From Tool to Teacher: Rethinking Search Systems as Instructive Interfaces
David Elsweiler
TL;DR
This work reframes information access systems as instructional environments that can cultivate user information literacy and strategic thinking, not merely retrieve content. It applies seven didactic frameworks from education and psychology to analyze current and emerging interfaces (e.g., query suggestions, source labels, GenAI agents, and memory-enabled chats) across two illustrative tasks. The analysis yields design implications and showcases hypothetical systems that embody scaffolding, cognitive apprenticeship, and self-regulated learning to foster long-term skill transfer. By emphasizing instructional value and evaluation beyond immediate task success, the paper argues for learning-focused information systems that support reflective, autonomous, and resilient information seekers.
Abstract
Information access systems such as search engines and generative AI are central to how people seek, evaluate, and interpret information. Yet most systems are designed to optimise retrieval rather than to help users develop better search strategies or critical awareness. This paper introduces a pedagogical perspective on information access, conceptualising search and conversational systems as instructive interfaces that can teach, guide, and scaffold users' learning. We draw on seven didactic frameworks from education and behavioural science to analyse how existing and emerging system features, including query suggestions, source labels, and conversational or agentic AI, support or limit user learning. Using two illustrative search tasks, we demonstrate how different design choices promote skills such as critical evaluation, metacognitive reflection, and strategy transfer. The paper contributes a conceptual lens for evaluating the instructional value of information access systems and outlines design implications for technologies that foster more effective, reflective, and resilient information seekers.