Balancing Teacher and Student Agency: Co-Orchestration Tool Design Supporting Real-Time Dynamic Pairing
Kexin Bella Yang (1), Menghan Liu (2), Liyi Xu (1), Nikol Rummel (3), and Vincent Aleven (1) ((1) Human-Computer Interaction Institute, Carnegie Mellon University, USA, (2) University of Washington, USA, (3) Institute of Educational Research, Ruhr-Universit\"at Bochum, Germany)

TL;DR
This paper investigates how to design educational tools that balance control between teachers and students during real-time pairing, emphasizing agency, trust, and dynamic coordination.
Contribution
It introduces a design space for distributing control in classroom orchestration tools and offers empirical insights and recommendations for hybrid-control approaches.
Findings
Structured teacher guidance at the start enhances control balance.
Gradually increasing student autonomy supports effective learning.
Design recommendations facilitate hybrid-control in pairing contexts.
Abstract
In human-AI interaction, respecting user agency is essential for fostering trust and sustaining effective use of technology. In educational settings, dynamically integrating individual and collaborative learning offers pedagogical value by supporting personalized, self-paced learning experiences. Prior research has demonstrated the feasibility of this approach through intelligent tutoring systems and human-AI co-orchestration tools. However, how to balance teacher and student control in this process remains largely unexplored. This work explores the design space of how control can be distributed between teachers and students across the orchestration process, using participatory speed dating and a mixed-method analysis. We focus on three stages of the pairing process: before, during, and after, taking context in designing classroom orchestration tools that support teachers in dynamically…
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