AI’s potential to support teacher-research mentoring
Posted on 9th September 2024 by Prof. Richard SmithIf the benefits of teacher-research are to be spread more widely, there are currently not enough experienced mentors, and not enough capacity for training them. If AI could support mentors, acting as a kind of assistant in guiding teachers to formulate viable research questions and to generate, analyse and interpret classroom data, this could help increase the numbers of teachers benefitting worldwide from teacher-research engagement; at the same time, this could provide good opportunities for reflection on effective mentoring for novice mentors using the tool.
There can be many benefits for teachers in researching their own classrooms – achieving a better understanding through exploratory and/or action research can improve relationships with learners, form a good basis for appropriate change and enhance teacher agency and motivation (Smith & Rebolledo, 2018). While many recent initiatives have shown the feasibility of teachers engaging in useful classroom research even in relatively large-class, low-resource contexts in Africa, Asia and Latin America, it has become clear that appropriate mentoring is needed to initiate and sustain teachers’ engagement – and spreading the benefits of teacher-research will require more mentors to be trained. In both respects, with the help of the work going into development of ‘Noa’ and the Noticing app, I’ve come to see that AI can play a potentially very useful role in supporting teacher-research.
Sirin Soyoz and I started discussing and experimenting with the capabilities of ChatGPT as a possible teacher-research mentoring assistant in January this year. Sirin is an experienced teacher-research mentor from Turkey who has been investigating the capabilities of AI in her work for the British Council. I had also been wondering about the potential of AI to aid with teacher-research mentoring but without the kind of clear focus on actually developing something that Sirin had, and which online interactions with her now gave me. We wrote and tweaked various prompts and inputted information about the issues facing us in our own teaching to see what mentoring we would receive. However, we soon came up against the limitations both of ChatGPT and of our own capacities to develop a viable tool. ChatGPT was overly helpful, indeed directive, bossy and patronising, giving us all kinds of advice about what we ‘should’ do in our classrooms but not scaffolding reflection or guiding us to formulate our own research questions for further exploration, as we knew a good teacher-research mentor would do.
We therefore decided that we would need to work with a developer, and, having heard recently about ‘Noticing’ and collaborated previously with Elena, I contacted her and Matthew to ask for a trial. We were immediately attracted to the way Noticing offers a non-directive, non-judgmental mentoring experience. This is due – as we subsequently learned from Matthew – to the way several AI platforms are combined to create a particular kind of dialogue partner, Noa, which doesn’t provide all the answers but instead leads the user to deeper reflection and understanding, in an empowering as opposed to deskilling process for teachers. This was impressive: after all, it corresponds with the main reason for engaging teachers to do their own research in the first place.
While Noa is under a continuous process of refinement, it can already mentor a teacher effectively in key areas of teacher-research, for example in formulating research questions. Partly, this has been achieved by inputting authentic mentoring conversations to which we have appended comments in a ‘think-aloud’ kind of way. In the bi-monthly collaborative sessions we’ve been having with Elena and Matthew since March, I’ve found it fascinating to have this opportunity to reflect more deeply and be more explicit than previously about different aspects of the teacher-research mentoring process; for example, when exactly does a teacher-research mentor need to be relatively directive (there are some occasions!)? We’ve also had tantalizing glimpses of how AI could itself be used as a data-gathering instrument for classroom data, so we feel we may even be developing a new form of teacher-research – time will tell!.
We’re now planning to engage in some more systematic collaborative research and piloting. Along with practical questions like ‘How can AI be used in a context of person-to-person mentoring?’, there will be some relatively philosophical ones (e.g. ‘What does attempting to develop AI support reveal that we didn’t already know about the mentoring process?). Answers to both kinds of question will help in the further development of AI’s capacities to mentor teacher-research, and it’s clear to me that a degree of usefulness in this area has already been achieved.
Written by Prof. Richard Smith
Written by Prof. Richard Smith
Richard Smith is a Professor of ELT & Applied Linguistics at the University of Warwick. He originated the
Exploratory Action Research approach to CPD for school teachers working in ‘difficult’ Global South circumstances,
and is also well-known for his work supporting mentors of teacher-research.
As former coordinator of the IATEFL Research SIG, he founded the Teachers Research! series of conferences and
launched the SIG’s open-access book publication programme. He also conceived the International Festival of
(Mentoring) Teacher-Research (three iterations to date) and is the founding chair of
MenTRnet – an international support network for
teacher-research mentors.