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  • Using collaborative interactivity metrics to analyze students' problem-solving behaviors during STEM+C computational modeling tasks

This content will become publicly available on July 1, 2026

Title: Using collaborative interactivity metrics to analyze students' problem-solving behaviors during STEM+C computational modeling tasks
Recently, there has been a surge in developing curricula and tools that integrate computing (C) into Science, Technology, Engineering, and Math (STEM) programs. These environments foster authentic problem-solving while facilitating students’ concurrent learning of STEM+C content. In our study, we analyzed students’ behaviors as they worked in pairs to create computational kinematics models of object motion. We derived a domain-specific metric from students’ collaborative dialogue that measured how they integrated science and computing concepts into their problem-solving tasks. Additionally, we computed social metrics such as equity and turn-taking based on the students’ dialogue. We identified and characterized students’ planning, enacting, monitoring, and reflecting behaviors as they worked together on their model construction tasks. This study in-vestigates the impact of students’ collaborative behaviors on their performance in STEM+C computational modeling tasks. By analyzing the relationships between group synergy, turn-taking, and equity measures with task performance, we provide insights into how these collaborative behaviors influence students’ ability to construct accurate models. Our findings underscore the importance of synergistic discourse for overall task success, particularly during the enactment, monitoring, and reflection phases. Conversely, variations in equity and turn-taking have a minimal impact on segment-level task performance.  more » « less
Award ID(s):
2327708
PAR ID:
10650792
Author(s) / Creator(s):
; ; ;
Publisher / Repository:
Science Direct: https://www.sciencedirect.com/science/article/pii/S1041608025001001
Date Published:
Journal Name:
Learning and Individual Differences
Volume:
121
Issue:
C
ISSN:
1041-6080
Page Range / eLocation ID:
102724
Subject(s) / Keyword(s):
Collaborative problem solving Computational modeling Synergistic STEM+C learning Multimodal learning analytics
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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