Exploring The Interaction-Outcome Paradox: Seemingly Richer and More Self-Aware Interactions with LLMs May Not Yet Lead to Better Learning

November 12, 2025 Β· Declared Dead Β· πŸ› arXiv.org

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Authors Rahul R. Divekar, Sophia Guerra, Lisette Gonzalez, Natasha Boos arXiv ID 2511.09458 Category cs.HC: Human-Computer Interaction Citations 0 Venue arXiv.org Last Checked 4 months ago
Abstract
While Large Language Models (LLMs) have transformed the user interface for learning, moving from keyword search to natural language dialogue, their impact on educational outcomes remains unclear. We present a controlled study (N=20) that directly compares the learning interaction and outcomes between LLM and search-based interfaces. We found that although LLMs elicit richer and nuanced interactions from a learner, they do not produce broadly better learning outcomes. In this paper, we explore this the ``Interaction-Outcome Paradox.'' To explain this, we discuss the concept of a cognitive shift: the locus of student effort moves from finding and synthesizing disparate sources (search) to a more self-aware identification and articulation of their knowledge gaps and strategies to bridge those gaps (LLMs). This insight provides a new lens for evaluating educational technologies, suggesting that the future of learning tools lies not in simply enriching interaction, but in designing systems that scaffold productive cognitive work by leveraging this student expressiveness.
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