🤖🔍 What if your search engine or AI chatbot would teach you to search better? 🧠
Our perspective paper "From Tool to Teacher: Rethinking Search Systems as Instructive Interfaces" by David Elsweiler has been accepted to CHIIR 2026 - and proposes a pedagogical perspective on information access systems.
Search engines and generative AI are central to how we seek, evaluate, and interpret information. But most systems are still designed to just find relevant content - not to help users become better searchers.
💡 Our paper argues for a shift in perspective:
What if we treated search systems not just as tools, but as instructive interfaces - systems that teach and guide users' learning?
Drawing on seven didactic frameworks from education, psychology, and behavioural science - including scaffolding, nudging, boosting, and self-regulated learning - this paper:
- Reframes search and conversational AI as pedagogical environments
- Examines how system features like query suggestions, source labels, and agentic AI shape learning
- Shows how different design choices can foster critical evaluation, metacognitive reflection, and strategy transfer
- Introduces a conceptual lens for evaluating the instructional value of information access systems
In an era where people use search systems to navigate complex information landscapes that require critical thinking and judgement,
the question is no longer just "Did the system retrieve the right answer?"
It is also: "Did it help the user learn how to search better?"
🔗 Read the pre-print of the paper here: https://arxiv.org/abs/2601.08035 (external link, opens in a new window)
And come and discuss with us. We'd love your input! 💡
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