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Title: Acknowledging Power Structures in the Design of AI-Based Orchestration Tools
Authors: Lawrence, LuEttaMae
Echeverria, Vanessa
Rummel, Nikol
Keywords: CSCL
Issue Date: 2023
Publisher: International Society of the Learning Sciences
Citation: Lawrence, L., Echeverria, V., & Rummel, N. (2023). Acknowledging power structures in the design of AI-based orchestration tools. In Damșa, C., Borge, M., Koh, E., & Worsley, M. (Eds.), Proceedings of the 16th International Conference on Computer-Supported Collaborative Learning - CSCL 2023 (pp. 173-176). International Society of the Learning Sciences.
Abstract: Classrooms are historically situated within hierarchical power structures. In traditional K-12 classrooms, teachers are positioned as the experts who makes decisions about learning, and students follow their instruction. This contrasts with approaches wherein teachers position students as having agency in how they learn and with whom. One way to disrupt more traditional power structures and support mutuality in the classroom is to leverage technology to provide an avenue to communicate and make decisions about learning. In this paper, we examine teachers’ views of shared control while designing an orchestration tool which it aimed at distributing power across teachers, students, and technology while students are moving between individual and collaborative activities. We discuss two case studies that highlight teachers’ nuanced views of how AI can be leveraged to support dynamic transitions for learning. Our contribution highlights a need to account for the range of teachers’ views about power structures when designing AI-based orchestration tools.
Description: Short Paper
Appears in Collections:ISLS Annual Meeting 2023

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