Curiosity as Linguistic Intervention: Using LLM Tutoring Dialogues to Influence Exploratory Learning Behavior

2026-06-21

AI Summary

This study addresses the challenge of effectively eliciting exploratory learning behaviors through language-based interventions. Grounded in Berlyne’s collative variables theory, it introduces the CURIOBOT framework, which operationalizes curiosity-driven dimensions—novelty, complexity, conflict, and uncertainty—into adaptive linguistic strategies tailored for conversational tutoring. The proposed approach enhances learners’ exploratory engagement independently, without compromising instructional quality. Empirical results demonstrate that, within a fixed time budget, curiosity-oriented interventions can increase dialogue turns by up to 2.4 times and significantly improve question-asking initiative, conversational autonomy, productive struggle, and observable curiosity.

Abstract

Large Language Models (LLMs) provide a new opportunity to study how language shapes exploratory cognition because conversational strategies can be systematically manipulated at inference time. We introduce CURIOBOT, a framework that operationalizes Berlyne's collative variables, novelty, complexity, conflict, and uncertainty, as adaptive linguistic interventions for conversational tutoring. Across 270 tutoring conversations spanning multiple model families, domains, and topic complexity levels, curiosity-oriented interventions consistently increased exploratory learner behaviors, producing up to 2.4x more conversational turns under fixed time budgets. To measure these effects, we further introduce a learner-centered evaluation framework capturing exploratory questioning, conversational agency, productive struggle, and observable curiosity. Learner-side gains persisted even when tutor-side instructional quality remained unchanged, suggesting that curiosity functions as a partially independent interaction-level mechanism. More broadly, our results demonstrate that LLM-mediated dialogue can serve as a scalable experimental framework for studying how language shapes exploratory learning behavior.

Problem

• curiosity
• exploratory learning
• linguistic intervention
• conversational tutoring
• LLM-mediated dialogue

Innovation

• curiosity-driven intervention
• exploratory learning
• large language models
• conversational tutoring
• collative variables