National Council of Teachers of English

ELATE Position Statement: Exploring, Incorporating, and Questioning Generative Artificial Intelligence in English Teacher Education

As English language arts (ELA) teacher educators committed to growing students’ passion for reading, writing, and thinking critically, we acknowledge the impact that emerging digital technologies have on educational practices. Generative artificial intelligence (GenAI) is one such technology that has sparked both excitement and concern. GenAI, driven by deep learning algorithms, enables machines to produce language that resembles human-written text (Fitria, 2023). GenAI platforms, such as ChatGPT and Gemini, have led to intense debate on various topics, including education, health care, and ethics (Dwivedi et al., 2023). In education, GenAI can assist in or perform a wide range of tasks, including writing, language translation, and lesson planning. However, concerns have been raised regarding its potential to generate misinformation, exacerbate existing racial, gender, and linguistic biases, extend and reinforce dominant social and economic ideologies, and diminish the need for human interactions in communication (Inclezan & Prádanos, 2023; Tacheva & Ramasubramanian, 2023). Striking a balance between embracing the opportunities presented by GenAI and mitigating its potential pitfalls is crucial (Chan, 2023).

Educators must stay vigilant and curious as GenAI platforms evolve. Awareness of the affordances and constraints of the technology will allow educators to equip students with the skills necessary for recognizing biases and reliable information (Ali et al., 2021). Teacher educators, especially, must share in the challenge of disseminating informed knowledge about GenAI to future teachers, particularly given NCTE’s commitment to addressing new technologies and antiracism in tandem (NCTE, 2021). Specifically, teacher educators should emphasize that it is vital to maintain a human-centered approach to education, stressing the significance of human connections, creativity, and critical thinking skills that cannot be replaced by GenAI (Shneiderman, 2021; Young et al., 2024).

This statement is the product of two years of ongoing conversation, writing, presentation, and productive, collaborative disagreement between the 14 members of the NCTE Commission on Digital Literacies and Teacher Education (D-LITE) AI working group and with teachers working in schools. Members of the D-LITE commission previously authored NCTE’s Beliefs for Integrating Technology into the English Language Arts Classroom [1] (2018), a position statement that deeply informs our approach to critically exploring the use of new technologies in ELA teacher education classrooms. We have all worked to critically and thoughtfully explore and incorporate generative AI into our work with preservice and inservice teachers and have published and presented on this subject in NCTE journals and conferences (e.g., Moran, 2024; Nash et al., 2023; Turner et al., 2024). As GenAI is a new technology, particularly in English education, we do not position ourselves as AI experts but, rather, as scholarly explorers investigating this evolving technology and drawing on our own and others’ ongoing research into digital literacies in ELA classrooms and teacher education. We offer this position statement with ten recommendations for incorporating, addressing, and exploring GenAI in ELA teacher education.

These recommendations are meant as starting points, not endpoints. We encourage teacher educators to mess around (Ito et al., 2010) with GenAI and seek students’ input on what works. We also encourage teacher educators to learn about AI, to explore the way the physical technologies needed for it to operate harm the planet, the economic imperatives that drive its development and govern its corporate platform-holders, and the myriad voices used without permission or left out of AI data corpuses (Crawford, 2021; Tacheva & Ramasubramanian, 2023). We encourage teacher educators to explore AI in its totality, working and learning with and about it, and inviting their students along for these journeys. We provide these statements as informed, evolving beliefs with suggestions for practice, knowing they likely will change as GenAI itself evolves. We offer these ideas as an invitation to other teachers and teacher educators to think along with us.

Conclusion

As with the many technologies that have preceded GenAI—from pencils, pens, and paper to typewriters, word processors, and voice-to-text dictation—our response to, implementation of, and instructional choices surrounding our use of GenAI will be informed by empirical research and reflective practice. We return to NCTE’s Definition of Literacy in a Digital Age [2] (2019), which reminds us that “a literate person possess[es] and intentionally appl[ies] a wide range of skills, competencies, and dispositions” and that “[t]​​hese literacies are interconnected, dynamic, and malleable.” Just as teachers and students have adapted and extended technologies to support ELA teaching and learning in the past, based on principled judgment and the changing nature of the tools and of ELA itself, so too will we learn to work with, extend, critique, and—when necessary—resist GenAI in our various classroom contexts. Given the rapidly changing nature of GenAI platforms, it is essential to recognize that this work is ongoing and involves a necessary and continual evolution of our approaches to curriculum, assessment, and teaching practice. In doing so, we, along with our students, will learn how to engage with GenAI in increasingly critical, ethical, and agentive ways—an endeavor, at heart, that we see as truly grounded in humanity and creativity.

References

Beach, C.L., Alvermann, D.E., Loomis, S., Wright, W., & Hutcherson Price, L. (2023). Digital remixing online: Entangled feelings. Digital Culture & Education, 14(4), 92–108. (Open Access) https://www.digitalcultureandeducation.com/volume-14-4

Behizadeh, N., Johnson, L.L., Garcia, M. (2023). Promise and perils of GenAI in English education: Reflections from the national technology leadership summit. English Education, 56(1), 8–19.

Bozard, Z. (2023). What does it mean to create art? Intellectual Property rights for Artificial Intelligence generated artworks. South Carolina Journal of International Law & Business, 20(1), 83–101.

Chan, C. K. Y. (2023). A comprehensive AI policy education framework for university teaching and learning. International Journal of Educational Technology in Higher Education, 20(1), 1–25.

Cohn, J. (2021). Skim, dive, surface: Teaching digital reading. West Virginia University Press.

Crawford, K. (2021). Atlas of AI: Power, politics, and the planetary costs of artificial intelligence. Yale University Press

Fitria, T. N. (2023, March). Artificial intelligence (AI) technology in OpenAI ChatGPT application: A review of ChatGPT in writing English essay. ELT Forum: Journal of English Language Teaching, 12(1), 44–58.

Hashem, R., Ali, N., El Zein, F., Fidalgo, P, & Abu 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

Inclezan, D., & Prádanos, L. I. (2023). AI for sustainability. In D. La Torre, F. P. Appio, H. Masri, F. Lazzeri, & F. Schiavone (Eds.), Impact of artificial intelligence in business and society (1st ed., pp. 192–211). Routledge. https://doi.org/10.4324/9781003304616-13

Ito, M., Baumer, S., Bittanti, M., Boyd, D., Cody, R., Herr-Stephenson, B., Horst, H. A., Lange, P. G., Mahendran, D., Martínez, K. Z., & Pascoe, C. J., (2010). Hanging out, messing around, and geeking out. MIT Press.

Kim, G. M., Johnson, L. L., & Nash, B. L. (2023). Games to promote empathy as a literacy practice: A new teacher’s playful practice. English Education, 56(1), 20–43. https://doi.org/10.58680/ee202356120

Kirkpatrick, K. (2023). Can AI demonstrate creativity? Communications of the ACM, 66(2), 21–23. https://doi.org/10.1145/3575665

Leander, K.M., Burriss, S.F. (2020). Critical literacy for a posthuman world: When people read, and become, with machines. British Journal of Educational Technology, 51(4), 1262–1275. doi:10.1111/bjet.12924

McBride, C., Smith, A., & Kalir, J. H. (2023). Tinkering toward teacher learning: a case for critical playful literacies in teacher education. English Teaching: Practice & Critique, 22(2), 221–233.

Moran, C. M. (2024), Ed. Revolutionizing English education: The power of AI in the classroom. Bloomsbury/Rowman & Littlefield/Lexington Books.

Nash, B. L., Hicks, T., Garcia, M., Fassbender, W., Alvermann, D., Boutelier, S., McBride, C., McGrail, E., Moran, C., O’Byrne, I., Piotrowski, A., Rice, M., & Young, C. A. (2023). Artificial intelligence in English education: Challenges and opportunities for teachers and teacher educators. English Education, 55(3), 201–206. https://doi.org/10.58680/ee202332555

National Council of Teachers of English (2018, October 25). Beliefs for integrating technology into the English language arts classroom. https://ncte.org/statement/beliefs-technology-preparation-english-teachers/

National Council of Teachers of English. (2019, November 7). Definition of literacy in a digital age. https://ncte.org/statement/nctes-definition-literacy-digital-age

National Council of Teachers of English (2021). NCTE standards for the initial preparation of teachers of English Language Arts 7–12 (Initial Licensure). https://ncte.org/wp-content/uploads/2021/11/2021_NCTE_Standards.pdf#:~:text=Standard%201:%20Candidates%20apply%20and

Noble, S. U. (2018). Algorithms of oppression: How search engines reinforce racism. NYU Press.

Robinson, B. (2023). Speculative propositions for digital writing under the new autonomous model of literacy. Postdigital Science and Education, 5(1), 117–135. https://doi.org/10.1007/s42438-022-00358-5

Shneiderman, B. (2021). Human-centered AI. Issues in Science and Technology, 37(2), 56–61.

Tacheva, J., & Ramasubramanian, S. (2023). AI Empire: Unraveling the interlocking systems of oppression in generative AI’s global order. Big Data & Society, 10(2), 20539517231219241. https://doi.org/10.1177/20539517231219241

Turner, K. H. & Hicks, T. (2015). Connected reading is the heart of research. English Journal, 105(2), 41–48.

Turner, K., Hicks, T., Schoenborn, A., Murchie, S., & Cornwell, A. (2024, March). Now the hard work begins: Inviting writers to use AI tools. In Society for Information Technology & Teacher Education International Conference, 2024(1), 887–891. Association for the Advancement of Computing in Education (AACE).

Young, C. A., Jacobs, L., Celaya, A., Lathrop, B., Hackett-Hill, K., Scialdone, M., Moehrke, H., Gaddis, B., Settie, K., Kuriny, D., and James, N. (2024). In conversation about GenAI in ELA education: Initial insights and experiences from ELA teachers and ELA teacher educators. In C. M. Moran (Ed.), Revolutionizing English education: The power of AI in the classroom. Bloomsbury/Rowman & Littlefield/Lexington Books.

Statement Authors

Brady L. Nash, The University of Florida
Merideth Garcia, University of Wisconsin-La Crosse
Carl A. Young, North Carolina State University
Kristen Hawley Turner, Drew University
Mary Rice, The University of New Mexico
Amy Piotrowski, Utah State University
W. Ian O’Byrne, College of Charleston
Cherise McBride, Stanford University
Ewa McGrail, Georgia State University
Clarice Moran, Appalachian State University
Troy Hicks, Central Michigan University
William Fassbender, Montana State University
Stefani Boutelier, Aquinas College
Donna Alvermann, The University of Georgia

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