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AI in Learning & Education

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Supporting learning and education.

Education exemplifies AI’s qualitative turn, where generative systems produce cultural outputs such as essays, explanations, and creative work that demand contextual interpretation rather than simple benchmarking. Yet current educational AI often operates through narrow metrics that homogenise learning, perpetuating limited conceptions of intelligence whilst marginalising alternative ways of knowing. Your research could challenge this, exploring how AI might engage meaningfully with educational complexity rather than flattening it.

You might investigate human-AI ensembles in learning contexts, moving beyond assistant models toward genuine collaboration that amplifies collective capabilities. Potential directions include developing interpretive educational AI capable of representing multiple valid perspectives, employing participatory approaches where diverse communities shape systems reflecting their epistemologies, examining how algorithmic homogenization affects learners and educators, or reimagining assessment to value contextual judgement over standardised outputs. This addresses real-world challenges: fewer than 10% of schools have AI guidance, assessment systems fail when AI generates acceptable work, and marginalised communities risk exclusion from design processes.

We welcome proposals employing participatory design that centres community voice, critical approaches examining power dynamics in educational technology, mixed methods integrating interpretive depth with empirical patterns, and speculative methods exploring alternatives to techno-determinism.

Place-Based and Regional Context

The North East offers opportunities for investigating how educational AI might resist homogenization and honour local contexts. You could collaborate with Newcastle City Council and North of Tyne Combined Authority, exploring community-centred approaches that develop AI with rather than for diverse populations. Regional partners like Sunderland Software City and Innovation SuperNetwork provide access to EdTech developers where your research could advocate for interpretive, culturally responsive systems over standardised solutions.

The area’s educational diversity enables investigation of how algorithmic systems perpetuate or challenge inequalities. Rather than treating this as a technical problem requiring scaled solutions, you could explore how different communities might shape AI, reflecting distinct epistemologies. NHS partnerships enable examination of human-AI ensembles in healthcare education. The region’s industrial transformation offers sites for investigating workplace learning where AI might enhance rather than displace situated expertise.

Relevant Partner Organisations

Cabinet OfficeDepartment for Science, Innovation and TechnologyDigital Safety CICGoogleInternational Centre for Life TrustNational Cyber Security CentreNewcastle City CouncilNokia Bell LabsNorth East Combined AuthorityNorth East MuseumsOfcomThoughtworksTrussell TrustVONNE

Partners enable challenging, narrow EdTech paradigms. Newcastle City Council and North of Tyne Combined Authority support exploring alternatives to dominant models. Technology partners (Nokia Bell Labs, Google, Thoughtworks) offer opportunities influencing development toward interpretive approaches. Policy bodies (Ofcom, DSIT, National Cyber Security Centre, Cabinet Office) enable examining governance supporting AI plurality. Third sector organizations (VONNE, Trussell Trust, Digital Safety CIC) connect with communities often excluded from design. Cultural partners (Tyne & Wear Archives & Museums, International Centre for Life Trust) provide contexts where interpretive depth matters profoundly. Healthcare partners enable the investigation of professional learning ensembles.

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2026

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