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Computer-Supported Collaborative Learning (CSCL) environments are often designed to support collaboration within a single digital platform. However, with the growth of technology in classrooms, students often find themselves working in multiple contexts (i.e., a student might work face-to-face with a peer on one task and then move to engaging in an online discussion for homework). We have created a CSCL environment that aims to support student help-giving across a variety of digital platforms. This paper describes three cycles of a design-based research study that aims to design a system to support help-giving and improve interaction quantity and quality across different contexts as well as to better understand whether students benefit by the addition of multiple contexts. The paper shares major refinements across the three cycles that worked to balance research, pedagogical, and technological goals to improve students’ help-giving behavior in a middle-school mathematics classroom.
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This content will become publicly available on July 14, 2025
Math in Motion: Analyzing Real-Time Student Collaboration in Computer-Supported Learning Environments
With the support of digital learning platforms, synchronous and collaborative learning has become a prominent learning paradigm in mathematics education. Computer-Supported Collaborative Learning (CSCL) has emerged as a valuable tool for enhancing mathematical discourse, problem solving, and ultimately learning outcomes. This paper presents an innovative examination of Graspable Math (GM), a dynamic mathematic notation and learning online platform, to enable synchronous, collaborative learning between pairs of students. Through analyzing students' online log data, we adopt a data-driven method to better understand the intricate dynamics of collaborative learning in mathematics as it happens. Specifically, we apply frequency distributions, cluster analysis to present students' dynamic interaction patterns and identify distinctive profiles of collaboration. Our findings reveal several collaboration profiles that emerge through these analyses. This research not only bridges the gap in current CSCL tools for mathematics, but also provides empirical insights into the effective design and implementation of such tools. The insights gained from this research offer implications for the design of digital learning tools that support effective and engaging collaborative learning experiences.
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- Award ID(s):
- 2331379
- PAR ID:
- 10531981
- Editor(s):
- Benjamin, Paaßen; Carrie, Demmans Epp
- Publisher / Repository:
- International Educational Data Mining Society
- Date Published:
- Format(s):
- Medium: X
- Right(s):
- Creative Commons Attribution 4.0 International
- Sponsoring Org:
- National Science Foundation
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