Using Large Language Models to Detect Socially Shared Regulation of Collaborative Learning
Open Access
- 26 April 2026
- conference paper
- Published by Association for Computing Machinery (ACM)
- p. 883-890
Abstract
No abstract availableAll Related Versions
Funding Information
- National Science Foundation (DRL-2112635)
- Institute of Education Sciences (R305C240010)
This publication has 24 references indexed in Scilit:
- Examining socially shared regulation of learning in medical training: the interplay of heart rate change points on regulatory interactionsEuropean Journal of Psychology of Education, 2025
- Rethinking the Potential of Multimodality in Collaborative Problem Solving Diagnosis with Large Language Models2025
- Using collaborative interactivity metrics to analyze students' problem-solving behaviors during STEM+C computational modeling tasksLearning and Individual Differences, 2025
- Towards a Human-in-the-Loop LLM Approach to Collaborative Discourse Analysis2024
- A First Step in Using Machine Learning Methods to Enhance Interaction Analysis for Embodied Learning Environments2024
- The Dynamics Between Self-Regulated Learning and Learning Outcomes: an Exploratory Approach and ImplicationsMetacognition and Learning, 2022
- Domain-Specific Modeling Languages in Computer-Based Learning Environments: a Systematic Approach to Support Science Learning through Computational ModelingInternational Journal of Artificial Intelligence in Education, 2020
- Mine the process: investigating the cyclical nature of upper primary school students’ self-regulated learningInstructional Science, 2020
- C2STEM: a System for Synergistic Learning of Physics and Computational ThinkingJournal of Science Education and Technology, 2019
- Measuring Self-Regulated Learning2000