Professional development and GenAI

The degree to which generative artificial intelligence (GenAI) has rapidly infiltrated education is unparalleled. Language education has been particularly impacted because GenAI tools process and generate the learning objective of that education, i.e., human language. Language teacher education programs have been faced with addressing GenAI since the public release of ChatGPT in November 2022, and we anticipate that many recent and future graduates will have had some formal education that includes it. Moorhouse & Kohnke (2024) provide initial insights from a group of language teacher educators on this topic. But what about those who have already completed their formal education and are in the language teaching workforce, the millions of individuals across the world actively teaching languages at all levels?

This is part of a draft of an article I wrote with Phil Hubbard. He wrote this part. In this paper, we are proposing a way in which teachers can organize their own professional development (PD) in the context of the rapid expansion of Generative AI. 
We call this  PD sustained integrated PD (GenAI-SIPD). Sustained because it is continuous and respectful of the other responsibilities and commitments teachers have; integrated because the PD activities are an integral part of what teachers do anyway; the teacher retains control of the PD process.

The full article is available as open access: 
Hubbard, Philip and Mathias Schulze (2025) AI and the future of language teaching – Motivating sustained integrated professional development (SIPD). International Journal of Computer Assisted Language Learning and Teaching 15.1., 1–17. DOI:10.4018/IJCALLT.378304 https://www.igi-global.com/gateway/article/full-text-html/378304

UNESCO (2024) has recognized the immediate need for AI competency across the board in education and why it should be addressed.

Al can pose significant risks to students, the teaching community, education systems and society at large…In education, Al can reduce teaching and learning processes to calculations and automated tasks in ways that devalue the role and influence of teachers and weaken their relationships with learners. It can narrow education to only that which Al can process, model and deliver. Finally, it can also exacerbate the worldwide shortage of qualified teachers through disproportionate spending on technology at the expense of investment in human capacity development (p. 13).

So, given this litany of dangers, what do we think language teachers need to know and be able to do to achieve a functional level of expertise so that they can safely leverage the affordances of GenAI to improve rather than degrade language learning processes and outcomes? How can language teachers and language programs support them in accomplishing this goal?

In our position paper, we address these questions by focusing on the importance of understanding the fundamentals of AI and its subset GenAI, as recognized in several AI competency and literacy frameworks. For example, the UNESCO (2024) AI Competency Framework for Teachers states that at the lowest of their three levels of AI competency, “Teachers are expected to acquire basic conceptual knowledge on AI, including: the definition of AI, basic knowledge of how AI models are trained, and associated knowledge on data and algorithms” (p. 30). The Educause (2024) Durable AI Literacy Framework, targeted at tertiary institutions, goes further: “Faculty must grasp the core principles of AI, including machine learning, natural language processing, and neural networks. This foundational knowledge is crucial for understanding how AI operates and what its potential applications are in various academic disciplines.” Other frameworks we discuss, such as those from the International Society for Technology in Education (ISTE) and Paradox Learning, echo this need for teacher understanding.

References

Educause. (2024). AI literacy in teaching and learning: A durable framework for higher education. https://www.educause.edu/content/2024/ai-literacy-in-teaching-and-learning/faculty-altl

Moorhouse, B. L., & Kohnke, L. (2024). The effects of generative AI on initial language teacher education: The perceptions of teacher educators. System, 122, 103290

UNESCO. (2024). AI competency framework for teachers. UNESCO Publishing. https://unesdoc.unesco.org/ark:/48223/pf0000391104