by Rachel Forsyth, Lund University, Sweden and Claire Hamshire, University of Salford, UK.
Regular readers of the Media and Learning blog don’t need to be reminded of the impact of Generative AI (GenAI) on education. It’s impossible to escape discussions about how GenAI is offering us endless possibilities or, alternatively, destroying everything we know about learning, teaching, and assessment. As educators who are both enthusiastic about technology and keenly aware of its complexities, but also committed to improving the educational environment, we have been reflecting on how GenAI presents opportunities and challenges in the context of inclusive learning communities.
Our previous work, stretching over more than 17 years, has shown that building inclusive learning communities requires an intentional partnership between staff and students. A partnership built on trust, transparency, and shared decision-making. When students are involved as co-creators and commentators in curriculum and assessment design, their diverse perspectives help shape educational practices that are genuinely responsive to their needs and inclusive. This collaborative approach empowers students, educates teachers, and also fosters a sense of trust and mutual respect.
On the surface, and in many advertisements and discussion pieces, GenAI offers the attractive prospect of personalised, adaptive learning, which appears to support inclusive practices. We are invited to imagine a learning environment where resources are matched to individual needs, where every student receives tailored feedback, and where barriers to participation are lowered for those with learning differences or language challenges. For some students, particularly those with dyslexia, ADHD, or autism, GenAI products can provide new ways to engage with content and demonstrate understanding. You can ask as many questions as you like, at any time of day, without fearing that you are tiring or irritating your human teacher. This potential for technology to support equity and accessibility is real and of great value.
Yet, beneath this promise lies a more complicated reality. AI systems are trained on vast datasets that reflect the biases and inequalities of the societies from which those datasets originate. This means that GenAI outputs may reinforce stereotypes and biases, marginalise students from minoritised backgrounds, and perpetuate existing disparities in student success. For students whose experiences or identities fall outside the mainstream, the risk of exclusion, disadvantage or discrimination is significant. Of course, this is unintended, but everything a GenAI product does is unintended; it is simply predicting the most likely sequence of outputs in a particular context based on the information available. The illusion of technological objectivity can mask these issues, making it even more important for users to remain vigilant and critical.
Taking some tips from research on creating inclusive learning communities, educators need to create trustworthy spaces for dialogue about GenAI, where staff and students can collectively explore new tools, share experiences, and develop policies together. Regularly and openly reviewing academic integrity guidelines and teaching practices is essential to ensure clarity around the acceptable use of AI, building trust and accountability within the learning community.
Continuous feedback is another cornerstone of inclusive practice. When trying new technologies or approaches, educators should invite students to share their thoughts and concerns: what excites them, what worries them, what challenges they face, and sometimes even what upsets them about the outputs. Simple strategies like anonymous feedback or small group discussions can provide valuable insights and help refine innovations in real time. Recognising when things aren’t working and being willing to adapt demonstrates a commitment to student success and helps to build trust.
It is also important to recognise that every educational context is different. What works in one course or institution may not be appropriate elsewhere. The design of inclusive curricula and assessments must be responsive to the diversity of educators’ and students’ backgrounds, experiences, and aspirations. Whether or not GenAI is involved, critical reflection on assumptions, values, and perspectives helps to ensure that no group is unintentionally excluded. By centring human interactions, working collaboratively and keeping critical reflection at the heart of innovation, we can endeavour to use GenAI as a tool for inclusion and not exclusion.
Rachel Forsyth, Lund University, sweden
Claire Hamshire, University of Salford, UK
This blog post is based on a chapter in a forthcoming book: Forsyth, R., Hamshire, C., Olumu, K., & King, E. (2025). The impact of AI on inclusive learning communities. In Handbook of Artificial Intelligence in Higher Education: Edward Elgar Publishing.
This article is connected to this event: Making educational resources accessible in higher education
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