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TutorUp: What If Your Students Were Simulated? Training Tutors to Address Engagement Challenges in Online Learning

Author(s)
Pan, Sitong; Schmucker, Robin; Garcia Bulle Bueno, Bernardo; Llanes, Salome Aguilar; Albo Alarc?n, Fernanda; Zhu, Hangxiao; Teo, Adam; Xia, Meng; ... Show more Show less
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Abstract
With the rise of online learning, many novice tutors lack experience engaging students remotely. We introduce TutorUp, a Large Language Model (LLM)-based system that enables novice tutors to practice engagement strategies with simulated students through scenario-based training. Based on a formative study involving two surveys (N1 = 86, N2 = 102) on student engagement challenges, we summarize scenarios that mimic real teaching situations. To enhance immersion and realism, we employ a prompting strategy that simulates dynamic online learning dialogues. TutorUp provides immediate and asynchronous feedback by referencing tutor-students online session dialogues and evidence-based teaching strategies from learning science literature. In a within-subject evaluation (N = 16), participants rated TutorUp significantly higher than a baseline system without simulation capabilities regarding effectiveness and usability. Our findings suggest that TutorUp provides novice tutors with more effective training to learn and apply teaching strategies to address online student engagement challenges.
Description
CHI ’25, Yokohama, Japan
Date issued
2025-04-25
URI
https://hdl.handle.net/1721.1/162801
Publisher
ACM|CHI Conference on Human Factors in Computing Systems
Citation
Sitong Pan, Robin Schmucker, Bernardo Garcia Bulle Bueno, Salome Aguilar Llanes, Fernanda Albo Alarcón, Hangxiao Zhu, Adam Teo, and Meng Xia. 2025. TutorUp: What If Your Students Were Simulated? Training Tutors to Address Engagement Challenges in Online Learning. In Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems (CHI '25). Association for Computing Machinery, New York, NY, USA, Article 20, 1–18.
Version: Final published version
ISBN
979-8-4007-1394-1

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