Original article | International Journal of Research in Teacher Education 2023, Vol. 14(3) 183-193
Selim Soner Sütçü & Elif Sütçü
pp. 183 - 193 | DOI: https://doi.org/10.29329/ijrte.2023.598.12 | Manu. Number: MANU-2309-30-0008
Published online: September 30, 2023 | Number of Views: 122 | Number of Download: 338
Abstract
The field of Artificial Intelligence in Education (AIED) has undergone tremendous developments during the last decades and with its latest affordances, it has become popular topic of educators as in all walks of life. Diverse Artificial Intelligence (AI) technologies are being employed more and more often in a range of educational situations and domains, including language learning, in order to accomplish a number of learning goals. However, this intensive and rapid emergence has raised some uncertainties about the effective adoption of AI tools into their language classes by educators. In this respect, this study addresses the attitudes and opinions of English teachers in order to shed light on some uncertainties on this issue. In this study, case study design was employed to determine the general attitudes of English teachers towards AI. The research's findings indicated that instructors are generally optimistic about the acceptance and adoption of AI applications in language instruction and they believe that their usage could contribute to language learning, but they have some reservations though.
Keywords: Artificial intelligence, language learning, teachers’ attitudes.
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Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50, 179–211. https:// doi. org/ 10. 1016/ 0749- 5978(91) 90020-T Allport, G. (1967). “Attitudes,” In Readings in attitude theory and measurement, M. Fishbein, Ed., Wiley. Baker, T., & Smith, L. (2019). Educ-AI-tion rebooted? Exploring the future of artificial intelligence in schools and colleges. Barros, S. D. S., & Elia, M. F. (1998). Physics teacher’s attitudes: How do they affect the reality of the classroom and models for change? In A. Tiberghien, L. E. Josem, & J. Barojas (Eds.), Connecting research in physics education with teacher education. The International Commission on Physics Education. Vol_1. Blazar, D. (2018). Validating teacher effects on students’ attitudes and behaviors: Evidence from random assignment of teachers to students. Education Finance and Police, 13(3), 281–309. https:// doi. org/ 10.1162/ edfp_a_ 00251 Blinder, A. S. (2006). Offshoring: the next industrial revolution?. Foreign affairs, 113-128 Bogdan, R., & Biklen, S. K. (2006). Qualitative research for education: An introduction to theories and methods (5th ed.). Pearson Education, Inc. Borchardt, F. and Page, E. (1994) Let computers use the past to predict the future. Paper presented at the Language Aptitude Invitational Symposium, CALL Arlington. Bowman, M., Vongkulluksn, V., Jiang, Z., & Xie, K. (2020). Teachers’ exposure to professional development and the quality of their instructional technology use: The mediating role of teachers’ value and ability beliefs. Journal of Research on Technology in Education, 1–17. https://doi.org/10.1080/15391523.2020.1830895 Council of Europe (2023, January 7). History of Artificial Intelligence. https://www.coe.int/en/web/artificial-intelligence/history-of-ai Debreli, E. (2012). Change in beliefs of pre‐service teachers about teaching and learning English as a foreign language throughout an undergraduate pre‐service teacher training program. Procedia‐Social and Behavioral Sciences, 46, 367‐373. https://doi.org/10.1016/j.sbspro.2012.05.124 Deeva, G., Bogdanova, D., Serral, E., Snoeck, M., & De Weerdt, J. (2020). A review of automated feedback systems for learners: Classification framework, challenges and opportunities. Computers & Education, 162, 104094. Divekar, R. R., Drozdal, J., Chabot, S., Zhou, Y., Su, H. , Chen, Y., Zhu, H., Hendler, J. A. & Braasch, J. (2022) Foreign language acquisition via artificial intelligence and extended reality: design and evaluation, Computer Assisted Language Learning, 35:9, 2332-2360, DOI: 10.1080/09588221.2021.1879162 Dodigovic, M. (2007) Artificial Intelligence and Second Language Learning: An Efficient Approach to Error Remediation, Language Awareness, 16:2, 99-113, DOI: 10.2167/la416.0 Farjon, D., Smits, A., & Voogt, J. (2019). Technology integration of pre-service teachers explained by attitudes and beliefs, competency, access, and experience. Computers & Education, 130, 81–93.https://doi.org/10.1016/j.compedu.2018.11.010 Fernández-Batanero, J. M., Román-Graván, P., Reyes-Rebollo, M. M., and Montenegro-Rueda, M. (2021). Impact of educational technology on teacher stress and anxiety: a literature review. Int. J. Environ. Res. Public Health 18:548. doi: 10.3390/ijerph18020548 Haristiani N. (2019). Artificial Intelligence (AI) Chatbot as Language Learning Medium: An inquiry Vol.1387 J. Phys.: Conf. Ser. IOP Publishing Ltd. https://doi.org/10.1088/1742-6596/1387/1/012020 Howe, L., & Krosncik, J. (2017). Attitude strength. Annual Review of Psychology, 68, 327–351. https://doi. org/ 10. 1146/ annur ev- psych- 122414- 033600 Istenic, A., Bratko, I., & Rosanda, V. (2021). Are pre-service teachers disinclined to utilize embodied humanoid social robots in the classroom? British Journal of Educational Technology, 52(6), 2340–2358. https:// doi. org/ 10. 1111/ bjet. 13144 Jones, C. (2018). Best way to improve student math scores? Change teachers’ attitudes, study says. G. Knezek and R. Christensen, “Extending the will, skill, tool model of technology integration: Adding pedagogy as a new model construct,” In J. Comput. in Higher Educ., vol. 28, no. 3, 2016, pp. 307–325, doi: 10.1007/s12528-016-9120-2. Kaban, A. L., & Boy Ergul, I. (2020). Teachers’ Attitudes Towards the Use of Tablets in Six EFL Classrooms. In L. Tomei & E. Podovšovnik (Eds.), Advances in Educational Technologies and Instructional Design. Examining the Roles of Teachers and Students in Mastering New Technologies (pp. 284–298). IGI Global. https://doi.org/10. 4018/ 978-1-7998-2104-5. ch015 Kaya, F., Aydin, F., Schepman, A., Rodway, P., Yetişensoy, O., & Kaya, M. D., (2022). The Roles of Personality Traits, AI Anxiety, and Demographic Factors in Attitudes toward Artificial Intelligence. International Journal Of Human-Computer Interaction 1-17. Kim, Na-Young, Cha, Yoonjung, & Kim, Hea-Suk. (2019). Future English learning: Chatbots and artificial intelligence. Multimedia-Assisted Language Learning, 22(3), 32-53. Leslie D., Burr C., Aitken M., Cowls J., Katell M. and Briggs M. (2021), “Artificial intelligence, human rights, democracy, and the rule of law: a primer”, Council of Europe, www.turing.ac.uk/research/publications/ai-human-rights-democracy-and-rulelaw-primer-prepared-council-europe Lin, M. P. C., & Chang, D. (2020). Enhancing post-secondary writers’ writing skills with a chatbot. Journal of Educational Technology & Society, 23(1), 78–92. Lee, I., & Perret, B. (2022). Preparing High School Teachers to Integrate AI Methods into STEM Classrooms. Proceedings of the AAAI Conference on Artificial Intelligence, 36(11), 12783-12791. https://doi.org/10.1609/aaai.v36i11.21557 Luckin, Rose; Holmes, Wayne; Griffiths, Mark and Forcier, Laurie B. (2016). Intelligence Unleashed: An argument for AI in Education. Pearson Education J. Loeckx, (2016). Blurring boundaries in education: context and impact of MOOCs. The International Review of Research in Open and Distributed Learning, 17(3), pp. 92–121, 2016. Kannan, J. & Munday, P. (2018). New trends in second language learning and teaching through the lens of ICT, networked learning, and artificial intelligence. In Fernández Juncal, C. & N. Hernández Muñoz (Eds.). Vías de transformación en la enseñanza de lenguas con mediación tecnológica. Círculo de Lingüística Aplicada a la Comunicación, 76, 13-30 http://dx.doi.org/10.5209/CLAC.62495 McCarthy, J., Minsky, M., Rochester, N. & Shanno, C. (2006). A Proposal for the Dartmouth Summer Research Project on Artificial Intelligence. AI Magazine, 27 (4), 12–14. Mercader, C. & Gairín, J. (2020). University teachers' perception of barriers to the use of digital technologies: the importance of the academic discipline. International Journal of Educational Technology in Higher Education, 17(4), https://doi.org/10.1186/s41239-020-0182-x Nilsson, Nils. (2010). The quest for artificial intelligence: A history of ideas and achievements. Cambridge University Press Popenici, S.A.D.; Kerr, S. (2017). Exploring the impact of artificial intelligence on teaching and learning in higher education. Res. Pract.Technol. Enhanc. Learn, 12, 22. Pozas M. and Letzel, V. (2021).“‘Do you think you have what it takes?’ – Exploring predictors of pre‑service teachers’ prospective ICT use,” In Technol., Know. & Learn., doi: 10.1007/s10758-021-09551-0. Ryan, G. W., & Bernard, H. R. (2003). Techniques to Identify Themes. Field Methods, 15(1), 85-109. https://doi.org/10.1177/1525822X02239569 Pokrivčáková, S. (2019). “Preparing teachers for the application of AIpowered technologies in foreign language education”, Journal of Language and Cultural Education. Shang, J.J., Jong, M.S., Lee, F.L., Lee, J.H., Wong, M.K., Luk, E.T., & Cheung, K.K. (2006). Using the "Record-Replay" Function for Elaboration of Knowledge in Educational Games. IEEE International Conference on Consumer Electronics. Schepman, A., & Rodway, P. (2020). Initial validation of the general attitudes towards Artificial Intelligence Scale. Computers in Human Behavior Reports, 1, 100014. https://doi.org/10.1016/j.chbr.2020.100014 Sharma, U., Forlin, C., Loreman, T., & Earle, C. (2006). Pre‐service teachers' attitudes, concerns and sentiments about inclusive education: An international comparison of novice pre‐service teachers. International Journal of Special Education, 21(2), 80-93. Shum, SJB; Luckin, R; (2019) Learning analytics and AI: Politics, pedagogy and practices. British Journal of Educational Technology , 50 (6) pp. 2785-2793. 10.1111/bjet.12880. Strobl, C., Ailhaud, E., Benetos, K., Devitt, A., Kruse, O., Proske, A., & Rapp, C. (2019). Digital support for academic writing: A review of technologies and pedagogies. Computers & Education, 131, 33–48. https://doi.org/10.1016/j.compedu.2018.12.005 Ulug, M., Ozden, M. S., & Eryilmaz, A. (2011). The effects of teachers’ attitudes on students’ personality and performance. Procedia-Social and Behavioral Sciences, 30, 738–742. https:// doi. org/ 10. 1016/j.sbspro. 2011. 10. 144 UNICEF (2021), Policy guidance on AI for children, available at www.unicef.org/globalinsight/media/2356/file/UNICEF-Global-Insight-policy-guidance-AI-children-2.0-2021.pdf UNESCO, (2019). The Challenge and Opportunities of Artificial Intelligence in Education. Paris: The United Nations Educational, Scientific and Cultural Organization. Vogel, T., & Wanke, M. (2016). Attitudes and attitude change. Routledge. Wijekumar, K. K., Meyer, B. J., & Lei, P. (2013). High-fidelity implementation of web-based intelligent tutoring system improves fourth and fifth graders content area reading comprehension. Computers & Education, 68, 366–379. Woolf, B. P., Lane, H. C., Chaudhri, V. K., & Kolodner, J. L. (2013). AI grand challenges for education. AI Magazine, 34(4), 66–84. https://doi.org/10.1609/aimag.v34i4.2490 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. |