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İngilizce Öğretmen Adaylarının Yapay Zekaya Yönelik Tutumları

Year 2025, Volume: 18 Issue: 3, 609 - 629, 24.07.2025

Pelin Derinalp , Melek Halife

https://doi.org/10.30831/akukeg.1644354

Abstract

Yapay Zeka (YZ), çağdaş toplumun birçok alanında aktif olarak yer almaktadır. Diğer birçok alanda olduğu gibi, dil eğitiminde de önemli bir dönüşüme öncülük etmiştir. Bugünün öğretmen adayları geleceği şekillendireceğinden, dil sınıflarında YZ kullanımına yönelik tutumlarını anlamak çok önemlidir. Bu nedenle, bu çalışma Türkiye'deki bir devlet üniversitesinde öğrenim gören İngilizce öğretmen adaylarının YZ'ye yönelik tutumlarını incelemeyi amaçlamaktadır. Bu çalışmada, karma yöntemli bir araştırma tasarımı benimsenmiştir. Nicel veriler, 193 Yabancı Dil Olarak İngilizce öğretmen adayının katılımıyla bir ölçek aracılığıyla toplanmış ve çeşitli betimsel değişkenler doğrultusunda analiz edilmiştir. Nitel veriler ise 10 katılımcı ile derinlemesine görüşmeler yoluyla toplanmış ve tematik analiz yoluyla analiz edilmiştir. Nicel bulgular, erkek katılımcıların YZ'ye karşı daha olumlu tutumlara sahip olduğunu ve YZ'ye aşina olan ve YZ kullanan bireylerin daha olumlu tutumlara sahip olduğunu göstermektedir. Ayrıca, üçüncü sınıf öğrencilerinin birinci sınıf öğrencilerine kıyasla daha yüksek davranışsal tutum puanlarına sahip olduğu bulunmuştur. Nitel analiz sonuçları, YZ'nin eğitim süreçlerine entegrasyonunda karşılaşılan zorluklar, sağladığı potansiyel faydalar, katılımcıların bu teknolojilere yönelik tercihleri ve eğitimde YZ'nin geleceğine ilişkin öngörüler gibi temaların öne çıktığını ortaya koymuştur.

Keywords

Yapay zeka İngiliz Dili Öğretimi tutum İngilizce Öğretmen Adayları

References

  • Adipat, S., Chotikapanich, R., Laksana, K., Busayanon, K., Piatanom, P., Ausawasowan, A., & Elbasouni, I. (2023). Technological pedagogical content knowledge for professional teacher development. Academic Journal of Interdisciplinary Studies, 12(1), 173-182. https://doi.org/10.36941/ajis-2023-0015
  • Ahmad, S. F., Alam, M. M., Rahmat, M. K., Mubarik, M. S., & Hyder, S. I. (2022). Academic and administrative role of artificial intelligence in education. Sustainability, 14(3), 1101. Sustainability. https://doi.org/10.3390/su14031101
  • Aljohani, R. A. (2021). Teachers and students’ perceptions on the impact of artificial intelligence on English language learning in Saudi Arabia. Journal of Applied Linguistics and Language Research, 8(1), 36–47. http://www.jallr.com/index.php/JALLR/article/view/1156
  • Arslan, S. (2025). English-as-a-foreign language university instructors' perceptions of integrating artificial intelligence: A Turkish perspective. System, 131, 103680. https://doi.org/10.1016/j.system.2025.103680
  • Bagozzi, R. P. (1978). The construct validity of the affective, behavioral, and cognitive components of attitude by analysis of covariance structures. Multivariate Behavioral Research, 13(1), 9–31.
  • Braun, V., & Clarke, V. (2019). Reflecting on reflexive thematic analysis. Qualitative Research in Sport, Exercise and Health, 11(4), 589–597. https://doi.org/10.1080/2159676X.2019.1628806
  • Cho, K. A., & Seo, Y. H. (2024). Dual mediating effects of anxiety to use and acceptance attitude of artificial intelligence technology on the relationship between nursing students’ perception of and intention to use them: A descriptive study. BMC Nursing, 23(1), 212. https://doi.org/10.1186/s12912-024-01887-z
  • Copeland, J. (1998). Artificial intelligence: A philosophical introduction. John Wiley & Sons.
  • Cotton, D. R. E., Cotton, P. A., & Shipway, J. R. (2023). Chatting and cheating: Ensuring academic integrity in the era of ChatGPT. Innovations in Education and Teaching International, 1–12. https://doi.org/10.1080/14703297.2023.2190148
  • Creswell, J. W., & Poth, C. N. (2018). Qualitative inquiry & research design: Choosing among five approaches (4th ed.). Sage.
  • Darwin, Rusdin, D., Mukminatien, N., Suryati, N., Laksmi, E. D., & Marzuki. (2024). Critical thinking in the AI era: An exploration of EFL students’ perceptions, benefits, and limitations. Cogent Education, 11(1), 2290342. https://doi.org/10.1080/2331186X.2023.2290342
  • Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340.
  • Derinalp, P. (2024). Past, Present, and Future of Artificial Intelligence in Education: A Bibliometric Study. Sakarya University Journal of Education, 14(2 (Special Issue-Artificial Intelligence Tools and Education)), 159-178. https://doi.org/10.19126/suje.1447044
  • Derinalp, P., & Özyurt, M. (2024). Adaptation of the student attitudes toward artificial intelligence scale to the Turkish context: Validity and reliability Study. International Journal of Human–Computer Interaction, 41(8), 4653–4667. https://doi.org/10.1080/10447318.2024.2352921
  • Eagly, A. H., & Chaiken, S. (1993). The psychology of attitudes. Harcourt Brace Jovanovich College Publishers.
  • Eyüp, B., & Kayhan, S. (2023). Pre-service Turkish language teachers' anxiety and attitudes toward artificial intelligence. International Journal of Education and Literacy Studies, 11(4), 43–56. http://dx.doi.org/10.7575/aiac.ijels.v.11n.4p.43
  • Fietta, V., Zecchinato, F., Stasi, B., Polato, M., & Monaro, M. (2022). Dissociation between users’ explicit and implicit attitudes toward artificial intelligence: An experimental study. IEEE Transactions on Human-Machine Systems, 52, 481–489.
  • Garcia-Marques, T., Prada, M., & Mackie, D. M. (2016). Familiarity increases subjective positive affect even in non-affective and non-evaluative contexts. Motivation and Emotion, 40, 638–645. https://doi.org/10.1007/s11031-016-9555-9
  • Harakchiyska, T., & Vassilev, T. (2024). Pre-service teachers’ perceptions of AI and its implementation in the foreign (English) language classroom. Strategies for Policy in Science & Education, 32, 218-232. https://doi.org/10.53656/str2024-5s-22-pre
  • Hashem, R., Ali, N., Zein, F., Fidalgo, P., & Khurma, O. (2023). AI to the rescue: Exploring the potential of ChatGPT as a teacher ally for workload relief and burnout prevention. Research and Practice in Technology Enhanced Learning, 19(23), 1-26. https://doi.org/10.58459/rptel.2024.19023
  • Hasibuan, R., & Azizah, A. (2023). Analyzing the potential of artificial intelligence (AI) in personalizing learning to foster creativity in students. Enigma in Education, 1(1). https://doi.org/10.61996/edu.v1i1.2
  • Hınız, G. (2024). A year of generative AI in English language teaching and learning – A case study. Journal of Research on Technology in Education, 1–21. https://doi.org/10.1080/15391523.2024.2404132
  • Kasımi, Y., & Fidan, Ş. (2023). An investigation into artificial intelligence (AI) in the English as a foreign language (EFL) context. International Journal of Educational Spectrum, 5(2), 269–280. https://doi.org/10.47806/ijesacademic.1341110
  • Katsantonis, A., & Katsantonis, I. G. (2024). University students’ attitudes toward artificial intelligence: An exploratory study of the cognitive, emotional, and behavioural dimensions of AI attitudes. Education Sciences, 14(9), 988. https://doi.org/10.3390/educsci14090988
  • Lopes, A., Dotta, L. T., & Pereira, F. (2023). Factors influencing teachers' uses of new technologies: Mindsets and professional identities as crucial variables. International Journal of Instruction, 16(4), 521-542. https://doi.org/10.29333/iji.2023.16430a
  • Metsärinne, M., & Kallio, M. (2016). How are students’ attitudes related to learning outcomes? International Journal of Technology and Design Education, 26, 353–371.
  • Mishra, P., & Koehler, M. J. (2006). Technological pedagogical content knowledge: A framework for teacher knowledge. Teachers College Record, 108(6), 1017–1054.
  • Salas-Pilco, S., Xiao, K., & Oshima, J. (2022). Artificial intelligence and new technologies in inclusive education for minority students: A systematic review. Sustainability. https://doi.org/10.3390/su142013572
  • Sarhan, Y. S. (2023). At the intersectionality of growth mindset and technology acceptance and use: A quantitative study [Doctoral dissertation]. The Chicago School of Professional Psychology.
  • Schepman, A., & Rodway, P. (2023). The general attitudes towards artificial intelligence scale (GAAIS): Confirmatory validation and associations with personality, corporate distrust, and general trust. International Journal of Human–Computer Interaction, 39(13), 2724–2741. https://doi.org/10.1080/10447318.2022.2085400
  • Simonovic, B., Vione, K. C., Fido, D., Stupple, E. J., Martin, J., & Clarke, R. (2022). The impact of attitudes, beliefs, and cognitive reflection on the development of critical thinking skills in online students. Online Learning, 26(2), 254–274.
  • So, H., & Kim, B. (2009). Learning about problem-based learning: Student teachers integrating technology, pedagogy and content knowledge. Australasian Journal of Educational Technology, 25, 101–116. https://doi.org/10.14742/AJET.1183
  • Suh, W., & Ahn, S. (2022). Development and validation of a scale measuring student attitudes toward artificial intelligence. SAGE Open, 12(2). https://doi.org/10.1177/21582440221100463
  • Özkan, E. K., Erdemir, N., & Coşkun, D. (2024). A systematic review of EFL teachers’ perspectives on artificial intelligence technologies. Ihlara Eğitim Araştırmaları Dergisi, 9(2), 150–168. https://doi.org/10.47479/ihead.1535035
  • Tapalova, O., & Zhiyenbayeva, N. (2022). Artificial intelligence in education: AIEd for personalised learning pathways. Electronic Journal of e-Learning. https://doi.org/10.34190/ejel.20.5.2597
  • Taşçı, S., & Tunaz, M. (2024). Opportunities and challenges in AI-assisted language teaching: Perceptions of pre-service EFL teachers. Araştırma ve Deneyim Dergisi, 9(2), 74–83. https://doi.org/10.47214/adeder.1575897
  • Tomić, B., Kijevcanin, A., Sevarac, Z., & Jovanovic, J. (2023). An AI-based approach for grading students’ collaboration. IEEE Transactions on Learning Technologies, 16, 292–305.
  • Vittorini, P., Menini, S., & Tonelli, S. (2020). An AI-based system for formative and summative assessment in data science courses. International Journal of Artificial Intelligence in Education, 31, 159–185. https://doi.org/10.1007/s40593-020-00230-2
  • Wang, Y. (2021). An improved machine learning and artificial intelligence algorithm for classroom management of English distance education. Journal of Intelligent & Fuzzy Systems, 40, 3477–3488. https://doi.org/10.3233/jifs-189385
  • Yetişensoy, O. (2024). Tomorrow's teachers and artificial intelligence: Exploring attitudes and perceptions of Turkish prospective social studies teachers. Eurasian Journal of Teacher Education, 5(1), 1–31. https://dergipark.org.tr/tr/download/article-file/3613703
  • Yetkin, R., & Özer-Altınkaya, Z. (2024). AI in the language classroom: Insights from pre-service English teachers. E-Learning and Digital Media. https://doi.org/10.1177/20427530241267011
  • Yılmaz-Virlan, A., & Tomak, B. (2024). AQ method study on Turkish EFL learners’ perspectives on the use of AI tools for writing: Benefits, concerns, and ethics. Language Teaching Research. https://doi.org/10.1177/13621688241308836
  • Younas, A., Subramanian, K., Haziazi, M., Hussainy, S., & Kindi, A. (2023). A review on implementation of artificial intelligence in education. International Journal of Research and Innovation in Social Science. https://doi.org/10.47772/ijriss.2023.7886
  • Zhang, B., & Dafoe, A. (2019). Artificial intelligence: American attitudes and trends. Center for the Governance of AI, Future of Humanity Institute, University of Oxford. https://dx.doi.org/10.2139/ssrn.3312874
  • Zhang, C., Schießl, J., Plößl, L., Hofmann, F., & Gläser-Zikuda, M. (2023). Acceptance of artificial intelligence among pre-service teachers: A multigroup analysis. International Journal of Educational Technology in Higher Education, 20(1), 49. https://doi.org/10.1186/s41239-023-00420-7
  • Zhou, C., & Hou, F. (2025). How do EFL teachers utilize AI tools in their language teaching? Theory and Practice in Language Studies. https://doi.org/10.17507/tpls.1502.10

Pre-Service English as a Foreign Language Teachers’ Attitudes toward Artificial Intelligence

Year 2025, Volume: 18 Issue: 3, 609 - 629, 24.07.2025

Pelin Derinalp , Melek Halife

https://doi.org/10.30831/akukeg.1644354

Abstract

Artificial Intelligence (AI) is actively involved in many areas of contemporary society. As in many other fields, it has pioneered a significant transformation in language education. As today’s preservice teachers will shape the future, it is crucial to understand their attitudes toward using AI in language classrooms. Hence, this study aims to examine the attitudes towards AI of pre-service English language teachers studying at a state university in Turkey. A mixed-method research design was adopted. Data was collected via a scale with the participation of 193 pre-service English as a Foreign Language teachers and analyzed in line with various descriptive variables. Qualitative data were collected through in-depth interviews with 10 participants and analyzed via thematic analysis. Quantitative findings show that male participants have more positive attitudes towards AI, and individuals who are familiar with AI and have used AI have more positive attitudes. In addition, third-year students were found to have higher behavioral attitude scores compared to first-year students. The results of the qualitative analysis revealed that themes such as the challenges faced in the integration of AI into educational processes, the potential benefits it provides, participants' preferences for these technologies, and predictions about the future of AI in education came to the fore.

Keywords

: Artificial Intelligence ELT pre-service English Language Teachers Attitude

Ethical Statement

Ethical approval of this study is obtained from Gaziantep University with approval number 456833.

Supporting Institution

TUBITAK

Thanks

We would like to thank Türkiye Bilimsel ve Teknolojik Araştırma Kurumu (TUBITAK) for funding this project. Also, we would like to extend our thanks to the editors and reviewers.

References

  • Adipat, S., Chotikapanich, R., Laksana, K., Busayanon, K., Piatanom, P., Ausawasowan, A., & Elbasouni, I. (2023). Technological pedagogical content knowledge for professional teacher development. Academic Journal of Interdisciplinary Studies, 12(1), 173-182. https://doi.org/10.36941/ajis-2023-0015
  • Ahmad, S. F., Alam, M. M., Rahmat, M. K., Mubarik, M. S., & Hyder, S. I. (2022). Academic and administrative role of artificial intelligence in education. Sustainability, 14(3), 1101. Sustainability. https://doi.org/10.3390/su14031101
  • Aljohani, R. A. (2021). Teachers and students’ perceptions on the impact of artificial intelligence on English language learning in Saudi Arabia. Journal of Applied Linguistics and Language Research, 8(1), 36–47. http://www.jallr.com/index.php/JALLR/article/view/1156
  • Arslan, S. (2025). English-as-a-foreign language university instructors' perceptions of integrating artificial intelligence: A Turkish perspective. System, 131, 103680. https://doi.org/10.1016/j.system.2025.103680
  • Bagozzi, R. P. (1978). The construct validity of the affective, behavioral, and cognitive components of attitude by analysis of covariance structures. Multivariate Behavioral Research, 13(1), 9–31.
  • Braun, V., & Clarke, V. (2019). Reflecting on reflexive thematic analysis. Qualitative Research in Sport, Exercise and Health, 11(4), 589–597. https://doi.org/10.1080/2159676X.2019.1628806
  • Cho, K. A., & Seo, Y. H. (2024). Dual mediating effects of anxiety to use and acceptance attitude of artificial intelligence technology on the relationship between nursing students’ perception of and intention to use them: A descriptive study. BMC Nursing, 23(1), 212. https://doi.org/10.1186/s12912-024-01887-z
  • Copeland, J. (1998). Artificial intelligence: A philosophical introduction. John Wiley & Sons.
  • Cotton, D. R. E., Cotton, P. A., & Shipway, J. R. (2023). Chatting and cheating: Ensuring academic integrity in the era of ChatGPT. Innovations in Education and Teaching International, 1–12. https://doi.org/10.1080/14703297.2023.2190148
  • Creswell, J. W., & Poth, C. N. (2018). Qualitative inquiry & research design: Choosing among five approaches (4th ed.). Sage.
  • Darwin, Rusdin, D., Mukminatien, N., Suryati, N., Laksmi, E. D., & Marzuki. (2024). Critical thinking in the AI era: An exploration of EFL students’ perceptions, benefits, and limitations. Cogent Education, 11(1), 2290342. https://doi.org/10.1080/2331186X.2023.2290342
  • Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340.
  • Derinalp, P. (2024). Past, Present, and Future of Artificial Intelligence in Education: A Bibliometric Study. Sakarya University Journal of Education, 14(2 (Special Issue-Artificial Intelligence Tools and Education)), 159-178. https://doi.org/10.19126/suje.1447044
  • Derinalp, P., & Özyurt, M. (2024). Adaptation of the student attitudes toward artificial intelligence scale to the Turkish context: Validity and reliability Study. International Journal of Human–Computer Interaction, 41(8), 4653–4667. https://doi.org/10.1080/10447318.2024.2352921
  • Eagly, A. H., & Chaiken, S. (1993). The psychology of attitudes. Harcourt Brace Jovanovich College Publishers.
  • Eyüp, B., & Kayhan, S. (2023). Pre-service Turkish language teachers' anxiety and attitudes toward artificial intelligence. International Journal of Education and Literacy Studies, 11(4), 43–56. http://dx.doi.org/10.7575/aiac.ijels.v.11n.4p.43
  • Fietta, V., Zecchinato, F., Stasi, B., Polato, M., & Monaro, M. (2022). Dissociation between users’ explicit and implicit attitudes toward artificial intelligence: An experimental study. IEEE Transactions on Human-Machine Systems, 52, 481–489.
  • Garcia-Marques, T., Prada, M., & Mackie, D. M. (2016). Familiarity increases subjective positive affect even in non-affective and non-evaluative contexts. Motivation and Emotion, 40, 638–645. https://doi.org/10.1007/s11031-016-9555-9
  • Harakchiyska, T., & Vassilev, T. (2024). Pre-service teachers’ perceptions of AI and its implementation in the foreign (English) language classroom. Strategies for Policy in Science & Education, 32, 218-232. https://doi.org/10.53656/str2024-5s-22-pre
  • Hashem, R., Ali, N., Zein, F., Fidalgo, P., & Khurma, O. (2023). AI to the rescue: Exploring the potential of ChatGPT as a teacher ally for workload relief and burnout prevention. Research and Practice in Technology Enhanced Learning, 19(23), 1-26. https://doi.org/10.58459/rptel.2024.19023
  • Hasibuan, R., & Azizah, A. (2023). Analyzing the potential of artificial intelligence (AI) in personalizing learning to foster creativity in students. Enigma in Education, 1(1). https://doi.org/10.61996/edu.v1i1.2
  • Hınız, G. (2024). A year of generative AI in English language teaching and learning – A case study. Journal of Research on Technology in Education, 1–21. https://doi.org/10.1080/15391523.2024.2404132
  • Kasımi, Y., & Fidan, Ş. (2023). An investigation into artificial intelligence (AI) in the English as a foreign language (EFL) context. International Journal of Educational Spectrum, 5(2), 269–280. https://doi.org/10.47806/ijesacademic.1341110
  • Katsantonis, A., & Katsantonis, I. G. (2024). University students’ attitudes toward artificial intelligence: An exploratory study of the cognitive, emotional, and behavioural dimensions of AI attitudes. Education Sciences, 14(9), 988. https://doi.org/10.3390/educsci14090988
  • Lopes, A., Dotta, L. T., & Pereira, F. (2023). Factors influencing teachers' uses of new technologies: Mindsets and professional identities as crucial variables. International Journal of Instruction, 16(4), 521-542. https://doi.org/10.29333/iji.2023.16430a
  • Metsärinne, M., & Kallio, M. (2016). How are students’ attitudes related to learning outcomes? International Journal of Technology and Design Education, 26, 353–371.
  • Mishra, P., & Koehler, M. J. (2006). Technological pedagogical content knowledge: A framework for teacher knowledge. Teachers College Record, 108(6), 1017–1054.
  • Salas-Pilco, S., Xiao, K., & Oshima, J. (2022). Artificial intelligence and new technologies in inclusive education for minority students: A systematic review. Sustainability. https://doi.org/10.3390/su142013572
  • Sarhan, Y. S. (2023). At the intersectionality of growth mindset and technology acceptance and use: A quantitative study [Doctoral dissertation]. The Chicago School of Professional Psychology.
  • Schepman, A., & Rodway, P. (2023). The general attitudes towards artificial intelligence scale (GAAIS): Confirmatory validation and associations with personality, corporate distrust, and general trust. International Journal of Human–Computer Interaction, 39(13), 2724–2741. https://doi.org/10.1080/10447318.2022.2085400
  • Simonovic, B., Vione, K. C., Fido, D., Stupple, E. J., Martin, J., & Clarke, R. (2022). The impact of attitudes, beliefs, and cognitive reflection on the development of critical thinking skills in online students. Online Learning, 26(2), 254–274.
  • So, H., & Kim, B. (2009). Learning about problem-based learning: Student teachers integrating technology, pedagogy and content knowledge. Australasian Journal of Educational Technology, 25, 101–116. https://doi.org/10.14742/AJET.1183
  • Suh, W., & Ahn, S. (2022). Development and validation of a scale measuring student attitudes toward artificial intelligence. SAGE Open, 12(2). https://doi.org/10.1177/21582440221100463
  • Özkan, E. K., Erdemir, N., & Coşkun, D. (2024). A systematic review of EFL teachers’ perspectives on artificial intelligence technologies. Ihlara Eğitim Araştırmaları Dergisi, 9(2), 150–168. https://doi.org/10.47479/ihead.1535035
  • Tapalova, O., & Zhiyenbayeva, N. (2022). Artificial intelligence in education: AIEd for personalised learning pathways. Electronic Journal of e-Learning. https://doi.org/10.34190/ejel.20.5.2597
  • Taşçı, S., & Tunaz, M. (2024). Opportunities and challenges in AI-assisted language teaching: Perceptions of pre-service EFL teachers. Araştırma ve Deneyim Dergisi, 9(2), 74–83. https://doi.org/10.47214/adeder.1575897
  • Tomić, B., Kijevcanin, A., Sevarac, Z., & Jovanovic, J. (2023). An AI-based approach for grading students’ collaboration. IEEE Transactions on Learning Technologies, 16, 292–305.
  • Vittorini, P., Menini, S., & Tonelli, S. (2020). An AI-based system for formative and summative assessment in data science courses. International Journal of Artificial Intelligence in Education, 31, 159–185. https://doi.org/10.1007/s40593-020-00230-2
  • Wang, Y. (2021). An improved machine learning and artificial intelligence algorithm for classroom management of English distance education. Journal of Intelligent & Fuzzy Systems, 40, 3477–3488. https://doi.org/10.3233/jifs-189385
  • Yetişensoy, O. (2024). Tomorrow's teachers and artificial intelligence: Exploring attitudes and perceptions of Turkish prospective social studies teachers. Eurasian Journal of Teacher Education, 5(1), 1–31. https://dergipark.org.tr/tr/download/article-file/3613703
  • Yetkin, R., & Özer-Altınkaya, Z. (2024). AI in the language classroom: Insights from pre-service English teachers. E-Learning and Digital Media. https://doi.org/10.1177/20427530241267011
  • Yılmaz-Virlan, A., & Tomak, B. (2024). AQ method study on Turkish EFL learners’ perspectives on the use of AI tools for writing: Benefits, concerns, and ethics. Language Teaching Research. https://doi.org/10.1177/13621688241308836
  • Younas, A., Subramanian, K., Haziazi, M., Hussainy, S., & Kindi, A. (2023). A review on implementation of artificial intelligence in education. International Journal of Research and Innovation in Social Science. https://doi.org/10.47772/ijriss.2023.7886
  • Zhang, B., & Dafoe, A. (2019). Artificial intelligence: American attitudes and trends. Center for the Governance of AI, Future of Humanity Institute, University of Oxford. https://dx.doi.org/10.2139/ssrn.3312874
  • Zhang, C., Schießl, J., Plößl, L., Hofmann, F., & Gläser-Zikuda, M. (2023). Acceptance of artificial intelligence among pre-service teachers: A multigroup analysis. International Journal of Educational Technology in Higher Education, 20(1), 49. https://doi.org/10.1186/s41239-023-00420-7
  • Zhou, C., & Hou, F. (2025). How do EFL teachers utilize AI tools in their language teaching? Theory and Practice in Language Studies. https://doi.org/10.17507/tpls.1502.10
There are 46 citations in total.

Details

Primary Language English
Subjects Instructional Technologies, Teacher Education and Professional Development of Educators, Educational Technology and Computing
Journal Section Articles
Authors

Pelin Derinalp 0000-0003-0537-2244

Melek Halife 0009-0000-5281-9147

Early Pub Date July 11, 2025
Publication Date July 24, 2025
Submission Date February 21, 2025
Acceptance Date July 7, 2025
Published in Issue Year 2025 Volume: 18 Issue: 3

Cite

APA Derinalp, P., & Halife, M. (2025). Pre-Service English as a Foreign Language Teachers’ Attitudes toward Artificial Intelligence. Journal of Theoretical Educational Science, 18(3), 609-629. https://doi.org/10.30831/akukeg.1644354
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