Digital Echoes: Crafting Chinese EFL Teacher Identity in the Era of AI-Enhanced Instruction—A Qualitative Exploration

Authors

  • Qing Zhou

    1 Faculty of Education, Universiti Kebangsaan Malaysia, Bangi 43600, Selangor, Malaysia; 2 Foreign Language Department, Science and Technology College GanNan Normal University, Ganzhou 341000, China

  • Harwati Hashim

    Faculty of Education, Universiti Kebangsaan Malaysia, Bangi 43600, Selangor, Malaysia

  • Nur Ainil Sulaiman

    Faculty of Education, Universiti Kebangsaan Malaysia, Bangi 43600, Selangor, Malaysia

DOI:

https://doi.org/10.30564/fls.v6i5.6864
Received: 12 July 2024 | Revised: 4 August 2024 | Accepted: 7 August 2024 | Published Online: 23 October 2024

Abstract

This study examines the impact of artificial intelligence (AI) integration on the professional identities of Chinese tertiary English as a Foreign Language (EFL) teachers. It explores how these educators perceive and adapt to the incorporation of AI tools into their teaching practices, focusing on both the opportunities and challenges encountered. Through qualitative analysis of semi-structured interviews with 16 tertiary EFL teachers, the study identifies key factors influencing their professional identities, including institutional support, professional development, peer influence, personal attitudes towards technology, and ethical considerations. The findings indicate that AI integration enhances personalized learning and reduces the burden of administrative tasks. However, it also challenges teachers to reshape their roles and manage both technological and ethical complexities effectively. The study highlights the necessity for ongoing professional development and robust institutional support to effectively integrate AI in educational settings, ensuring it enhances rather than undermines the teaching and learning process.

Keywords:

Artificial Intelligence; EFL Teaching; Professional Identity; Educational Technology; AI in Education

References

Crompton, H., Burke, D., 2023. Artificial intelligence in higher education: The state of the field. International Journal of Educational Technology in Higher Education. 20(22), 1–22. DOI: https://doi.org/10.1186/s41239-023-00392-8

Tapalova, O., Zhiyenbayeva, N., 2022. Artificial intelligence in education: AIEd for Personalised Learning Pathways. Electronic Journal of E-learning. 20(5), 639–653. DOI: https://doi.org/10.34190/ejel.20.5.2597

Jiang, R., 2022. How does artificial intelligence empower EFL teaching and learning nowadays? A review on artificial intelligence in the EFL context. Frontiers in Psychology. 13, 1–8. DOI: https://doi.org/10.3389/fpsyg.2022.1049401

Xu, Z., Wijekumar, K., Ramirez, G., et al., 2019. The effectiveness of intelligent tutoring systems on K-12 students' reading comprehension: A meta-analysis. British Journal of Educational Technology. 50(6), 3119–3137. DOI: https://doi.org/10.1111/bjet.12758

Yang, H., Kim, H., Lee, J.H., et al., 2022. Implementation of an AI chatbot as an English conversation partner in EFL speaking classes. ReCALL. 34(3), 327–343. DOI: https://doi.org/10.1017/S0958344022000039

Liu, Y., Huang, L.P., 2020. The phenomenon and countermeasure of “path-dependence” in college English education reform. Progress in Education. 10(6), 1085–1089 (in Chinese). DOI: https://doi.org/10.12677/AE.2020.106183

Chen, X., Zou, D., Xie, H., et al., 2022. Two decades of artificial intelligence in education. Educational Technology & Society. 25(1), 28–47. Available from: https://www.jstor.org/stable/48647028

Meihami, H., Esfandiari, R., 2021. Exploring EFL teachers' professional identity development in a CALL teacher preparation program. The JALT CALL Journal. 17(2), 135–157. DOI: https://doi.org/10.29140/jaltcall.v17n2.404

Diasti, K.S., 2021. Constructing professional identity: Investigating stress factors and resilience experienced by EFL novice teachers. Scholaria: Jurnal Pendidikan dan Kebudayaan. 11(1), 1–10. DOI: https://doi.org/10.24246/j.js.2021.v11.i1.p1-10

Kim, J., Lee, H., Cho, Y.H., 2022. Learning design to support student-AI collaboration: Perspectives of leading teachers for AI in education. Education and Information Technologies. 27, 6069–6104. DOI: https://doi.org/10.1007/s10639-021-10831-6

Zhang, C., Schießl, J., Plößl, L., et al., 2023. Acceptance of artificial intelligence among pre-service teachers: A multigroup analysis. International Journal of Educational Technology in Higher Education. 20(49), 1–22. DOI: https://doi.org/10.1186/s41239-023-00420-7

Beijaard, D., Meijer, P.C., Verloop, N., 2004. Reconsidering research on teachers’ professional identity. Teaching and teacher education. 20(2), 107–128. DOI: https://doi.org/10.1016/j.tate.2003.07.001

Pennington, M.C., Richards, J.C., 2016. Teacher identity in language teaching: Integrating personal, contextual, and professional factors. RELC Journal. 47(1), 5–23. DOI: https://doi.org/10.1177/0033688216631219

Wenger, E., 1998. Communities of practice: Learning, meaning, and identity. Cambridge University Press: Cambridge. pp. 1–336. DOI: https://doi.org/10.1017/CBO9780511803932

Gee, J.P., 2000. Chapter 3: Identity as an analytic lens for research in education. Review of Research in Education. 25(1), 99–125. DOI: https://doi.org/10.3102/0091732x025001099

Sachs, J., 2005. Teacher education and the development of professional identity: Learning to be a teacher. In: Kompf, M., Denicolo, P., (eds.). Connecting policy and practice: Challenges for teaching and learning in schools and universities. Routledge, Taylor and Francis Group: London. pp. 5–21. DOI: https://doi.org/10.4324/9780203012529

Yazan, B., 2023. A conceptual framework to understand language teacher identities. Second Language Teacher Education. 1(2), 185–208. DOI: https://doi.org/10.1558/slte.24908

Akgun, S., Greenhow, C., 2022. Artificial intelligence in education: Addressing ethical challenges in K-12 settings. AI and Ethics. 2, 431–440. DOI: https://doi.org/10.1007/s43681-021-00096-7

Chen, X., Xie, H., Hwang, G.-J., 2020. A multi-perspective study on Artificial Intelligence in Education: Grants, conferences, journals, software tools, institutions, and researchers. Computers and Education: Artificial Intelligence. 1, 1–11. DOI: https://doi.org/10.1016/j.caeai.2020.100005

Gupta, K.P., Bhaskar, P., 2020. Inhibiting and motivating factors influencing teachers’ adoption of AI-based teaching and learning solutions: Prioritization using analytic hierarchy process. Journal of Information Technology Education, Research. 19, 693–723. DOI: https://doi.org/10.28945/4640

Hieu, H.H., Thao, L.T., 2024. Exploring the impact of AI in language education: Vietnamese EFL teachers’ views on using ChatGPT for fairy tale retelling tasks. International Journal of Learning, Teaching and Educational Research. 23(3), 486–503. DOI: https://doi.org/10.26803/ijlter.23.3.24

Tiwari, H.P., 2024. Artificial intelligence in the classroom: Revolutionizing English language teaching. Journal of English Teaching and Linguistics Studies. 6(1), 42–59. DOI: https://doi.org/10.55215/jetli.v6i1.9757

Varghese, M., Morgan, B., Johnston, B., et al., 2005. Theorizing language teacher identity: Three perspectives and beyond. Journal of Language, Identity, and Education. 4(1), 21–44. DOI: https://doi.org/10.1207/s15327701jlie0401_2

Tsui, A.B.M., 2011. Complexities of identity formation: A narrative inquiry of an EFL Teacher. TESOL Quarterly. 41(4), 657–680. Available from: http://www.jstor.org/stable/40264401

Canagarajah, A.S., 2012. Teacher development in a global profession: An autoethnography. TESOL Quarterly. 46(2), 258–279. DOI: https://doi.org/10.1002/tesq.18

Salinas, D., 2017. EFL teacher identity: Impact of macro and micro contextual factors in education reform frame in Chile. World Journal of Education. 7(6), 1–11. DOI: https://doi.org/10.5430/wje.v7n6p1

Goodson, I., Gill, S., 2014. Critical narrative as pedagogy. Bloomsbury Publishing USA.

Yazici, E.A., Atay, D., 2023. ICT Transformation in Education: Its Impact on Language Teachers’ Professional Identities. Iranian Journal of Language Teaching Research. 11(1), 141–156. DOI: https://doi.org/10.30466/ijltr.2023.121276

Tan, S., 2023. Harnessing artificial intelligence for innovation in education. In: Rajaram, K. Learning intelligence: Innovative and digital transformative learning strategies: Cultural and social engineering perspectives. Springer: Singapore. pp. 335–363. DOI: https://doi.org/10.1007/978-981-19-9201-8_8

Bahari, A., 2022. Teacher identity in technology-assisted language learning: Challenges and affordances. E-Learning and Digital Media. 19(4), 396–420. DOI: https://doi.org/10.1177/20427530221092855

Hennink, M., Hutter, I., Bailey, A., 2020. Qualitative research methods, 2nd ed. Sage: London. pp. 1–376.

Whitehead, D., Ferguson, C., 2020. Data collection and sampling in qualitative research. In: Whitehead, D., LoBiondo-Wood, G., Ferguson, C., Haber, J. (eds.). Nursing and midwifery research methods and appraisal for evidence-based practice, 6th ed. Elsevier: Sydney. pp. 118–135.

Scanlan, C.L., 2020. Preparing for the unanticipated: Challenges in conducting semi-structured, in-depth interviews. Sage Research Methods. DOI: https://doi.org/10.4135/9781529719208

Belina, A., 2023. Semi-structured interviewing as a tool for understanding informal civil society. Voluntary Sector Review. 14(2), 331–347. DOI: https://doi.org/10.1332/204080522X16454629995872

Rosairo, H.S.R., 2023. Thematic analysis in qualitative research. Journal of Agricultural Sciences–Sri Lanka. 18(3), 1–3. DOI: https://doi.org/10.4038/jas.v18i3.10526

Bhandari, P., 2022. Triangulation in Research | guide, types, examples. Scribbr. Available from: https://www.scribbr.com/methodology/triangulation/ (cited 30 July 2024).

Hales, D., Peersman, G., Rugg, D., et al., 2010. An introduction to triangulation. UNAIDS: Switzerland. pp. 1–79. Available from: https://www.unaids.org/sites/default/files/sub_landing/files/10_4-Intro-to-triangulation-MEF.pdf

Crompton, H., Burke, D., 2018. The use of mobile learning in higher education: A systematic review. Computers & Education. 123, 53–64. DOI: https://doi.org/10.1016/j.compedu.2018.04.007

Ayanwale, M.A., Adelana, O.P., Odufuwa, T.T., 2024. Exploring STEAM teachers’ trust in AI-based educational technologies: a structural equation modelling approach. Discover Education. 3(44), 1–22. DOI: https://doi.org/10.1007/s44217-024-00092-z

Luan, H., Geczy, P., Lai, H., et al., 2020. Challenges and future directions of big data and artificial intelligence in education. Frontiers in Psychology. 11, 1–11. DOI: https://doi.org/10.3389/fpsyg.2020.580820

Chen, L., Chen, P., Lin, Z., 2020. Artificial intelligence in education: A review. IEEE Access. 8, 75264–75278. DOI: https://doi.org/10.1109/ACCESS.2020.2988510

Chukwubueze, N.V., Vinella, O., 2024. Artificial intelligence and future of secondary education in delta state: Implications for educational administration. Journal of Asian Scientific Research. 14(3), 277–288. DOI: https://doi.org/10.55493/5003.v14i3.5073

Zhao, L., Wu, X., Luo, H., 2022. Developing AI literacy for primary and middle school teachers in China: Based on a structural equation modeling analysis. Sustainability. 14(21), 1–16. DOI: https://doi.org/10.3390/su142114549

Walter, Y., 2024. Embracing the future of Artificial Intelligence in the classroom: The relevance of AI literacy, prompt engineering, and critical thinking in modern education. International Journal of Educational Technology in Higher Education. 21(15), 1–29. DOI: https://doi.org/10.1186/s41239-024-00448-3

Oyasola, S.O., 2022. Effectiveness of peer-collaboration learning strategy and 21st century skill knowledge on pre-service teachers’ academic achievement in integrated science in Nigerian colleges of education. Journal of Science and Science Education. 6(1), 14–22. DOI: https://doi.org/10.24246/josse.v6i1p14-22

Abulibdeh, A., Zaidan, E., Abulibdeh, R., 2024. Navigating the confluence of artificial intelligence and education for sustainable development in the era of industry 4.0: Challenges, opportunities, and ethical dimensions. Journal of Cleaner Production. 437. 1–15. DOI: https://doi.org/10.1016/j.jclepro.2023.140527

Elshamly, A., Gameel, Z.A.A., 2023. AI and BDA impact on stakeholders' responses to education technology adoption. Migration Letters. 20(8), 1041–1067. DOI: https://doi.org/10.59670/ml.v20i8.5738

Stadler-Altmann, U., Schumacher, S., 2022. I’m not a robot - report on the implementation of AI in early childhood education. Education and New Developments. 1, 1–5. DOI: https://doi.org/10.36315/2022v1end033

Jonker, H., März, V., Voogt, J., 2020. Curriculum flexibility in a blended curriculum. Australasian Journal of Educational Technology. 36(1), 68–84. DOI: https://doi.org/10.14742/ajet.4926

Musa, S., Nurhayati, S., 2024. Educators’ resilience amidst digital era challenges: Case study in Indonesia. Journal of Electrical Systems. 20(4s), 832–840. DOI: https://doi.org/10.52783/jes.2121

Parycek, P., Schmid, V., Novak, A.S., 2023. Artificial intelligence (AI) and automation in administrative procedures: Potentials, limitations, and framework conditions. Journal of the Knowledge Economy. 15, 8390–8415. DOI: https://doi.org/10.1007/s13132-023-01433-3

Downloads

How to Cite

Zhou, Q., Hashim, H., & Sulaiman, N. A. (2024). Digital Echoes: Crafting Chinese EFL Teacher Identity in the Era of AI-Enhanced Instruction—A Qualitative Exploration. Forum for Linguistic Studies, 6(5), 32–50. https://doi.org/10.30564/fls.v6i5.6864