Cited by 7Intelligent Tutoring Systems and Adaptive LearningInnovative Teaching and Learning MethodsMathematics Education and Teaching Techniques

Does Feedback on Talk Time Increase Student Engagement? Evidence from a Randomized Controlled Trial on a Math Tutoring Platform

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Demszky, Dorottya, Wang, Rose, Geraghty, Sean, Yu, Carol·2024·Proceedings of the 14th Learning Analytics and Knowledge Conference

Abstract

Providing ample opportunities for students to express their thinking is pivotal to their learning of mathematical concepts. We introduce the Talk Meter, which provides in-the-moment automated feedback on student-teacher talk ratios. We conduct a randomized controlled trial on a virtual math tutoring platform (n=742 tutors) to evaluate the effectiveness of the Talk Meter at increasing student talk. In one treatment arm, we show the Talk Meter only to the tutor, while in the other arm we show it to both the student and the tutor. We find that the Talk Meter increases student talk ratios in both treatment conditions by 13-14%; this trend is driven by the tutor talking less in the tutor-facing condition, whereas in the student-facing condition it is driven by the student expressing significantly more mathematical thinking. Through interviews with tutors, we find the student-facing Talk Meter was more motivating to students, especially those with introverted personalities, and was effective at encouraging joint effort towards balanced talk time. These results demonstrate the promise of in-the-moment joint talk time feedback to both teachers and students as a low cost, engaging, and scalable way to increase students’ mathematical reasoning.

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Crossref · 10.1145/3636555.3636924

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  • Students' motivation to complete the program changes when completion is tied to a grade or placement in an advanced course.

    “Finally, students' motivation to complete the program changes when completion is tied to a grade or placement in an advanced course (Chamberlin et al., 2023;Demszky et al., 2024;Rodríguez Rincón et al., 2024).”

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Authors
Demszky, D., Wang, R., Geraghty, S., & Yu, C.
Affiliations
  • Stanford University (US)
  • Cuemath, India
Venue
Proceedings of the 14th Learning Analytics and Knowledge Conference
Publisher
ACM
Published
2024-03-18
Pages
632-644
OpenAlex
W4392484082
Cited by
7
References
4
Citations by year
2025: 5 · 2024: 2
FWCI
1.69
Type
conference paper
Language
en
Open access
Locations
International Conference on Learning Analytics and Knowledge (LAK) (publishedVersion, cc-by)
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
  • Social Sciences › Psychology › Developmental and Educational Psychology › Innovative Teaching and Learning Methods
  • Social Sciences › Education › Mathematics Education and Teaching Techniques
Keywords
automated feedback, student talk time, student engagement, mathematical reasoning, student mathematical thinking, tutor-student interaction, introversion, online tutoring platform

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