{"id":12506,"date":"2026-01-08T10:50:34","date_gmt":"2026-01-08T10:50:34","guid":{"rendered":"https:\/\/sites.manchester.ac.uk\/humteachlearn\/?p=12506"},"modified":"2026-10-14T14:41:58","modified_gmt":"2026-10-14T13:41:58","slug":"aied-2025","status":"publish","type":"post","link":"https:\/\/sites.manchester.ac.uk\/humteachlearn\/2026\/01\/08\/aied-2025\/","title":{"rendered":"AIED 2025: Rethinking AI’s Role \u2013 From Answer Engine to Socratic Tutor"},"content":{"rendered":"

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As someone who has spent years using NVivo’s AI-powered features for qualitative data analysis, I thought I understood artificial intelligence in educational contexts. But when generative AI tools like ChatGPT became widely available, they changed education faster than policies could catch up. As a lecturer in education at the University of Manchester, I found myself asking: is this plagiarism, or a tool students should learn to use responsibly?\u00a0<\/p>\n

That uncertainty\u2014and my desire to learn from educators and researchers worldwide\u2014is what brought me to the Artificial Intelligence in Education (AIED) 2025 conference in Palermo, Italy this summer. The experience combined academic rigour with cultural richness, bringing together more than 700 participants from around the globe. From lively bus stop conversations to late-night discussions over gelato, it was a week of learning, connection, and reflection on the transformative potential of artificial intelligence in education.\u00a0<\/p>\n

First Impressions: Palermo and Conference Culture<\/b>\u00a0<\/p>\n

\"two

Bus-stop conversations: where the best discussions started before the conference even began.<\/p><\/div>\n

Palermo welcomed us with vibrant streets, historic architecture, and intense summer heat. I stayed in a hotel in the town centre\u2014<\/p>\n

affordable, comfortable, and close to everything. Getting around proved challenging; the buses were rarely on time. At first, this felt inconvenient, but I soon realised it was a blessing. Each morning at the bus stop, I met fellow conference attendees heading to the same venue. These unplanned encounters sparked deep conversations about AI in classrooms, the future of teaching, and our shared hopes for education.\u00a0\u00a0<\/p>\n

On arrival at the conference, we received a bag with the programme and a water bottle\u2014a simple but invaluable gift in the Sicilian heat. Evenings were filled with Italian dishes (I must have eaten more aubergine and octopus than ever before!) and a welcome variety of vegetarian options. The gala dinner by the seashore was unforgettable: live music, dancing, conversations under the<\/span><\/span><\/p>\n

\"the

AIED 2025: registration day \u2014 and the most valuable gift in Palermo\u2019s heat, a water bottle.<\/p><\/div>\n

stars, and the\u00a0<\/span>sparkling view of ships in the distance. Palermo itself buzzed with life\u2014street orchestras, flower-filled squares, and spontaneous meetups with colleagues who quickly became friends.<\/span>\u00a0<\/span><\/span>\u00a0<\/span><\/p>\n

From Answer Engine to Socratic Tutor: The Core Shift<\/b>\u00a0<\/p>\n

The central question running through the conference was not whether AI belongs in education, but how it should function. A recurring theme\u00a0emerged\u00a0with remarkable consistency: AI should not simply provide answers\u2014instead, it should guide students in finding answers, encouraging reasoning, exploration, and deeper engagement.\u00a0<\/p>\n

This\u00a0represents\u00a0a fundamental shift in how we conceptualise AI’s role. Rather than functioning as an answer engine that short-circuits the learning process, AI can act as a Socratic tutor\u2014one that poses questions, prompts reflection, and scaffolds thinking without doing the cognitive work for students. This philosophy resonated throughout keynotes, paper presentations, and informal conversations alike.\u00a0<\/p>\n

One particularly memorable keynote came from Dr Kristen DeCerbo, Chief Learning Officer at Khan Academy, who spoke about moving education from the transfer of information to transforming learner outcomes. She traced the arc from television to the internet to AI, highlighting how each wave of technology reshaped learning. Crucially, she emphasised that AI should guide students to find answers\u2014not simply hand them over. She referenced\u00a0Khanmigo, Khan Academy’s AI tutor, not as an answer machine but as a guide for problem-solving. The message was clear: the future of AI in education lies in collaboration, not substitution.\u00a0<\/p>\n

Pedagogical Frameworks: Making AI Work for Learning<\/b>\u00a0<\/p>\n

Several sessions explored practical frameworks for implementing AI in educationally sound ways. The ICAP framework (Interactive, Constructive, Active, Passive learning), developed by cognitive science researcher Michelene Chi and her colleague Ruth Wylie, featured prominently in discussions about how AI can support higher levels of cognitive engagement from Passive, to Active, to Constructive, to Interactive. Rather than allowing students to passively consume answers, well-designed AI tools can prompt them to interact, construct arguments, and take cognitive ownership of their learning.\u00a0<\/p>\n

Discussions also examined how teachers might use AI to generate questions\u2014selecting the best ones to challenge students\u2014and to provide formative feedback on essays and assignments. This approach\u00a0isn’t\u00a0about outsourcing the teacher’s role but about saving time and scaffolding feedback, allowing educators to focus on the deeper pedagogical strategies that matter most.\u00a0<\/p>\n

A particularly striking framework came from discussions of activity theory, which envisions AI as a tool embedded within the triangle of students, teachers, and outcomes, alongside rules and responsibilities. This helped me see AI not as an\u00a0external add-on but as part of the educational ecosystem itself\u2014a perspective that resonates with my own experience using AI-powered features in NVivo, where the technology augments rather than replaces analytical judgement.\u00a0<\/p>\n

Voices from the Field: What Educators Are Doing<\/b>\u00a0<\/p>\n

One of the richest aspects of AIED was hearing directly from educators and researchers about their practical implementations:\u00a0\u00a0<\/p>\n

\"Smiling

Lunch breaks: where research discussions continued with laughter and new connections.<\/p><\/div>\n

Christine Fox shared her curiosity about how intelligent tutoring systems (ITS) are being used in real courses, highlighting the gap between research prototypes and classroom reality.\u00a0<\/p>\n

Bruno\u00a0Poellhuber\u00a0described developing an intelligent biology tutor through user-centred design with teachers and students\u2014an approach that ensures AI tools meet actual pedagogical needs rather than imposing technological solutions.\u00a0<\/p>\n

Ute Fiedler offered a particularly compelling example from Nova Scotia Community College, where she has trained GPTs to act as teaching assistants. These AI assistants can answer syllabus questions, explain content, and even apply rubrics to student work\u2014demonstrating\u00a0how AI can handle routine tasks while freeing instructors for more complex pedagogical interactions.\u00a0<\/p>\n

Informal polls revealed the tools people are using most: ChatGPT, Claude, Gemini, DeepSeek, and open-source models like\u00a0LLaMA. Opinions varied on their relative strengths, but what struck me was the spirit of experimentation and adaptation. Benjamin Nye offered a useful comparative assessment: while GPT 4.5 has proven reliable but suffers from slowness,\u00a0high costs, and ambiguous practical benefits, Google’s new\u00a0LearnLM\u00a0(based on Gemini Flash 2.5) shows\u00a0particular promise\u00a0for creating educational content. Claude’s performance\u00a0remains\u00a0acceptable, though ongoing evaluation continues.\u00a0<\/p>\n

The European Digital Education Hub (EDEH) presented a thought-provoking report on explainable AI (XAI) in education, covering detection tools, automated grading, and legal and ethical dimensions. Their work on building actionable guidelines for teachers and developers addresses a critical need: as AI becomes more prevalent in education, transparency and accountability become essential.\u00a0<\/p>\n

Posters, Research, and Critical Perspectives<\/b>\u00a0<\/p>\n

The poster sessions were particularly energising. One study explored students’ emotions while using AI\u2014a crucial reminder that learning is affective as well as cognitive. Another examined how AI can support emotional awareness in students during mathematics learning by creating visual representations. Several posters focused on using AI to reduce teachers’ cognitive load, a practical concern that could make the difference between AI adoption and rejection.\u00a0<\/p>\n

Attendees recommended Failure to Disrupt: Why Technology Alone Can’t Transform Education by Justin Reich\u2014a sobering counterpoint to the conference’s enthusiasm. Reich argues that while AI brings excitement, technology alone\u00a0won’t\u00a0address deep-rooted educational challenges without thoughtful pedagogy, equity, and systemic change. This critical perspective is essential: AI holds enormous promise, but we must remain thoughtful and critical in its adoption, not swept up in technological determinism.\u00a0<\/p>\n

Key Themes: What Emerged Across Sessions<\/b>\u00a0<\/p>\n

Several themes echoed throughout the conference:\u00a0<\/p>\n

Productive Struggle<\/b>: AI should create friction that matters, pushing students to wrestle with ideas rather than making learning too easy. This connects to decades of research on desirable difficulties and the importance of effortful learning.\u00a0<\/p>\n

Curiosity as Currency<\/b>: In the age of LLMs, curiosity and judgement are more valuable than memorising facts. Education must shift toward cultivating dispositions and capabilities that AI cannot replicate.\u00a0<\/p>\n

AI Literacy for Teachers<\/b>: Professional development needs to give teachers hands-on experience with AI tools, helping them build comfort and confidence. Teachers cannot thoughtfully integrate tools they\u00a0don’t\u00a0understand.\u00a0<\/p>\n

Human\u2013AI Collaboration<\/b>: The best future is not AI replacing humans but humans and AI learning together, each contributing their unique strengths to the educational process.\u00a0<\/p>\n

Equity and Access<\/b>: Multiple sessions raised concerns about who has access to sophisticated AI tools and whether AI might widen existing educational inequalities rather than closing them.\u00a0<\/p>\n

Looking Ahead<\/b>: Five Trends Shaping AI in Education\u00a0<\/p>\n

Reflecting on the conference, I see five major trends likely to shape the future of AI in education:\u00a0<\/p>\n

    \n
  1. AI as Co-Teacher<\/b>: From lesson planning to rubrics, AI will increasingly support\u2014not replace\u2014teachers, amplifying their ability to personalise learning and respond to individual student needs.<\/li>\n
  2. Explainable and Ethical AI<\/b>: Students, teachers, and policymakers will demand transparency and responsibility in AI systems. Black box algorithms will face growing scrutiny.<\/li>\n
  3. Personalised Learning at Scale<\/b>: Large language models will help create adaptive pathways where every student can progress at their own pace, while still being guided by strong pedagogical principles.<\/li>\n
  4. Integration Beyond the Classroom<\/b>: AIwon’tstop at assignments\u2014it will support wellbeing, emotional intelligence, and lifelong learning skills, recognising that education encompasses more than academic content.\u00a0<\/li>\n
  5. Open Source and Democratisation<\/b>: Open models likeLLaMAand DeepSeek will give educators more flexibility and reduce dependency on a few large technology companies, potentially addressing equity concerns.\u00a0<\/li>\n<\/ol>\n

    What This Means for My Practice<\/b>\u00a0<\/p>\n

    Returning to Manchester, I find myself thinking differently about the questions that brought me to Palermo. Is using AI plagiarism or a tool for responsible use? The answer, I now believe, lies in how we frame it pedagogically.\u00a0<\/p>\n

    Just as NVivo’s AI features enhance qualitative analysis without replacing analytical thinking, generative AI can enhance learning without replacing the cognitive work that makes education meaningful. The key is designing learning experiences where AI serves as a Socratic tutor\u2014prompting questions, scaffolding exploration, and supporting metacognition\u2014rather than as an answer engine that short-circuits intellectual development.\u00a0<\/p>\n

    This means I need to:<\/b>\u00a0<\/p>\n