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Synapse
March 29, 20260 citationsOpen Access

Common ground improves learning with conversational agents

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AKAnita KörnerATAntonia TolzinAJAndreas Janson

Key Points

  • This research aims to understand how common ground influences learning effectiveness with conversational agents.
  • Conducted an in-class experiment with students using two types of conversational agents.
  • One agent emphasized common ground, while the control agent did not.
  • Evaluated learning experiences and assessed knowledge retention after the learning unit.
  • Students using the common ground agent performed better on a post-study knowledge test.
  • Participants engaged longer with the common ground conversational agent.

Abstract

Although conversational agents are successfully applied in teaching, it is largely unclear which communication principles should be employed to optimise learning. We examine the influence of common ground (i.e. shared knowledge on which to build during conversation) on learning. In an in-class experiment, students studied with one of two pedagogical conversational agents. The control version provided information without emphasising grounding, whereas the common ground version emphasised grounding, for example, by encouraging students to monitor and repair common ground. After the learning unit, students evaluated their learning experience and the pedagogical conversational agent, after which they were tested on the studied material. Students in the common ground (vs. the control) condition performed better in a post-study knowledge test and engaged longer with the pedagogical conversational agent. Thus, the common ground emphasis facilitated learning with a conversational agent, indicating that grounding principles should be incorporated when designing conversational agents.

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Cite This Study

Körner et al. (2025) studied this question.

synapsesocial.com/papers/69c8c2b8de0f0f753b39d162https://doi.org/10.17170/kobra-2026032712028
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Seeking common ground with a conversational chatbot2025
  2. 2Common ground in artificial intelligence applications2025
  3. 3Empathic Grounding: Explorations using Multimodal Interaction and Large Language Models with Conversational Agents2024 · 13 citations
  4. 4Exploring the Impact of Generative AI-Powered Conversational Agents on Student Learning: A Systematic Review and Meta-Analysis Grounded in Activity Theory2026 · 1 citations
  5. 5Triadic Agent Framework for Grammar-Focused Role-Playing: Pedagogical Effects and Educational Experiences of Generative AI, Teachers, and Peers2026