Common ground improves learning with conversational agents
Bibliographic Data
| ID | 21452045 |
|---|---|
| Authors | Anita Körner (0000-0003-3761-2118, University of Kassel, corresponding author), Antonia Tolzin (0009-0005-4110-4361, University of Kassel), Andreas Janson (0000-0003-3149-0340, University of St.Gallen), Jan Marco Leimeister (0000-0002-1990-2894, University of Kassel), Ralf Rummer (0000-0002-2568-0925, University of Kassel) |
| Year | 2026 |
| Volume | 45 |
| Issue | 5 |
| Pages | 932-948 |
| Publication date | 2026-03-16 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Behaviour and Information Technology (JOURNAL) |
| Journal identifiers | ISSN: 0144-929X • E-ISSN: 1362-3001 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/0144929x.2025.2541222 |
| OpenAlex | W4413203790 |
| Language | EN |
| Citations received | 2 |
| References cited | 128 |
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
Common ground · AI in Service Interactions · Artificial Intelligence · Communication · Computer Science · Psychology · Social Robot Interaction and HRI · Speech and dialogue systems
Using Language
Education at a Glance 2022
Living up to the chatbot hype
Intelligent tutoring systems
Revolutionizing education with AI
Effects of Feedback in a Computer-Based Learning Environment on Students’ Learning Outcomes
Real conversations with artificial intelligence
Audience Design in Meaning and Reference
Why is conversation so easy?
A Taxonomy of Social Cues for Conversational Agents
The Power of Feedback Revisited
Establishing and maintaining long-term human-computer relationships
Universal Principles in the Repair of Communication Problems
Improving Students’ Learning With Effective Learning Techniques
Developing and Validating Trust Measures for e-Commerce
Interacting with educational chatbots
Differentiating Instruction in Response to Student Readiness, Interest, and Learning Profile in Academically Diverse Classrooms
Delivering Cognitive Behavior Therapy to Young Adults With Symptoms of Depression and Anxiety Using a Fully Automated Conversational Agent (Woebot)
A Systematic Review of Research on Personalized Learning
Chatbots
Effectiveness of Intelligent Tutoring Systems
Are We There Yet? - A Systematic Literature Review on Chatbots in Education
The Relative Effectiveness of Human Tutoring, Intelligent Tutoring Systems, and Other Tutoring Systems
Grounding in communication.
Are People Polite to Computers? Responses to Computer‐Based Interviewing Systems 1
Learning Versus Performance
Understanding by addressees and overhearers
References in conversation between experts and novices.
Rediscovering the use of chatbots in education
Building a Stronger Casa
Reformulation of symptom descriptions in dialogue systems for fault diagnosis
Audience design and egocentrism in reference production during human-computer dialogue
Direct and indirect linguistic measures of common ground in dialogue studies involving a matching task
Effects of social skills on lexical alignment in human-human interaction and human-computer interaction
Anthropomorphism and social presence in Human–Virtual service assistant interactions
Trust through words
Anthropomorphic response
Someone out there? A study on the social presence of anthropomorphized chatbots
Make chatbots more adaptive
How to leverage anthropomorphism for chatbot service interfaces
Chatbots for learning
Understanding the effectiveness of automated feedback
Feasibility of adaptive teaching with technology
Pedagogical agent design for K-12 education
The power of affective pedagogical agent and self-explanation in computer-based learning
The synergistic effects in an AI-supported online scientific argumentation learning environment
The effectiveness of personalized technology-enhanced learning in higher education
Using a pedagogical agent to deliver conversational style instruction
Artificial intelligence for teaching and learning in schools
How pedagogical agents communicate with students
Psychological insights into the research and practice of embodied conversational agents, chatbots and social assistive robots
The effect of personal pronouns on users and the social role of conversational agents
The promise and challenges of generative AI in education
Examining the persuasiveness of text and voice agents
Speakers extrapolate community-level knowledge from individual linguistic encounters
Do AI chatbots improve students learning outcomes? Evidence from a meta‐analysis
Collaborating with technology-based autonomous agents
Uncovering the mechanisms of common ground in human–agent interaction
Audience Design in Collaborative Dialogue between Teachers and Students
Understanding friends and strangers
The effects of intended audience on message production and comprehension
Co-constructing intersubjectivity with artificial conversational agents
Machines and Mindlessness
Coordination of knowledge in communication
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Building machines that learn and think with people
A behaviourally informed chatbot increases vaccination rates in Argentina more than a one-way reminder
Promises and challenges of generative artificial intelligence for human learning
Linguistic alignment between people and computers
Elements of Discourse Understanding
The Preference for Self-Correction in the Organization of Repair in Conversation
| Unique citing works | 2 |
|---|---|
| Citations per year | 2 |
| Citation span | 2026 - 2026 (1) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 2 |