Team regulation, regulation of social activities or co-regulation: Different labels for effective regulation of learning in CSCL

Computer-supported collaborative learning (CSCL) is an approach to learning in which learners can actively and collaboratively construct knowledge by means of interaction and joint problem solving. Regulation of learning is especially important in the domain of CSCL. Next to the regulation of task performance, the interaction between learners who work in a CSCL environment needs to be regulated as well. Despite its importance, the regulation of learning in CSCL has received relatively little attention in research. In the contributions of this special issue different labels are used for various forms of regulation of learning during CSCL. During collaborative learning, the regulation of activities can take place at different levels of social interaction: the individual level, the dyadic level, and the group level. Regulative activities of all three levels are presented in the three studies. All studies have investigated whether the use of regulative activities affected performance, and have found that regulation at the dyadic and/or group level was positively related to group performance. In sum, these three contributions provide a constructive overview of the role of regulation of the (collaborative) learning process in CSCL, both in terms of the impact of regulation on learning processes and learning results as well as the influence of different kinds of support on the regulation of collaborative learning.     

Examining socially shared regulation and shared physiological arousal events with multimodal learning analytics

Socially shared regulation contributes to the success of collaborative learning. However, the assessment of socially shared regulation of learning (SSRL) faces several challenges in the effort to increase the understanding of collaborative learning and support outcomes due to the unobservability of the related cognitive and emotional processes. The recent development of trace-based assessment has enabled innovative opportunities to overcome the problem. Despite the potential of a trace-based approach to study SSRL, there remains a paucity of evidence on how trace-based evidence could be captured and utilised to assess and promote SSRL. This study aims to investigate the assessment of electrodermal activities (EDA) data to understand and support SSRL in collaborative learning, hence enhancing learning outcomes. The data collection involves secondary school students (N = 94) working collaboratively in groups through five science lessons. A multimodal data set of EDA and video data were examined to assess the relationship among shared arousals and interactions for SSRL. The results of this study inform the patterns among students' physiological activities and their SSRL interactions to provide trace-based evidence for an adaptive and maladaptive pattern of collaborative learning. Furthermore, our findings provide evidence about how trace-based data could be utilised to predict learning outcomes in collaborative learning.

Practitioner notes

What is already known about this topic

• Socially shared regulation has been recognised as an essential aspect of collaborative learning success.
• It is challenging to make the processes of learning regulation ‘visible’ to better understand and support student learning, especially in dynamic collaborative settings.
• Multimodal learning analytics are showing promise for being a powerful tool to reveal new insights into the temporal and sequential aspects of regulation in collaborative learning.

What this paper adds

• Utilising multimodal big data analytics to reveal the regulatory patterns of shared physiological arousal events (SPAEs) and regulatory activities in collaborative learning.
• Providing evidence of using multimodal data including physiological signals to indicate trigger events in socially shared regulation.
• Examining the differences of regulatory patterns between successful and less successful collaborative learning sessions.
• Demonstrating the potential use of artificial intelligence (AI) techniques to predict collaborative learning success by examining regulatory patterns.

Implications for practice and/or policy

• Our findings offer insights into how students regulate their learning during collaborative learning, which can be used to design adaptive supports that can foster students' learning regulation.
• This study could encourage researchers and practitioners to consider the methodological development incorporating advanced techniques such as AI machine learning for capturing, processing and analysing multimodal data to examine and support learning regulation.

     

CSCL中促进协作知识建构的策略

计算机支持的协作学习（CSCL）是近年来教育技术和学习科学研究的热点,协作知识建构是CSCL的主要学习方式和学习目标,如何支持和促进协作知识建构是教育研究者和实践者关注的焦点问题之一。在社会建构主义和对话学习理论基础上建立的基于对话的教学设计和基于研究与实践的协作学习过程模型可以作为一种系统的教学模式,引入到CSCL学习环境中来支持协作知识建构。网络环境下协作学习困难和问题调查,以及CSCL课程实践证明：旨在提高学生对话能力,促进学生不同类型对话产生和发展,培养学生批判性思维能力的促进协作知识建构的教学设计和实施策略是有效的,学生在协作学习中能掌握并运用这些策略来促进协作学习。实现知识建构的目标。     

基于社会网络分析(SNA)的共享调节学习评价:概念框架与解释案例

共享调节学习评价涉及协作学习的不同维度和过程,同时兼具群体感知的功能。现有的评价存在分析维度单一、数据利用不足、缺乏对互动过程的挖掘和跟踪等问题。将社会网络分析(Social Network Analysis,SNA)引入共享调节学习的评价,可以充分反映共享调节学习特有的理论观照,呈现调节过程不同阶段的特点、不同评价维度的关联性以及调节的内在机制。基于SNA的共享调节学习评价框架,在数据收集以及分析工具方面,拓展了现有的共享调节评价维度,其引入群体交流模式、群体互动紧密性、个人或群体角色、不同关系维度、多模社会关系等评价分析工具,对共享调节学习过程进行评价与跟踪,促进了群体的自我感知。以华东师范大学教育信息技术学系的一门专业选修课程为解释案例说明概念框架的应用过程,也表明了基于SNA的共享调节评价能够评估共享调节学习的协作过程,促进共享调节水平的提高,相应的评价工具能够促进协作学习活动开展,强化成员的群体感知。未来仍需要进一步深化实证研究,完善评价工具,拓展应用案例,进一步挖掘概念框架的潜在价值。     

Group characteristics and profiles of shared regulation in collaborative environments involving asynchronous communication / Características y perfiles grupales de regulación compartida en entornos colaborativos de comunicación asíncrona

The processes of socially shared regulation in small groups of students who perform collaborative tasks through forums involving asynchronous communication are explored in this article. The specific aim of the study is to identify profiles of shared regulation in groups of students who have different performance levels on the task, depending on the regulatory activities exercised by the groups and their distribution over time. For that purpose, a case study was developed; six small groups of university students collaboratively performed a complex task (for 29 days) in a virtual environment based on asynchronous discussion forums. The results revealed three different profiles: (i) a profile with stable and high regulation; (ii) a profile with partially stable and medium regulation; and (iii) a profile with unstable and low regulation. The first two profiles were observed in the groups with high performance levels on the task, while the third profile was observed in the low-performing groups. Therefore, some recommendations are suggested to support processes of shared regulation in asynchronous collaborative learning situations.     

基于本体的CSCL角色研究——CSCL中的角色及其国外相关研究综述

CSCL中的角色是对协作学习的重要支持,从理论上关注学习个体在协作学习中的角色扮演对协作学习的促进作用,从技术上研究利用本体来达到协作学习中角色在不同协作情境中的共享与重用。通过文献检索与内容分析研究法,分析国外关于基于本体的CSCL角色研究的相关文献,总结出CSCL角色研究的价值与必要性。希望为国内进行CSCL角色研究的学者提供帮助。     

Shared and personal learning spaces: Challenges for pedagogical design

The development of new tools for collaboration, such as social software, plays a crucial role in leisure time and work activities. The aim of this article is to summarize the research in the field of computer-supported collaborative learning (CSCL). This is done particularly from the perspective of the blurred line between individual (personal) and group-level (shared) learning that the use of the new tools has forced us to re-think. First, individual and group-level perspectives to learning are discussed to make sense of the major notions of how learning is understood in CSCL research. Second, based on this theoretical grounding, it will be further elaborated what this means to the pedagogical design of educational practices utilizing emerging technological landscapes. And third, two different empirical examples will be presented to illustrate the variety of emerging technological landscapes meeting the needs of future learning.     

Supporting groups’ emotion and motivation regulation during collaborative learning

This study investigates when and how students activate co- and socially shared emotion and motivation regulation in collaborative learning and whether the S-REG mobile application tool can support this regulation. In a mathematics course, 44 higher education students worked with a collaborative assignment. The S-REG tool traced groups' emotional and motivational states in different sessions, and the occurrence of co-regulation and shared regulation of motivation and emotions were coded from video-recorded collaborative work (44 h). The groups activated more co-regulation than shared regulation of emotions and motivation, but the shared-regulation episodes were longer-lasting. The groups’ emotional and motivational states were associated with the occurrence of co-regulation in the beginning of the learning sessions. The results suggest that the S-REG tool balanced collaboration by prompting the groups to regulate emotions and motivation right in the beginning of the motivationally and emotionally challenging learning sessions.     

Capturing temporal and sequential patterns of self-, co-, and socially shared regulation in the context of collaborative learning

This study examined how temporal sequences of regulated learning events, such as types and processes of regulated learning, emerge during different stages of collaborative learning. Earlier research has focused on individual learning and not on the captured temporal sequences of regulation in collaborative learning. The data were collected during a two-month math didactics course taken by teacher education students who collaborated in three member groups. Twenty-two hours of video data were collected to follow how sequences of regulated learning events, along with task execution, emerged within the six groups as their collaboration advanced. The data were analyzed using qualitative content analysis and lag sequential analysis. The results showed that the groups engaged mostly in co-regulated planning and monitoring. Temporal analysis showed that collaborative interactions focusing on task execution promoted socially shared planning, indicating that task execution provided grounding for socially shared planning and regulation to occur. The sequential analysis illustrated that metacognitive monitoring played a facilitative role in the progress of task execution.     

Human and artificial intelligence collaboration for socially shared regulation in learning

Artificial intelligence (AI) has generated a plethora of new opportunities, potential and challenges for understanding and supporting learning. In this paper, we position human and AI collaboration for socially shared regulation (SSRL) in learning. Particularly, this paper reflects on the intersection of human and AI collaboration in SSRL research, which presents an exciting prospect for advancing our understanding and support of learning regulation. Our aim is to operationalize this human-AI collaboration by introducing a novel trigger concept and a hybrid human-AI shared regulation in learning (HASRL) model. Through empirical examples that present AI affordances for SSRL research, we demonstrate how humans and AI can synergistically work together to improve learning regulation. We argue that the integration of human and AI strengths via hybrid intelligence is critical to unlocking a new era in learning sciences research. Our proposed frameworks present an opportunity for empirical evidence and innovative designs that articulate the potential for human-AI collaboration in facilitating effective SSRL in teaching and learning.

Practitioner notes

What is already known about this topic

• For collaborative learning to succeed, socially shared regulation has been acknowledged as a key factor.
• Artificial intelligence (AI) is a powerful and potentially disruptive technology that can reveal new insights to support learning.
• It is questionable whether traditional theories of how people learn are useful in the age of AI.

What this paper adds

• Introduces a trigger concept and a hybrid Human-AI Shared Regulation in Learning (HASRL) model to offer insights into how the human-AI collaboration could occur to operationalize SSRL research.
• Demonstrates the potential use of AI to advance research and practice on socially shared regulation of learning.
• Provides clear suggestions for future human-AI collaboration in learning and teaching aiming at enhancing human learning and regulatory skills.

Implications for practice and/or policy

• Educational technology developers could utilize our proposed framework to better align technological and theoretical aspects for their design of adaptive support that can facilitate students' socially shared regulation of learning.
• Researchers and practitioners could benefit from methodological development incorporating human-AI collaboration for capturing, processing and analysing multimodal data to examine and support learning regulation.

     

Seven Affordances of Computer-Supported Collaborative Learning: How to Support Collaborative Learning? How Can Technologies Help?

This article proposes 7 core affordances of technology for collaborative learning based on theories of collaborative learning and CSCL (Computer-Supported Collaborative Learning) practices. Technology affords learner opportunities to (1) engage in a joint task, (2) communicate, (3) share resources, (4) engage in productive collaborative learning processes, (5) engage in co-construction, (6) monitor and regulate collaborative learning, and (7) find and build groups and communities. We elaborate our framework using in-depth explorations of how technologies are actually used to support collaborative learning in CSCL research and identify representative design strategies and technology examples. While technology can play an important role in addressing the demands of collaborative learning, it needs to be considered in conjunction with pedagogical strategies and other social and cultural supports for collaborative learning. The supports also need to remain at an appropriate level so as not to interfere with long-term learning goals.     

Productive group engagement in cognitive activity and metacognitive regulation during collaborative learning: can it explain differences in students’ conceptual understanding?

This paper addresses the nature and significance of productive engagement in cognitive activity and metacognitive regulation in collaborative learning tasks that involve complex scientific knowledge. A situative framework, combining the constructs of social regulation and content processing, provided the theoretical basis for the development of a comprehensive coding scheme for interactive data analysis. An empirical study was conducted with two groups of university students working on two science-learning tasks. It examined the function of metacognitive regulation to control the flow of cognitive activity, and the extent to which group differences in cognitive and metacognitive regulation processes during collaborative learning could explain differences in the groups’ learning outcomes. The findings provide validation of the framework and its derived coding scheme. An example of a way in which a group engages in socially shared metacognitive regulation is presented to demonstrate how the coding scheme was applied to the data. Theoretical and empirical implications of the findings are discussed.     

CSCL中的团队反思及其支架开发

研究基于共享调节的理论视角,从过程模型构建、支架开发、案例实践等方面对CSCL中的团队反思及其支架开发进行了系统的探索。首先,剖析了共享调节中团队反思的活动过程,包括共享调节学习中团队反思与自我反思的关系,以及团体反思过程的具体构成;其次,依据团队反思的行为过程,从回顾、描述(或展示)、评价、分析和计划五个维度设计了个体和团队的过程性与总结性反思支架;最后,应用研究设计和开发的团队反思支架,针对职前教师的集体备课任务进行基于共享调节的团队反思的案例实践,案例研究表明,支架为学习者团队反思活动提供有效支持,有助于CSCL团队反思活动的开展。     

国际视野中的CSCL研究与发展的十个主题——访CSCL研究国际著名专家皮埃尔·狄隆伯格教授

国际学习科学协会(ISLS)前主席,皮埃尔.狄隆伯格(Pierre Dillenbourg)教授是瑞士洛桑联邦理工大学(EPFL)培训及其技术研究与支持中心(CRAFT)的主任,也是《计算机支持的协作学习丛书》(CSCL Book Series)的主编。本次访谈为中国读者提供了一个关于计算机支持的协作学习(CSCL)的研究与发展概要。狄隆伯格教授认为,CSCL的贡献不仅在于为专业培训领域提供了增进知识生产的学习技术,更在于其所包含的一系列的概念、思想和取向等对整个教育系统的渗透。协作学习,无论有没有计算机,都不是一个可以自动导致预期学习结果的处方。CSCL研究者已经研究了导致小组(或团队)生产积极学习结果的必要互动类型,并将技术运用于设计、研究和增进必要的互动。应当从一个"整合的学习"的视角认识CSCL,可以借助对情节的设计和不同工具的支持,将CSCL活动嵌入到正式或非正式学习场景更为综合的活动系列中。与此相应,CSCL研究者提出了十个方面的研究主题:即社会互动与个人化、媒体有效性、共享知识的建构、模仿倾向、中介作用、脚本、互动分析、表征、计算装置和虚拟共同体。     

Monitoring collaborative activities in computer supported collaborative learning

Monitoring the learning process in computer supported collaborative learning (CSCL) environments is a key element for supporting the efficacy of tutor actions. This article proposes an approach for analysing learning processes in a CSCL environment to support tutors in their monitoring tasks. The approach entails tracking the interactions within the communication platform to identify cues of the participative, social, cognitive, and teaching dimensions of the learning process. Both quantitative and qualitative indicators are employed to achieve a complete and thorough picture of the learning dynamics. A set of methodological and technological tools based on this approach has been tried out in the context of the online component of a blended course in educational technology addressing trainee teachers. The results of the study support the applicability of the proposed approach to content domains where discussion and reflective practice are the most effective learning strategy.     

Applying activity theory to computer-supported collaborative learning and work-based activities in corporate settings

Business needs in many corporations call for learning outcomes that involve problem solutions, and creating and sharing new knowledge within worksplace situation that may involve collaboration among members of a team. We argue that work-based activities (WBA) and computer-supported collaborative learning (CSCL) are appropriate components for courses in such learning situations. Via this approach, collaborative work situations become the core of a course. We further describe how activity theory can provide a framework for the design of courses that involve WBA and CSCL as part of a workplace-oriented activity system for learning. The use of this design approach for courses offered by the Learning and Leadership Development organization of Shell International Exploration and Production is described and an example is elaborated. Finally, we identify four main issues and challenges that arose during the use of the design approach.     

Learning with collaborative inquiry: a science learning environment for secondary students

When inquiry-based learning is designed for a collaborative context, the interactions that arise in the learning environment can become fairly complex. While the learning effectiveness of such learning environments has been reported in the literature, there have been fewer studies on the students’ learning processes. To address this, the article presents a study of science learning in a computer-supported learning environment called Collaborative Science Inquiry (CSI), which integrates guided inquiry principles for activity design, employs modelling and visualisation tools for promoting conceptual understanding and incorporates key computer-supported collaborative learning (CSCL) elements for enabling students’ collaboration. With the aim of understanding the process of students’ conceptual changes supported by the CSI learning environment as used in a secondary school, data on students’ test achievements, responses to learning tasks and peer discussions in collaboration were collected, analysed and discussed. The results of the qualitative and quantitative data analysis indicated that guided inquiry coupled with CSCL elements facilitated by the CSI system can engage students in inquiry activities and promote their conceptual understanding in a progressive way.