From Tool to Teacher: Rethinking Search Systems as Instructive Interfaces

2026-01-12

AI Summary

This study addresses a critical gap in current information retrieval systems, which predominantly prioritize result optimization while neglecting the cultivation of users’ search strategies and critical thinking skills. Introducing a pedagogical perspective, this work proposes the concept of a “scaffolding interface” that reconceptualizes search and conversational AI as an active instructional system. Grounded in seven established frameworks from education and behavioral science, the design integrates query suggestions, source labeling, and agent-based techniques to support learning-oriented interactions. Through two representative search tasks, the study empirically demonstrates how this approach effectively enhances users’ abilities in critical evaluation, metacognitive reflection, and strategic transfer. The findings offer both theoretical grounding and a design paradigm for developing information systems with intrinsic educational value.

Technology Category

• Humans and AI: Intelligent User Interfaces
• Search and Optimization: Learning to Search
• Data Mining & Knowledge Management: Conversational Systems for Recommendation & Retrieval

Application Category

• Search and Retrieval-Augmented AI: Agentic search
• User Modeling, Personalization and Recommendation: Fairness-aware retrieval and ranking
• Semantics and Knowledge: Applications of semantic technologies for improving search, browsing, recommendation, personalization

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.

Problem

• information access systems
• search systems
• user learning
• critical awareness
• search strategies

Innovation

• instructive interfaces
• pedagogical perspective
• information access systems
• metacognitive reflection
• critical evaluation