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  • Multimodal analytics for collaborative teacher reflection of human-ai hybrid teaching: design opportunities and constraints
Title: Multimodal analytics for collaborative teacher reflection of human-ai hybrid teaching: design opportunities and constraints
Past research shows that teachers benefit immensely from reflecting on their classroom practices. At the same time, adaptive and artificially intelligent (AI) tutors are shown to be highly effective for students, especially when teachers are involved in supporting students’ learning. Yet, there is little research on how to support teachers to reflect on their practices around AI tutors. We posit that analytics built on multimodal data from the classroom (e.g., teacher position, student-AI interaction) would be beneficial in providing effective scaffolding and evidence for teachers’ collaborative reflection on human-AI hybrid teaching. To better understand the design opportunities and constraints of a future tool for teacher reflection, we conducted storyboarding sessions with seven in-service teachers. Our analysis revealed that certain modalities (e.g., position v. video) might be more beneficial and less constrained than others in identifying reflection-worthy moments and trends. We discuss teachers’ needs for reflection in classrooms with AI tutors and their boundaries in using multimodal analytics.  more » « less
Award ID(s):
2119501
PAR ID:
10470770
Author(s) / Creator(s):
; ; ; ; ;
Editor(s):
Viberg, O.; Jivet, I.; Muñoz-Merino, P.; Perifanou, M.; Papathoma, T.
Publisher / Repository:
Springer
Date Published:
Edition / Version:
Proceedings of the 18th European Conference on Technology-Enhanced Learning, EC-TEL 2023
Page Range / eLocation ID:
580–585
Subject(s) / Keyword(s):
Teachers, Multimodal Analytics, Storyboards, Reflection, Human-AI Partnerships, Collaboration
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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