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Exploring How Agent Voice Accents Shape Human-AI Collaboration in K-12 Group Learning

● high · 2026-06-12equity, generative-ai, human-in-the-loop, k-12, llm, student-experience, human-ai-collaboration, ai-literacy, teacher-role

Ravi, Stevens, Hurt, Hanks, Lin & Anderson (2026).

Ravi et al. investigate how the voice accent of a Generative AI conversational peer agent shapes learners' perceptions, trust, and interactional dynamics in K 12 group learning. While prior work examined agent accent effects in one-to-one settings, little is known about how these effects manifest in multi-party group contexts — a critical gap as AI peer agents enter collaborative classrooms.

The between-subjects mixed-methods study involved 33 teachers interacting with a GenAI voice agent in three accent conditions — British, Indian, and African American. Key findings:

1. The British-accented agent was largely treated as a tool and engaged with in detached, utility-based ways — less anthropomorphized, more like an external resource.

2. Indian- and African American-accented agents were more readily anthropomorphized and integrated as peers — building stronger trust, engagement, and reliance over time.

3. These role expectations influenced collaboration dynamics: turn-taking, questioning patterns, and perceived social presence all shifted based on accent condition.

The findings advance understanding of how GenAI's sociolinguistic design features shape group dynamics in CSCL (computer-supported collaborative learning), with implications for designing culturally inclusive AI partners. The work connects to Human AI Collaboration debates about teacher and AI roles in collaborative classrooms, and raises important questions about how accent may inadvertently reinforce or disrupt power dynamics in educational AI.

Connected Concepts

  • Generative AI
  • K 12
  • Intelligent Tutoring
  • Equity
  • Human AI Collaboration
  • Teacher Role
  • AI Literacy

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    • Citation

    Ravi, P., Stevens, C., Hurt, B., Hanks, B., Lin, G., & Anderson, E. (2026). Exploring How Agent Voice Accents Shape Human-AI Collaboration in K-12 Group Learning. arXiv:2606.12805.