicity. Psychometrika, 39(1), 31–36. https://doi.org/10.1007/BF02291575

Kohnke, L. (2023). A pedagogical chatbot: A supplemental language learning tool. RELC Journal, 54 (3), 828–838. https://doi.org/10.1177/00336882231162844

Lawshe, C. H. (1975). A quantitative approach to content validity. Personnel Psychology, 28(4), 563–575.

Liu, M. (2023). Exploring the application of artificial intelligence in foreign language teaching: challenges and future development. SHS Web of Conferences, 168, 03025. https://doi.org/10.1051/shsconf/202316803025

Marković, L., Živković, E., & Paunović, T. (2022). Pre-service EFL teachers as reflective practitioners: student portfolios as evidence of emerging professional identities. Journal of Contemporary Philology, 5(2), 65-76.

Mishra, P., & Koehler, M. J. (2006). Technological pedagogical content knowledge: A framework for teacher knowledge. Teachers College Record, 108(6), 1017–1054. https://doi.org/10.1111/j.1467-9620.2006.00684.x

Ng, D. T. K., Leung, J. K. L., Su, J., Ng, R. C. W., & Chu, S. K. W. (2023). Teachers’ AI digital competencies and twenty-first century skills in the post-pandemic world. Educational Technology Research and Development, 71(1), 137–161. https://doi.org/10.1007/s11423-023-10203-6

Nunnally, J. C. (1978). Psychometric theory (2nd ed.). McGraw-Hill.

Patiño, A., Montaño, V., Buri, P., Rojas, M., & González, A. (2024). The improvement of oral communicative competence in English through the artificial intelligence. Latam Revista Latinoamericana De Ciencias Sociales Y Humanidades, 5(1). https://doi.org/10.56712/latam.v5i1.1850

Popenici, S.A.D., Kerr, S. (2017). Exploring the impact of artificial intelligence on teaching and learning in higher education. Research and Practice in Technology Enhanced Learning, 12. https://doi.org/10.1186/s41039-017-0062-8

Priyantin, T., & Herawati, A. (2023). EFL teachers’ strategies and challenges in developing digital competency: A narrative inquiry. Pedagogy: Journal of English Language Teaching, 11(1), 01.

Rosli, N. D. M., Khambari, M. N. Md., Wong, S. L., Zakaria, N. S., Abdullah, K., Hamzah, S. R., Moses, P., & Abdrahim, N. A. (2024). A scientometric review of digital competency among educators during the past 10 years. International Journal of Evaluation and Research in Education, 14(1), 74.

Selwyn, N. (2021). Ed-Tech Within Limits: Anticipating educational technology in times of environmental crisis. E- Learning and Digital Media, 18(5), 496–510.

Selwyn, N. (2023). Should robots replace teachers? AI and the future of education (2nd ed.). Polity Press.

Strasser, T. A. (2023). ELT in the digital age: We have come a long way. Aaa-Arbeiten Aus Anglistik Und Amerikanistik, 48(1), 121–136. https://doi.org/10.24053/aaa-2023-0006

Tabachnick, B. G., & Fidell, L. S. (2013). Using multivariate statistics (6th ed.). Pearson.

Taber, K.S. (2018). The Use of Cronbach’s alpha when developing and reporting research instruments in science education. Research in Science Education, 48, 1273–1296. https://doi.org/10.1007/s11165-016-9602-2

Tenberga, I., & Daniela, L. (2024). Artificial intelligence literacy competencies for teachers through self-assessment tools. Sustainability, 16(23), 10386. https://doi.org/103390/su162310386

Tondeur, J., Aesaert, K., Prestridge, S., & Consuegra, E. (2017). A multilevel analysis of what matters in the training of pre-service teacher's ICT competencies. Computers & Education, 122, 32–42.

Yin, H., Khan, S., Alharbi, A., & Nazir, S. (2022). Assessing English teaching linguistic and artificial intelligence for efficient learning using analytical hierarchy process and technique for order of preference by similarity to ideal solution. Journal of Software Evolution and Process, 36(2). https://doi.org/10.1002/smr.2462

Yuliani, S., Mukhibbah, T. L., & Agustina, E. (2024). Artificial intelligence usage in higher education: EFL students' view. ELTR Journal, 8(2), 119–129.