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Redefining Teacher Identity in the Age of GenAI

What's your teacher GenAI identity? The starry-eyed? The cautious? The early adopter? Is our GenAI use falling starting to create a typology?

Victoria Hedlund, 9th Feb 2025

A few months ago, it was revolutionary that GenAI could create a lesson plan. Since then, more and more tools and services have emerged that serve the same function in different ways: reducing teacher workload by creating materials for them. This in itself was enough to grab headlines, but is that enough anymore? Like the widespread use of pre-made schemes of work, the shiny appeal of functionality soon gets lost to the notion of alignment. In this post, I argue that we’ve gone past the point of being impressed by functional possibility, into the realm of matching a GenAI tool to your specific teacher identity. Vanilla shouldn't be the only flavour available.

To understand this shift from function to alignment, we need to delve into the concept of teacher identity. The concept of teacher identity is established. Rushton, Rawlings Smith, Steadman, and Towers (2023) define teacher identity as being socially constructed, dynamic, and hybrid. They acknowledge that it is influenced by a range of individual factors such as biographies and narratives, alongside emotion, social contexts, and relationships with others. So in this GenAI age, how does this map to GenAI tool use? I’ll explore each factor in turn, looking at how these aspects can be translated and connected to GenAI tool use.

Is Teacher GenAI Identity Really a Thing?

Is GenAI socially constructed? As it is trained on a large subset of the internet, I’d argue that it is. I’d go so far as to say the concept of GenAI itself has parallels with a giant socially constructed machine such as Viki in I, Robot. Teachers have user profiles for these GenAI tools and accounts, so by using them, they are, by definition, subscribing to the beginnings of a Teacher GenAI Identity. What could the diversity of these identities look like? How well do they map to the classroom? How representative or relational are they to the identity observed in classroom practice? These are all questions that we are just beginning to explore. This aligns well with the idea of a teacher identity being ‘dynamic’. Would a teacher identity survive without a GenAI aspect? At what point will there be any teachers left who don’t use GenAI in some way or another? This human-machine way of interfacing could be seen as the ultimate ‘hybrid’ component of teacher identity.

It seems likely that a GenAI Identity could indeed fulfil the criteria of being socially constructed, dynamic, and hybrid, but what about the other aspects? How can GenAI be used with real-life teacher narratives? A classroom is full of narratives. A teacher has their own narratives. Arguably, this is such a nuanced and personally-loaded concept that it is difficult to see how it could be mirrored by the digital domain. I’ve spent some time trying to deconstruct this concept of narratives, especially for teachers early in their training or careers. A narrative is context-dependent and value-laden, and awareness of them requires advanced reflective capacity. I’ve discovered something, though, with prior knowledge scenarios. Our prior knowledge generator is perhaps the best way to illustrate this. While we are using the ‘new science’ within the CCF/ITTECF, in our profession we will be focusing on establishing the prior knowledge of children for some time to come.

Prior knowledge is more than just prior learning, though. It is contextual and dependent on lived experience and personal significance. These are difficult aspects for beginning teachers to master, as their lived experience and database of what prior knowledge could look like for children is in its infancy. So our open-source prior knowledge scenario prompt generator aims to provide a scaffold to promote the consideration of the narratives of the individuals in a class. In this capacity, although the scenarios may not be exactly representative of the specific needs of the class, they encourage a teacher to consider the diversity of the possible prior knowledge of the children in their class. A scaffold for one size does NOT fit all approach.

Continuing with the idea of individual differences, how can we view a Teacher GenAI Identity as being affected by emotion or relationships with others? I’ve observed that the mere fact that there is the capability of GenAI being used to do ‘teacher’s work’ evokes an emotional response in individuals, such as those who are actively resistant to AI in education (Shea, 2024). How can a team of colleagues function, in the future age of GenAI adoption, if there are huge differences in the response to its use? How do departments and institutions address this, and is there even a need or requirement to? Is an early adopter of GenAI Teacher tools at a social advantage? Are they perceived as holding a position of responsibility to influence the GenAI identities of others in a team? In this regard, I could argue that a Teacher GenAI Identity is not just a personal attribute but one that is socially impacted and relevant to teams of employees and their functionality.

Towards a Typology

So if teachers can be thought of as having a Teacher GenAI Identity, what could the diversity of these identities look like? Stay with me and consider my rapidly developing (and slightly humourous) typology:

🤖 The early adopter: Has been involved since GenAI was just AI. Can explain the difference and also talk at length about machine learning. Has already created their own agents and published several papers. Could be utilised to upskill other employees but is struggling to find common ground with ‘the cautious’.

🤔 The intrigued: Can see the potential to save time and get creative. Will happily attend any specific training and give things a go but lacks deep understanding of how it works or how it could be developed within education.

😇 The saviours: Have happily subscribed to its use as the ‘new normal’. Convinced it will solve all problems for their institution and maybe even humanity.

😿 The Shakespeare mourners: Have already charged GenAI with the crime of ending humanity’s ability to write, and maybe even think.

🙄 The accepting: Will go with the flow. Will use it when it is normalised into operational function but won’t develop it or appraise it.

⚠️ The cautious: Worried about the impact upon cognitive development through over-reliance on it. Will cite evidence that taxi-drivers and younger people have already lost critical thinking skills because of it.

🪄 The magicians: Convinced that it works by magic, and will happily believe in the power of magic. If magic saves them time, then magic they will use!

😱 The scared: Convinced it will end humanity, or at the very least be the death of critical thinking skills.

🤩 The starry-eyed: Infatuated with its existence and excited by the sheer possibilities of use and development.

🪤 The boundary-observing: Like the starry-eyed, but also aware that within the sheer possibilities of future use and development could be AGI and human enslavement.

As we look to how Teacher GenAI Identity may progress, which of these ‘types’ do you best associate with at present? If, however, you would require a more descriptive typology, the UNESCO AI Competency Framework for Teachers might be a good place to start. Being a competency framework, it is concerned with tangible and measurable outcomes that are explained and exemplified in detail in the report. The basis can be seen in the table opposite. For the definition of Teacher GenAI Identity, there appears to be a need to incorporate the notion of competency. This opens the gates of discussion surrounding the related attributes of self-concept, values, and beliefs. How does a GenAI-produced lesson plan echo the self-concept, values, and beliefs of the individual teacher? This can be explored through considering the specifics of the generation of lesson plans.

Teacher GenAI Identities in GenAI-produced Lesson Plans

Most of the lesson plan GenAI Tools I’ve used follow some kind of repeatable structure. Aila (Oak National Academy) reliably provides reasonably detailed prior knowledge, retrieval starter quizzes, and a lesson plan based on ‘lesson cycles’. Teachmate (Teachmate) consistently produces adaptive strategies at the end of their plans. Twinkl's Ari (Twinkl Educational Publishing) seems to have some variability with lesson structure but the overall approach follows a reasonably standard format. I could go on for many other tools.

We could question whether every lesson should be based on a repeatable, set, rigid structure. Tools are now integrating opportunities for the teacher to adapt the generated content either during or after the generation, but how likely is it that a teacher will actually do this? I see a need for research in this area. Recent research from TeacherTapp are telling us how many teachers are using GenAI tools, but what are they actually doing with the outputs? Modifying them? Using them vanilla-style? Where is the space in this construct for a teacher ‘taking the children outside’ for a lesson or otherwise deviating in a way that could be an extreme obvious example of the 'manifestation of teacher identity'?

There are those who will argue that all lessons should follow a rigid structure heavily related to specific objectives and not deviate away even slightly, to maintain attention on the required content and outcomes. In this scenario, the more rigid GenAI Tools fulfill their purpose.

Many will wonder if, or perhaps 'feel', that teaching is more than this static structure of what a lesson should be. What is it about me that makes my lesson planning different to yours? A bigger question could be framed as 'how does a lesson plan reflect or indicate aspects of teacher identity'. Our Lesson Inspector tool was created to provide a critically reflective scaffold to begin to explore this question. I know my teacher identity has aspects that strongly admire dual coding and wholesome consideration to the personal significance components of prior knowledge. Could we get to a situation where teachers can choose their tool based on that tool's alignment to aspects of their teacher identity? Or perhaps they fancy a move out of their comfort zone and want to know which tool could provide this.

Moving forward, it is likely that to answer these questions of GenAI and identity, we will need to consider the space for affect within GenAI tools. Could affective GenAI soon permeate this realm too? What would that mean for tool use? How could my preference for a gel pen or a bit of plasticine modelling be represented through a GenAI tool's knowledge of my teacher identity? Taking this a step further, how long until the user doesn't input or select from options related to their teacher identity, and their identity is inferred from their social media profiles, like LinkedIn...

Perhaps I have now morphed from 'the starry eyed' into 'the scared'...😱🤖

References:

Cedefop. (2024) 'UNESCO AI competency framework for teachers'. Available at: https://www.cedefop.europa.eu/files/unesco_ai_competency_framework_for_teachers.pdf (Accessed: 7 February 2025).

Rushton, E. A. C., Rawlings Smith, E., Steadman, S., & Towers, E. (2023). Understanding teacher identity in teachers' professional lives: A systematic review of the literature. Review of Education, 11, e3417. https://doi.org/10.1002/rev3.3417

Shea, P. (2024). The resistance to AI in education isn’t really about learning. Medium. Retrieved from https://danielschristian.com/learning-ecosystems/2024/07/26/the-resistance-to-ai-in-education-isnt-really-about-learning-shea/ (Accessed: 7 February 2025).

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