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Surveying Teachers' Preferences And Boundaries Regarding Human-Ai Control In Dynamic Pairing Of Students For Collaborative Learning, Kexin Bella Yang, Luettamae Lawrence, Vanessa Echeverría, Boyuan Guo, Nikol Rummel, Vincent Aleven
Surveying Teachers' Preferences And Boundaries Regarding Human-Ai Control In Dynamic Pairing Of Students For Collaborative Learning, Kexin Bella Yang, Luettamae Lawrence, Vanessa Echeverría, Boyuan Guo, Nikol Rummel, Vincent Aleven
Instructional Technology and Learning Sciences Faculty Publications
Orchestration tools may support K-12 teachers in facilitating student learning, especially when designed to address classroom stakeholders’ needs. Our previous work revealed a need for human-AI shared control when dynamically pairing students for collaborative learning in the classroom, but offered limited guidance on the role each agent should take. In this study, we designed storyboards for scenarios where teachers, students and AI co-orchestrate dynamic pairing when using AI-based adaptive math software for individual and collaborative learning. We surveyed 54 math teachers on their co-orchestration preferences. We found that teachers would like to share control with the AI to lessen their …