Exploring Shared Monitoring in Large Language Model (LLM)-Supported Online Collaborative Problem Solving for High-Cohesion and Low-Cohesion Groups

IF 5.7 2区教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH

Journal of Computer Assisted Learning Pub Date : 2026-04-15 DOI:10.1002/jcal.70249

Xiaoyun Liu, Xu Du, Jui-Long Hung, Hao Li, Shuoqiu Yang, Yiqian Xie

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引用次数: 0

Abstract

Background

Recent research increasingly highlights the central role of interventions in enhancing shared monitoring during collaborative problem-solving. However, traditional intervention approaches suffer from limitations in timeliness and adaptability. Large language model (LLM), equipped with deep semantic parsing and contextual perception, can dynamically detect latent challenges and provide targeted, timely, context-sensitive feedback.

Objectives

This study examines how LLM-supported interventions affect group shared monitoring during dynamic CPS processes.

Methods

This study designed a collaborative problem-solving platform integrated with LLM, and 28 students from a university in China participated in CPS activities. Chi-square tests, conditional random fields, linear mixed models and correlation analyses were adopted to examine the changes in both monitoring behaviour and equality of monitoring participation in high-cohesion (HCGs) and low-cohesion groups (LCGs) after LLM-supported group metacognitive scaffolding (LLM-GMS) intervention, as well as their effects on collaborative performance.

Results and Conclusions

The results show that (1) LLM-GMS activated more socio-cognitive and behavioural monitoring in HCGs, whereas LCGs mainly exhibited heightened behavioural monitoring. (2) Descriptive analyses revealed divergent trends in monitoring participation equality across group types, with HCGs showing increased equality and LCGs exhibiting a decline. (3) In HCGs, socio-emotional monitoring was positively associated with collaborative performance, whereas participation equality and behavioural monitoring exhibited negative associations with collaborative performance. In contrast, among LCGs, behavioural monitoring was positively related to performance, whereas socio-cognitive monitoring was unexpectedly negatively associated with performance.

Implications

These findings highlight that LLM-GMS can be a valuable tool for supporting collaborative learning, but its effectiveness depends on group characteristics and its implementation approach.

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探索大语言模型（LLM）支持的高内聚和低内聚群体在线协作问题解决中的共享监控

最近的研究越来越强调干预措施在协作解决问题过程中加强共享监测的核心作用。然而，传统的干预方法在时效性和适应性方面存在局限性。大型语言模型（LLM）具有深度语义解析和上下文感知能力，可以动态发现潜在的挑战，并提供有针对性的、及时的、上下文敏感的反馈。目的：本研究探讨llm支持的干预措施如何影响动态CPS过程中的群体共享监测。方法本研究设计了一个与LLM相结合的协同解决问题平台，并让28名来自中国某高校的学生参与到CPS活动中。采用卡方检验、条件随田野、线性混合模型和相关分析，考察llm支持的群体元认知脚手架（LLM-GMS）干预后，高凝聚力（hcg）和低凝聚力（LCGs）群体监测行为和监测参与平等性的变化及其对协作绩效的影响。结果与结论结果表明：(1)LLM-GMS激活的社会认知和行为监测更多，而lcg主要表现为行为监测增强。(2)描述性分析显示，不同群体类型的参与平等监测趋势存在差异，hcg群体的参与平等程度有所提高，LCGs群体的参与平等程度有所下降。(3)社会情绪监测与合作绩效呈正相关，参与平等和行为监测与合作绩效呈负相关。相反，在lcg中，行为监测与表现呈正相关，而社会认知监测与表现出乎意料地呈负相关。这些发现强调LLM-GMS可以成为支持协作学习的有价值的工具，但其有效性取决于群体特征和实施方法。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Computer Assisted Learning EDUCATION & EDUCATIONAL RESEARCH-

CiteScore

9.70

自引率

6.00%

发文量

116

期刊介绍： The Journal of Computer Assisted Learning is an international peer-reviewed journal which covers the whole range of uses of information and communication technology to support learning and knowledge exchange. It aims to provide a medium for communication among researchers as well as a channel linking researchers, practitioners, and policy makers. JCAL is also a rich source of material for master and PhD students in areas such as educational psychology, the learning sciences, instructional technology, instructional design, collaborative learning, intelligent learning systems, learning analytics, open, distance and networked learning, and educational evaluation and assessment. This is the case for formal (e.g., schools), non-formal (e.g., workplace learning) and informal learning (e.g., museums and libraries) situations and environments. Volumes often include one Special Issue which these provides readers with a broad and in-depth perspective on a specific topic. First published in 1985, JCAL continues to have the aim of making the outcomes of contemporary research and experience accessible. During this period there have been major technological advances offering new opportunities and approaches in the use of a wide range of technologies to support learning and knowledge transfer more generally. There is currently much emphasis on the use of network functionality and the challenges its appropriate uses pose to teachers/tutors working with students locally and at a distance. JCAL welcomes: -Empirical reports, single studies or programmatic series of studies on the use of computers and information technologies in learning and assessment -Critical and original meta-reviews of literature on the use of computers for learning -Empirical studies on the design and development of innovative technology-based systems for learning -Conceptual articles on issues relating to the Aims and Scope