phd-proposal-thoughts-and-reframing
Something I have struggled with throughout the PhD so far is how to describe what the research is actually about, in specfic terms. When asked, I usually fall back on a generic description, “AI in learning and teaching” which never quite captures it. Additionally, due to the interdisciplinary nature of the research, I often don’t know how to express how all these strands coming together in a succinct/coherent way.
The ‘generative AI in education’ framing (and AI in general) carries so much baggage right now – hype, panic, polarised opinion – that I feel this positioning can obscure what is genuinely specific and interesting about the work.
So I have been taking some time to make to try to express my research more coherently so things feel clearer, this is helpful for outward facing conversations, but also for my research trajectory.
This research sits at the intersection of speculative design, creative computing, and critical AI. The organising question is: what might learning and teaching look like after the current assumptions about intelligence, knowledge, and technology are opened up and challenged?
Rather than studying AI in education from the outside, the research proceeds through making; by building LLM-based tools, interactive systems, and participatory learning environments as the primary mode of inquiry. Each prototype is both a technical artefact and a theoretical proposition.
Key questions include:
- What assumptions about intelligence and knowledge are embedded in generative AI systems, and what do those assumptions mean for how we learn and teach?
- How can speculative design methods help us imagine and build alternatives to dominant AI narratives in education - not just critique them?
- How does working with generative tools change the practice of thinking itself?
- How can the conditions of live, performative practice (from live coding to the open research process of PhD-Live itself) offer different models for learning and knowledge-making?
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