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MAI-A Proactive Speech Agent for Metacognitive Mediation in Collaborative Learning

Edwards, Justin; Nguyen, Andy; Sobocinski, Marta; Lämsä, Joni; De Araujo, Adelson; Dang, Belle; Whitehead, Ridwan; Roberts, Anni Sofia; Kaarlela, Matti; Järvela, Sanna (2024-07-08)

 
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https://doi.org/10.1145/3640794.3665585

Edwards, Justin
Nguyen, Andy
Sobocinski, Marta
Lämsä, Joni
De Araujo, Adelson
Dang, Belle
Whitehead, Ridwan
Roberts, Anni Sofia
Kaarlela, Matti
Järvela, Sanna
ACM
08.07.2024

Justin Edwards, Andy Nguyen, Marta Sobocinski, Joni Lämsä, Adelson de Araujo, Belle Dang, Ridwan Whitehead, Anni-Sofia Roberts, Matti Kaarlela, and Sanna Jarvela. 2024. MAI - A Proactive Speech Agent for Metacognitive Mediation in Collaborative Learning. In Proceedings of the 6th ACM Conference on Conversational User Interfaces (CUI '24). Association for Computing Machinery, New York, NY, USA, Article 46, 1–5. https://doi.org/10.1145/3640794.3665585

https://rightsstatements.org/vocab/InC/1.0/
© 2024 Copyright held by the owner/author(s). This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in Proceedings of the 6th Conference on ACM Conversational User Interfaces, CUI 2024, http://dx.doi.org/10.1145/3640794.3665585.
https://rightsstatements.org/vocab/InC/1.0/
doi:https://doi.org/10.1145/3640794.3665585
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https://urn.fi/URN:NBN:fi:oulu-202502061496
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Abstract

We introduce MAI - a proactive speech agent aimed at enhancing metacognitive awareness among learners in collaborative learning settings. Background is presented around Socially Shared Regulation of Learning and the role of metacognition in learning. Next, the design of the rules that MAI uses to prompt learners and mediate metacognition are introduced. We describe the conditions in which MAI has been piloted thus far, including as a Wizard of Oz prototype and as a fully functional prototype using natural language processing. We discuss the ethical considerations that went into the prototyping and testing of MAI. Finally, we describe our next steps for understanding the interactions learners had with MAI already, planned design changes, and the future of testing the agent.
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