Skip to main content Accessibility help
×
  1. Home
  2. Books
  3. Generative Artificial Intelligence and Language Teaching
  • Cited by 10
    • An Online Appendix for this Element is available here.
      • Show more authors
      • You may already have access via personal or institutional login
    • Select format
    • Publisher:
      Cambridge University Press
      Publication date:
      26 June 2025
      24 July 2025
      ISBN:
      9781009618823
      9781009618861
      9781009618816
      DOI:
      https://doi.org/10.1017/9781009618823
      Dimensions:
      (229 x 152 mm)
      Weight & Pages:
      0.274kg, 94 Pages
      Dimensions:
      (229 x 152 mm)
      Weight & Pages:
      0.149kg, 94 Pages
      • Subjects:
      Teacher training and professional development, Education policy, strategy and reform, Education
      Series:
      Elements in Generative AI in Education
    You may already have access via personal or institutional login
    • Selected: Digital
    Add to cart View cart Buy from Cambridge.org
    Subjects:
    Teacher training and professional development, Education policy, strategy and reform, Education
    Series:
    Elements in Generative AI in Education
    Information

    Book description

    The development of Generative Artificial Intelligence (GenAI) has led to intense wonder, surprise, excitement, and concern within the language teaching profession. These tools offer the potential to assist language teachers in helping their learners achieve their language learning goals, and at the same time, risk disrupting language teaching and learning processes, the teaching profession, and possibly the instrumental needs to learn foreign languages. This Element provides an accessible introduction and guide to the use of GenAI for language teaching. It aims to facilitate language teachers' development of the professional knowledge and skills they need to use GenAI responsibly, ethically and effectively. The Element It is a valuable resource for pre-service and in-service language teachers of all experience levels. Each section includes helpful tips and questions for reflection to get teachers started with GenAI while ensuring they engage critically and responsibly with these tools. Evidence-informed approaches are promoted throughout the Element.

    References

    References

    Al-khresheh, M. H. (2024). Bridging technology and pedagogy from a global lens: Teachers’ perspectives on integrating ChatGPT in English language teaching. Computers and Education: Artificial Intelligence, 6, 100218. https://doi.org/10.1016/j.caeai.2024.100218.
    Ali, O., Murray, P. A., Momin, M., Dwivedi, Y. K., & Malik, T.. (2024). The effects of artificial intelligence applications in educational settings: Challenges and strategies. Technological Forecasting and Social Change, 199, 123076.10.1016/j.techfore.2023.123076
    Bai, L., Liu, X., & Su, J. (2023). ChatGPT: The cognitive effects on learning and memory. Brain-X, 1(3), e30. https://doi.org/10.1002/brx2.30.
    Baker, W. (2012). From cultural awareness to intercultural awareness: Culture in ELT. ELT Journal, 66, 62–70. https://doi.org/10.1093/ELT/CCR017.
    Barrot, J. S. (2020). Integrating technology into ESL/EFL writing through Grammarly. RELC Journal, 53(3), 764–768. https://doi.org/10.1177/0033688220966632.
    Barrot, J. S. (2023). Using ChatGPT for second language writing: Pitfalls and potentials. Assessing Writing, 57, 100745. https://doi.org/10.1016/j.asw.2023.100745.
    Bauml, M. (2014). Collaborative lesson planning as professional development for beginning primary teachers. The New Educator, 10(3), 182–200.10.1080/1547688X.2014.925741
    Bax, S. (2003). CALL: Past, present, and future. System, 31(1), 13–28.10.1016/S0346-251X(02)00071-4
    Birss, D. (2023) How to research and write using generative AI tools. LinkedIn Learning, formerly Lynda.com. www.linkedin.com/learning/how-to-research-and-write-using-generative-ai-tools.
    Bonner, E., Lege, R. & Frazier, E. (2023). Large language model-based artificial intelligence in the language classroom: Practical ideas for teaching. Teaching English with Technology, 23(1), 23–41. https://doi.org/10.56297/bkam1691/wieo1749.
    Brown, T., Mann, B., Ryder, N., Subbiah, M., Kaplan, J. D., Dhariwal, P., & Amodei, D. (2020). Language models are few-shot learners. Advances in Neural Information Processing Systems, 33, 1877–1901. https://proceedings.neurips.cc/paper_files/paper/2020.
    Cain, W. (2023). Prompting change: Exploring prompt engineering in large language model AI and its potential to transform education. TechTrends, 68(1), 47–57. https://doi.org/10.1007/s11528-023-00896-0.
    Cao, L. & Dede, C. (2023). Navigating a World of Generative AI: Suggestions for Educators. The Next Level Lab at Harvard Graduate School of Education. https://bpb-us-e1.wpmucdn.com/websites.harvard.edu/dist/a/108/files/2023/08/Cao_Dede_final_8.4.23.pdf.
    Chan, C. K. Y., & Colloton, T. (2024). Generative AI in Higher Education: The ChatGPT Effect. Routledge.10.4324/9781003459026
    Chen, Z., Liu, T., & Liu, X. (2024). Twee: Artificial intelligence assistant to generate versatile materials for language education. RELC Journal. https://doi.org/10.1177/00336882241282471.
    Chiu, T. K., Moorhouse, B. L., Chai, C. S., & Ismailov, M. (2023). Teacher support and student motivation to learn with artificial intelligence (AI) based chatbot. Interactive Learning Environments, 32(7), 3240–3256. https://doi.org/10.1080/10494820.2023.2172044.
    Crompton, H., & Burke, D. (2024). The educational affordances and challenges of ChatGPT: State of the field. TechTrends, 68, 380–392. https://doi.org/10.1007/s11528-024-00939-0.
    Darvin, R. (2025). The need for critical digital literacies in generative AI-mediated L2 writing. Journal of Second Language Writing, 67, 101186. https://doi.org/10.1016/j.jslw.2025.101186.
    Dewey, J. (1933). How We Think: A Restatement of the Relation of Reflective Thinking to the Educative Process. D. C. Health and Company.
    Dooley, M., Thrasher, T., & Sadler, R. (2023). ‘Whoa! incredible!’: Language learning experiences in virtual reality. RELC Journal, 54(2), 321–339. https://doi.org/10.1177/00336882231167610.
    Draxler, F., Werner, A., Lehmann, F., Hoppe, M., Schmidt, A., Buschek, D., & Welsch, R. (2024). The AI ghostwriter effect: When users do not perceive ownership of AI-generated text but self-declare as authors. ACM Transactions on Computer-Human Interaction, 31(2), 1–40. https://doi.org/10.1145/3637875.
    Dwivedi, Y. K., Kshetri, N., Hughes, L., Slade, E. L., Jeyaraj, A., Kar, A. K., Wright, R. (2023). Opinion paper: ‘So what if ChatGPT wrote it?’ Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy. International Journal of Information Management, 71, 102642. https://doi.org/10.1016/j.ijinfomgt:.2023.102642.
    Farrokhnia, M., Banihashem, S. K., Noroozi, O., & Wals, A. (2023). A SWOT analysis of ChatGPT: Implications for educational practice and research. Innovations in Education and Teaching International, 61(3), 460–474. https://doi.org/10.1080/14703297.2023.2195846.
    Fryer, L. K., Coniam, D., Carpenter, R., & Lăpușneanu, D. (2020). Bots for language learning now: Current and future directions. Language, Learning and Technology, 24(2), 8–22.
    Fui-Hoon Nah, F., Zheng, R., Cai, J., Siau, K., & Chen, L. (2023). Generative AI and ChatGPT: Applications, challenges, and AI-human collaboration. Journal of Information Technology Case and Application Research, 25(3), 277–304.10.1080/15228053.2023.2233814
    Godwin-Jones, R. (2022). Partnering with AI: Intelligent writing assistance and instructed language learning. Language Learning & Technology, 26(2), 5–24. http://doi.org/10125/73474.
    Godwin-Jones, R. (2024). Distributed agency in second language learning and teaching through generative AI. Language Learning & Technology, 28(2), 5–30. https://doi.org/10125/73570.
    Gruber, P. (2023) Using ChatGPT for efficient data analysis with R. Instats Inc. https://doi.org/10.61700/XWWIQWCMK4X0R469.
    Harmer, J. (2015). The Practice of English Language Teaching. Pearson.
    Hockly, N. (2023). Artificial intelligence in English language teaching: The good, the bad and the ugly. RELC Journal, 54(2): 445–451. https://doi.org/10.1177/00336882231168504.
    Hong, W. C. H. (2023). The impact of ChatGPT on foreign language teaching and learning: Opportunities in education and research. Journal of Educational Technology and Innovation, 5(1), 37–45. https://jeti.thewsu.org/index.php/cieti/article/view/103.
    Instefjord, E. J., & Munthe, E. (2017). Educating digitally competent teachers: A study of integration of professional digital competence in teacher education. Teaching and Teacher Education, 67, 37–45.10.1016/j.tate.2017.05.016
    Jacobs, H. H., & Fisher, M. (2023). Prompt literacy: A key for AI-based learning. www.ascd.org/el/articles/prompt-literacy-a-key-for-ai-based-learning.
    Javier, D. R. C., & Moorhouse, B. L. (2023). Developing secondary school English language learners’ productive and critical use of ChatGPT. TESOL Journal, (e755), 1–9.
    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, 5873–15892. https://doi.org/10.1007/s10639-023-11834-1.
    Kasneci, E., Seßler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., & Kasneci, G. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences, 103, 102274.10.1016/j.lindif.2023.102274
    Kerr, P. (2014). Translation and Own-Language Activities. Cambridge University Press.10.1017/9781009024815
    Knoth, N., Tolzin, A., & Janson, A. (2024). AI literacy and its implications for prompt engineering strategies. Computers and Education: Artificial Intelligence, 49(4), 100225. https://doi.org/10.1016/j.caeai.2024.100225.
    Kohnke, L. (2023). Using Technology to Design ESL/EFL Microlearning Activities. Springer.10.1007/978-981-99-2774-6
    Kohnke, L., & Jarvis, A. (2023). Developing infographics for English for academic purposes courses. TESOL Journal, 14, e675. https://doi.org/10.1002/tesj.6753-197.
    Kohnke, L., Foung, D., & Zou, D. (2024). Microlearning: A new normal for flexible teacher professional development in online and blended learning. Education and Information Technologies, 29(4), 4457–4480.10.1007/s10639-023-11964-6
    Kohnke, L., Foung, D., Zou, D., & Jiang, M. (2024). Creating the conditions for professional digital competence through microlearning. Educational Technology & Society, 27(1), 18.
    Kohnke, L., & Moorhouse, B. L. (2024). An exploration of microlearning as continuous professional development for English language teachers: Initial findings and insights. Open Learning: The Journal of Open, Distance and e-Learning, 1–17.10.1080/02680513.2024.2362649
    Kohnke, L., Moorhouse, B. L., & Zou, D. (2023). Using ChatGPT for language teaching and learning. RELC Journal, 54(2), 537–550. https://doi.org/10.1177/00336882231162868.
    Kohnke, L. & Zou, D. (2024). The role of ChatGPT in enhancing English teaching: A paradigm shift in lesson planning and instructional practice. Educational Technology and Society, 28(3), 4–20.
    König, J., Jäger-Biela, D. J., & Glutsch, N. (2020). Adapting to online teaching during Covid-19 school closure: Teacher education and teacher competence effects among early career teachers in Germany. European Journal of Teacher Education, 43(4), 608–622.10.1080/02619768.2020.1809650
    Kostka, I., & Toncelli, R. (2023). Exploring applications of ChatGPT to English language teaching: Opportunities, challenges, and recommendations. Teaching English as a Second or Foreign Language, 27(3). https://doi.org/10.55593/ej.27107int.
    Lee, Y. J. (2020). The long-term effect of automated writing evaluation feedback on writing development. English Teaching, 75(1), 67–92.10.15858/engtea.75.1.202003.67
    Lee, S., & Jeon, J. (2024). Enhancing pre-service EFL teachers’ TPACK through chatbot-integrated lesson planning projects. Language Learning & Technology, 28(1), 1–20. https://hdl.handle.net/10125/73598.
    Lim, W. M., Gunasekara, A., Pallant, J. L., Pallant, J. I., & Pechenkina, E. (2023). Generative AI and the future of education: Ragnarök or reformation? A paradoxical perspective from management educators. International Journal of Management in Education, 21(2), 100790. https://doi.org/10.1016/j.ijme.2023.100790.
    Lo, L. S. (2023). The CLEAR path: A framework for enhancing information literacy through prompt engineering. The Journal of Academic Librarianship, 49(4), 102720. https://doi.org/10.1016/j.acalib.2023.102720.
    Lucchi, N. (2023). ChatGPT: A case study on copyright challenges for generative artificial intelligence systems. European Journal of Risk Regulation, 1–23. https://doi.org/10.1017/err.2023.59.
    Lund, B. D., Wang, T., Mannuru, N. R., Nie, B., Shimray, S., & Wang, Z. (2023). ChatGPT and a new academic reality: Artificial intelligence‐written research papers and the ethics of the large language models in scholarly publishing. Journal of the Association for Information Science and Technology, 74(5), 570–581. https://doi.org/10.1002/asi.24750.
    Maloy, R. W., & Gattupalli, S. (2024). Prompt literacy. EdTechnica, https://doi.org/10.59668/371.14442.
    McGrath, I. (2016). Materials Evaluation and Design for Language Teaching. Edinburgh University Press.10.1515/9780748694822
    Meniado, J. C. ( 2023). Digital language teaching 5.0: Technologies, trends and competencies. RELC Journal, 54(2), 461–473.10.1177/00336882231160610
    Milroy, J. (2001). Language ideologies and the consequences of standardization. Journal of Sociolinguistics, 5(4), 530–555. https://doi.org/10.1111/1467-9481.00163.
    Mishan, F. (2015). Materials Development for TESOL. Edinburgh University Press.10.1515/9780748691371
    Mishra, P., Warr, M., & Islam, R. (2023). TPACK in the age of ChatGPT and generative AI. Journal of Digital Learning in Teacher Education, 39(4), 235–251. http://dx.doi.org/10.1080/21532974.2023.2247480.
    Mizumoto, A., & Eguchi, M. (2023). Exploring the potential of using an AI language model for automated essay scoring. Research Methods in Applied Linguistics, 2(2), 100050. https://doi.org/10.1016/j.rmal.2023.100050.
    Moorhouse, B. L. (2023). Teachers’ digital technology use after a period of online teaching. ELT Journal, 77(4), 445–457.10.1093/elt/ccac050
    Moorhouse, B. L. ( 2024). Generative artificial intelligence and ELT. ELT Journal, 78(4), 378–392. https://doi.org/10.1093/elt/ccae032.
    Moorhouse, B. L., Ho, T. Y., Wu, C., & Wan, Y. (2025). Pre-service language teachers’ task-specific large language model prompting practices. RELC Journal. https://doi.org/10.1177/00336882251313701.
    Moorhouse, B. L., & Kohnke, L. (2024). The effects of generative AI on initial language teacher education: The perceptions of teacher educators. System, 122, 103290. https://doi.org/10.1016/j.system.2024.103290.
    Moorhouse, B. L., Wan, Y., Ho, T. Y., & Lin, A. M. (2024). Generative AI-assisted, evidence-informed use of L1 in L2 classrooms. ELT Journal, 78(4), 453–465.10.1093/elt/ccae033
    Moorhouse, B. L., Wong, K. M., & Li, L. (2023). Teaching with technology in the post-pandemic digital age: Technological normalisation and AI-induced disruptions. RELC Journal, 54(2), 311–320. https://doi.org/10.1177/00336882231176929.
    Moorhouse, B. L., & Yan, L. (2023). Use of digital tools by English language schoolteachers. Education Sciences, 13(3), 226.10.3390/educsci13030226
    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 & Development, 71(1), 137–161.10.1007/s11423-023-10203-6
    Palfreyman, D. M., & Benson, P. (2019). Autonomy and its role in English language learning: Practice and research. In Second Handbook of English Language Teaching, Gao, X., editor. Springer, 661–681.10.1007/978-3-030-02899-2_38
    Pinter, A. (2017). Teaching Young Language Learners. Oxford University Press.
    Porter, B., & Machery, E. (2024) AI-generated poetry is indistinguishable from human-written poetry and is rated more favorably. Scientific Reports, 14, 26133. https://doi.org/10.1038/s41598-024-76900-1.
    Reinhardt, K. S., & Elwood, S. (2019). Promising practices in online training and support: Microlearning and personal learning environments to promote a growth mindset in learners. In Handbook of Research on Virtual Training and Mentoring of Online Instructors, 298–310. IGI Global.
    Richards, J. C. (2010). Competence and performance in language teaching. RELC Journal, 41(2), 101–122. https://doi.org/10.1177/0033688210372953.
    Richards, J. C. (2015). Materials design in language teacher education: An example from Southeast Asia. In International Perspectives on English Language Teacher Education: Innovations from the Field, 90–106. Palgrave Macmillan UK.10.1057/9781137440068_6
    Richards, J. C., & Rodgers, T. S. (2014). Approaches and Methods in Language Teaching (Third Edition). Cambridge University Press.10.1017/9781009024532
    Rifkin, B. (2003). Oral proficiency learning outcomes and curricular design. Foreign Language Annals, 36(4), 582–588.10.1111/j.1944-9720.2003.tb02148.x
    Scarino, A. (2009). Assessing intercultural capability in learning languages: Some issues and considerations. Language Teaching, 42, 67–80. https://doi.org/10.1017/S0261444808005417.
    Scrivener, J. (2011). Learning Teaching. Macmillan.
    Shaikh, S., Daudpota, S. M., Yayilgan, S. Y., & Sindhu, S. (2023 ). Exploring the potential of large-language models (LLMs) for student feedback sentiment analysis. In 2023 International Conference on Frontiers of Information Technology (FIT), 214–219. Institute of Electrical and Electronics Engineers.10.1109/FIT60620.2023.00047
    Shin, D., & Lee, J. H. (2023). Can ChatGPT make reading comprehension testing items on par with human experts? Language Learning & Technology, 27(3), 27–40.
    Smith, G., Fleisig, E., Bossi, M., Rustagi, I., & Yin, X. (2024). Standard language ideology in AI-generated language. arXiv, arXiv:2406.08726.
    Speechace (2024). Speaking test. Speechace. www.speechace.com/speaking-test/.
    Stahl, B. C., & Eke, D. (2024). The ethics of ChatGPT: Exploring the ethical issues of an emerging technology. International Journal of Information Management, 74, 102700. https://doi.org/10.1016/j.ijinfomgt.2023.102700.
    Steiss, J., Tate, T., Graham, S., Cruz, J., Hebert, M., Wang, J., & Olson, C. B. (2024). Comparing the quality of human and ChatGPT feedback of students’ writing. Learning and Instruction, 91, 101894.10.1016/j.learninstruc.2024.101894
    Stockwell, G., & Wang, Y. (2023). Exploring the challenges of technology in language teaching in the aftermath of the pandemic. RELC Journal, 54(2), 474–482. https://doi.org/10.1177/00336882231168438.
    Stockwell, G., & Wang, Y. (2024). Expanding the learning ecology and autonomy of language learners with mobile technologies. Educational Technology and Society, 27(2), 60–69. https://doi.org/10.30191/ETS.202404_27(2).SP05.
    Strokel-Walker, C. (2024, May 1). AI chatbots have thoroughly infiltrated scientific publishing. Scientific American. www.scientificamerican.com/article/chatbots-have-thoroughly-infiltrated-scientific-publishing/.
    Thornbury, S. (1999). How to Teach Grammar. Longman
    Thorne, S. L. (2003). Artifacts and cultures-of-use in intercultural communication. Language Learning & Technology, 7(2), 38–67. http://llt.msu.edu/vol7num2/thorne/.
    Tomlinson, B. (2014). 7 teacher growth through materials development. The European Journal of Applied Linguistics and TEFL, 3(2), 89–107.
    Tomlinson, B. (2015). Developing principled materials for young learners of English as a foreign. In Teaching English to Young Learners: Critical Issues in Language Teaching with 3-12 Year Olds, Bland, J., editor. Bloomsbury, 279.
    Trust, T. (2023). Essential considerations for addressing the possibility of AI-driven cheating, part 2. www.facultyfocus.com/articles/teaching-with-technology-articles/essential-considerations-for-addressing-the-possibility-of-ai-driven-cheating-part-2/.
    Tseng, W., & Warschauer, M. (2023). AI-writing tools in education: If you can’t beat them, join them. Journal of China Computer-Assisted Language Learning, 3(2), 258–262.10.1515/jccall-2023-0008
    van den Berg, G. & E. du Plessis (2023). ChatGPT and generative AI: Possibilities for its contribution to lesson planning, critical thinking and openness in teacher education. Education Sciences, 13(10), 998. https://doi.org/10.3390/educsci13100998.
    Walters, W. H., & Wilder, E. I. (2023). Fabrication and errors in the bibliographic citations generated by ChatGPT. Scientific Reports, 13(1), 14045. https://doi.org/10.1038/s41598-023-41032-5.
    Wan, Y., & Moorhouse, B. L. (2024). Using Call Annie as a generative artificial intelligence speaking partner for language learners. RELC Journal. https://doi.org/10.1177/00336882231224813.
    Wang, L., Chen, X., Deng, X., Wen, H., You, M., Liu, W., Li, Q., & Li, J. (2024). Prompt engineering in consistency and reliability with the evidence-based guideline for LLMs. npj Digital Medicine, 7, 41. https://doi.org/10.1038/s41746-024-01029-4.
    Warschauer, M., Tseng, W., Yim, S., Webster, T., Jacob, S., Du, Q., & Tate, T. (2023). The affordances and contradictions of AI-generated text for writers of English as a second or foreign language. Journal of Second Language Writing. https://doi.org/10.2139/ssrn.4404380.
    Yeo, M. A., Moorhouse, B. L., & Wan, Y. (2025). From academic text to talk-show: Deepening engagement and understanding with Google NotebookLM. TESL-EJ, 28(4), 1–14.10.55593/ej.28112int
    Zhang, R., & Zou, D. (2024). Self-regulated second language learning: A review of types and benefits of strategies, modes of teacher support, and pedagogical implications. Computer Assisted Language Learning, 37(4), 720–765.10.1080/09588221.2022.2055081

    Metrics

    Altmetric attention score

    Full text views

    Total number of HTML views: 0
    Total number of PDF views: 0 *
    Loading metrics...

    Book summary page views

    Total views: 0 *
    Loading metrics...

    * Views captured on Cambridge Core between #date#. This data will be updated every 24 hours.

    Usage data cannot currently be displayed.

    Accessibility standard: Missing or limited accessibility features

    Why this information is here

    This section outlines the accessibility features of this content - including support for screen readers, full keyboard navigation and high-contrast display options. This may not be relevant for you.

    Accessibility Information

    The PDF of this book is known to have missing or limited accessibility features. We may be reviewing its accessibility for future improvement, but final compliance is not yet assured and may be subject to legal exceptions. If you have any questions, please contact accessibility@cambridge.org.

    Content Navigation
    Table of contents navigation

    Allows you to navigate directly to chapters, sections, or non‐text items through a linked table of contents, reducing the need for extensive scrolling.

    Reading Order and Textual Equivalents
    Single logical reading order

    You will encounter all content (including footnotes, captions, etc.) in a clear, sequential flow, making it easier to follow with assistive tools like screen readers.

    Short alternative textual descriptions

    You get concise descriptions (for images, charts, or media clips), ensuring you do not miss crucial information when visual or audio elements are not accessible.

    Visual Accessibility
    Use of colour is not sole means of conveying information

    You will still understand key ideas or prompts without relying solely on colour, which is especially helpful if you have colour vision deficiencies.

    Structural and Technical Features
    ARIA roles provided

    You gain clarity from ARIA (Accessible Rich Internet Applications) roles and attributes, as they help assistive technologies interpret how each part of the content functions.