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Dialogues across time and space in a video-based collaborative learning environment Intern. J. Comput.-Support. Collab. Learn. (IF 5.611) Pub Date : 2024-04-16 Charlotte Beal, Rolf Steier
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Effects of group awareness support in CSCL on students’ learning performance: A three-level meta-analysis Intern. J. Comput.-Support. Collab. Learn. (IF 5.611) Pub Date : 2024-02-26 Dengkang Chen, Yi Zhang, Heng Luo, Zhifang Zhu, Jingsi Ma, Yuru Lin
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Taking a stance in the process of learning: Developing perspectival understandings through knowledge co-construction during synchronous computer-mediated classroom discussion Intern. J. Comput.-Support. Collab. Learn. (IF 5.611) Pub Date : 2024-02-23 Hannah Park, Diane L. Schallert, Kyle M. Williams, Rachel E. Gaines, Jeonghyun Lee, Eunjeong Choi
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Learning within fiber-crafted algorithms: Posthumanist perspectives for capturing human-material collaboration Intern. J. Comput.-Support. Collab. Learn. (IF 5.611) Pub Date : 2024-02-21 Anna Keune
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Exploring students’ immersive VR experiences as resources for collaborative meaning making and learning Intern. J. Comput.-Support. Collab. Learn. (IF 5.611) Pub Date : 2024-02-15 Kenneth Silseth, Rolf Steier, Hans Christian Arnseth
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Understanding the effect of differences in prior knowledge on middle school students’ collaborative interactions and learning Intern. J. Comput.-Support. Collab. Learn. (IF 5.611) Pub Date : 2023-12-29
Abstract We investigated how the level of variance in students’ prior knowledge may have influenced their collaborative interactions and science learning in small groups. We examined learning outcomes from 102 groups from seven science teachers’ classes and discourse from two contrasting groups: Homogeneous versus heterogeneous. We examined individual and group outcomes using hierarchical linear modeling
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Studying teacher withitness in the wild: comparing a mirroring and an alerting & guiding dashboard for collaborative learning Intern. J. Comput.-Support. Collab. Learn. (IF 5.611) Pub Date : 2023-12-28 Reet Kasepalu, Pankaj Chejara, Luis P. Prieto, Tobias Ley
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Can CPS better prepare 8th graders for problem-solving in electromagnetism and bridging the gap between high- and low-achievers than IPS? Intern. J. Comput.-Support. Collab. Learn. (IF 5.611) Pub Date : 2023-12-27 Jiun-Wei Guo, Hsiao-Ching She, Meng-Jun Chen, Pei-Yi Tsai
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The role of first-language heterogeneity in the acquisition of online interaction self-efficacy in CSCL Intern. J. Comput.-Support. Collab. Learn. (IF 5.611) Pub Date : 2023-11-11 Natalia Reich-Stiebert, Jan-Bennet Voltmer, Jennifer Raimann, Stefan Stürmer
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Co-constructing knowledge with generative AI tools: Reflections from a CSCL perspective Intern. J. Comput.-Support. Collab. Learn. (IF 5.611) Pub Date : 2023-10-20 Ulrike Cress, Joachim Kimmerle
Generative Artificial Intelligence (AI) tools, such as ChatGPT, have received great attention from researchers, the media, and the public. They are gladly and frequently used for text production by many people. These tools have undeniable strengths but also weaknesses that must be addressed. In this squib we ask to what extent these tools can be employed by users for individual learning as well as
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Contesting sociocomputational norms: Computer programming instructors and students’ stancetaking around refactoring Intern. J. Comput.-Support. Collab. Learn. (IF 5.611) Pub Date : 2023-09-06 Morgan M. Fong, David DeLiema, Virginia J. Flood, Oia Walker-van Aalst
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Identifying collaborative problem-solver profiles based on collaborative processing time, actions and skills on a computer-based task Intern. J. Comput.-Support. Collab. Learn. (IF 5.611) Pub Date : 2023-08-30 Yue Ma, Huilin Zhang, Li Ni, Da Zhou
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The mechanism and effect of class-wide peer feedback on conceptual knowledge improvement: Does different feedback type matter? Intern. J. Comput.-Support. Collab. Learn. (IF 5.611) Pub Date : 2023-08-24 Jesmine S. H. Tan, Wenli Chen, Junzhu Su, Guo Su
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Exploring the impact of chat-based collaborative activities and SRL-focused interventions on students’ self-regulation profiles, participation in collaborative activities, retention, and learning in MOOCs Intern. J. Comput.-Support. Collab. Learn. (IF 5.611) Pub Date : 2023-08-23 Georgios Psathas, Stergios Tegos, Stavros N. Demetriadis, Thrasyvoulos Tsiatsos
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Does matching peers at finer-grained levels of prior performance enhance gains in task performance from peer review? Intern. J. Comput.-Support. Collab. Learn. (IF 5.611) Pub Date : 2023-08-16 Zheng Zong, Christian D. Schunn
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Promoting knowledge building through meta-discourse and epistemic discourse understanding Intern. J. Comput.-Support. Collab. Learn. (IF 5.611) Pub Date : 2023-08-10 Yuyao Tong, Carol K. K. Chan
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Facilitated model-based reasoning in immersive virtual reality: Meaning-making and embodied interactions with dynamic processes Intern. J. Comput.-Support. Collab. Learn. (IF 5.611) Pub Date : 2023-08-09 Michelle Lui, Kit-Ying Angela Chong, Martha Mullally, Rhonda McEwen
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Understanding young children’s science learning through embodied communication within an MR environment Intern. J. Comput.-Support. Collab. Learn. (IF 5.611) Pub Date : 2023-07-31 Xintian Tu, Joshua Danish, Megan Humburg, Mengxi Zhou, Nitasha Mathayas, Noel Enyedy, Tessaly Jen
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Gesture-mediated collaboration with augmented reality headsets in a problem-based astronomy task Intern. J. Comput.-Support. Collab. Learn. (IF 5.611) Pub Date : 2023-07-29 James Planey, Robin Jephthah Rajarathinam, Emma Mercier, Robb Lindgren
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Mobile augmented reality supporting families’ immersive collaborative learning: Learning-on-the-move for place-based geoscience sense-making Intern. J. Comput.-Support. Collab. Learn. (IF 5.611) Pub Date : 2023-07-26 Heather Toomey Zimmerman, Susan M. Land, Lillyanna Faimon, Yu-Chen Chiu
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Coordinating modalities of mathematical collaboration in shared VR environments Intern. J. Comput.-Support. Collab. Learn. (IF 5.611) Pub Date : 2023-06-27 Wen Huang, Candace Walkington, Mitchell J. Nathan
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Common “place” observations about embodiment and CSCL Intern. J. Comput.-Support. Collab. Learn. (IF 5.611) Pub Date : 2023-06-23 Victor R. Lee
The focus of this commentary is on the role of “place” in designed embodied computer-supported collaborative learning experiences. While earlier embodied learning technology work centered individual experiences, the emphasis in this collection of articles is on embodiment as social and multi-person. I observe that a notion of shared place emerges as a key aspect, where multiple bodies collaborate and
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Correction: An artificial intelligence-driven learning analytics method to examine the collaborative problem-solving process from the complex adaptive systems perspective Intern. J. Comput.-Support. Collab. Learn. (IF 5.611) Pub Date : 2023-04-10 Fan Ouyang, Weiqi Xu, Mutlu Cukurova
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Fostering regulatory processes using computational scaffolding Intern. J. Comput.-Support. Collab. Learn. (IF 5.611) Pub Date : 2023-03-27 Leonardo Silva, António Mendes, Anabela Gomes, Gabriel Fortes
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An artificial intelligence-driven learning analytics method to examine the collaborative problem-solving process from the complex adaptive systems perspective Intern. J. Comput.-Support. Collab. Learn. (IF 5.611) Pub Date : 2023-03-13 Fan Ouyang, Weiqi Xu, Mutlu Cukurova
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The temporal dynamics of online problem-based learning: Why and when sequence matters Intern. J. Comput.-Support. Collab. Learn. (IF 5.611) Pub Date : 2023-03-10 Mohammed Saqr, Sonsoles López-Pernas
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An automated group learning engagement analysis and feedback approach to promoting collaborative knowledge building, group performance, and socially shared regulation in CSCL Intern. J. Comput.-Support. Collab. Learn. (IF 5.611) Pub Date : 2023-03-04 Lanqin Zheng, Miaolang Long, Jiayu Niu, Lu Zhong
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Visions of the good in computer-supported collaborative learning: unpacking the ethical dimensions of design-based research Intern. J. Comput.-Support. Collab. Learn. (IF 5.611) Pub Date : 2023-03-04 Etan Cohen, Dani Ben-Zvi, Yotam Hod
In this article we discuss some of the ethical dimensions of design-based research, which we believe should feature more prominently in CSCL scholarship. We begin by sketching out why it is important for CSCL researchers to articulate their visions of the good and how this can be accomplished in a systematic way. We then outline how ethical discourses can take shape at the various stages of design-based
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Mediating and perspective-taking manipulatives: Fostering dynamic perspective-taking by mediating dialogic thinking and bolstering empathy in role-play and reflection for microteaching Intern. J. Comput.-Support. Collab. Learn. (IF 5.611) Pub Date : 2022-12-24 Toshio Mochizuki, Hiroshi Sasaki, Takehiro Wakimoto, Yoshihiko Kubota, Brendan Eagan, Ryoya Hirayama, Yuta Yamaguchi, Natsumi Yuki, Hideo Funaoi, Hideyuki Suzuki, Hiroshi Kato
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The impact of scripts on blended and online socially shared regulation of learning: A role-playing game theory perspective Intern. J. Comput.-Support. Collab. Learn. (IF 5.611) Pub Date : 2022-12-12 Clyde A. Warden, Chi-Cheng Chang, James O. Stanworth, D’Arcy Caskey, Judy F. Chen
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Emotion expression and recognition in written digital discussions on Civic Issues Intern. J. Comput.-Support. Collab. Learn. (IF 5.611) Pub Date : 2022-11-14 Benzi Slakmon, Omer Keynan, Orly Shapira
This study examines emotion regulation strategies in written digital discussions revolving around controversial issues. Twenty-five undergraduate students, placed in five study groups, took part in written digital discussions. Two groups were chosen to participate in the study. Participants were interviewed and were asked to read the transcript of the digital conversation they took part in, while referring
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Implementing learning analytics in wiki-supported collaborative learning in secondary education: A framework-motivated empirical study Intern. J. Comput.-Support. Collab. Learn. (IF 5.611) Pub Date : 2022-09-07 Xiao Hu, Jeremy T. D. Ng, Samuel K. W. Chu
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iTalk–iSee: A participatory visual learning analytical tool for productive peer talk Intern. J. Comput.-Support. Collab. Learn. (IF 5.611) Pub Date : 2022-08-31 Liru Hu, Jiajun Wu, Gaowei Chen
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Patterns of action transitions in online collaborative problem solving: A network analysis approach Intern. J. Comput.-Support. Collab. Learn. (IF 5.611) Pub Date : 2022-07-25 Shupin Li, Johanna Pöysä-Tarhonen, Päivi Häkkinen
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Cross-community knowledge building with idea thread mapper Intern. J. Comput.-Support. Collab. Learn. (IF 5.611) Pub Date : 2022-06-28 Guangji Yuan, Jianwei Zhang, Mei-Hwa Chen
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Collaborative analytics-supported reflective Assessment for Scaffolding Pre-service Teachers’ collaborative Inquiry and Knowledge Building Intern. J. Comput.-Support. Collab. Learn. (IF 5.611) Pub Date : 2022-06-10 Yuqin Yang, Gaoxia Zhu, Daner Sun, Carol K. K. Chan
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A classification of Challenges encountered in Complex Teamwork Settings Intern. J. Comput.-Support. Collab. Learn. (IF 5.611) Pub Date : 2022-06-04 Maedeh A. Kazemitabar, Susanne P. Lajoie, Tianshu Li
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‘Supporting socially shared regulation during collaborative task-oriented reading’ Intern. J. Comput.-Support. Collab. Learn. (IF 5.611) Pub Date : 2022-05-13 Jolique Kielstra, Inge Molenaar, Roel van Steensel, Ludo Verhoeven
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Supporting children’s place-based observations and explanations using collaboration scripts while learning-on-the-move outdoors Intern. J. Comput.-Support. Collab. Learn. (IF 5.611) Pub Date : 2022-04-06 Heather Toomey Zimmerman, Susan M. Land
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CSsCL: the performance of collaborative learning Intern. J. Comput.-Support. Collab. Learn. (IF 5.611) Pub Date : 2022-03-25 Charles Crook
This article discusses the integration of three concepts central to the enterprise of computer-supported collaborative learning: namely, collaboration scripts, self-regulation, and group awareness. It does so through consideration of five reports in this Special Issue that address the integration challenge. Various themes are extracted and proposed as important to the field. These include the layered
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Adaptable scaffolding of mathematical argumentation skills: The role of self-regulation when scaffolded with CSCL scripts and heuristic worked examples Intern. J. Comput.-Support. Collab. Learn. (IF 5.611) Pub Date : 2022-03-21 Freydis Vogel, Ingo Kollar, Frank Fischer, Kristina Reiss, Stefan Ufer
Collaboration scripts and heuristic worked examples have been described as powerful scaffolds to support skill acquisition in CSCL. While CSCL scripts particularly facilitate argumentative discourse within groups, heuristic worked examples provide heuristics and worked out pathways to solve domain-specific tasks. Yet, both scripts and heuristic worked examples are often designed in a one-size-fits-all
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Integrating a collaboration script and group awareness to support group regulation and emotions towards collaborative problem solving Intern. J. Comput.-Support. Collab. Learn. (IF 5.611) Pub Date : 2022-03-12 Matias Rojas, Miguel Nussbaum, Orlando Guerrero, Pablo Chiuminatto, Samuel Greiff, Rodrigo Del Rio, Danilo Alvares
The research landscape displays increasing awareness of the important role of self-regulation and emotions in the process of acquiring Collaborative Problem-Solving skills (CPS), which are considered essential in almost all areas of life. However, there is still a dearth of research on developing CPS skills among elementary-school students. Our research therefore looks at how elementary school students'
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Group awareness and regulation in computer-supported collaborative learning Intern. J. Comput.-Support. Collab. Learn. (IF 5.611) Pub Date : 2022-03-09 Lenka Schnaubert, Daniel Bodemer
Group awareness is of critical relevance for collaborative learning and interaction and is thus often referred to in CSCL research. However, the concept is only vaguely defined as some kind of understanding or perception of characteristics of learning partners or the collaborating group. Most CSCL research activities concerned with group awareness aim at modifying learners' awareness using so-called
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Integrating collaboration scripts, group awareness, and self-regulation in computer-supported collaborative learning Intern. J. Comput.-Support. Collab. Learn. (IF 5.611) Pub Date : 2022-03-01 Lenka Schnaubert,Freydis Vogel
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Many are the ways to learn identifying multi-modal behavioral profiles of collaborative learning in constructivist activities Intern. J. Comput.-Support. Collab. Learn. (IF 5.611) Pub Date : 2022-01-21 Nasir, Jauwairia, Kothiyal, Aditi, Bruno, Barbara, Dillenbourg, Pierre
Understanding the way learners engage with learning technologies, and its relation with their learning, is crucial for motivating design of effective learning interventions. Assessing the learners’ state of engagement, however, is non-trivial. Research suggests that performance is not always a good indicator of learning, especially with open-ended constructivist activities. In this paper, we describe
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The trade-off between individuals and groups: role interactions under different technology affordance conditions Intern. J. Comput.-Support. Collab. Learn. (IF 5.611) Pub Date : 2022-01-10 Wang, Cixiao, Li, Shuling
Virtual manipulatives running on tablets have been demonstrated to improve students’ conceptual understanding in previous studies. However, the differential effects on group interaction during face-to-face collaborative inquiry learning from the support of alternative technology affordances has received little attention. Technology affordances in collaborative learning refer to the types of support
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Self-efficacy and behavior patterns of learners using a real-time collaboration system developed for group programming Intern. J. Comput.-Support. Collab. Learn. (IF 5.611) Pub Date : 2022-01-01 Ting-Chia Hsu, Hal Abelson, Evan Patton, Shih-Chu Chen, Hsuan-Ning Chang
In order to promote the practice of co-creation, a real-time collaboration (RTC) version of the popular block-based programming (BBP) learning environment, MIT App Inventor (MAI), was proposed and implemented. RTC overcomes challenges related to non-collocated group work, thus lowering barriers to cross-region and multi-user collaborative software development. An empirical study probed into the differential
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Educational dialogues and computer supported collaborative learning: critical analysis and research perspectives Intern. J. Comput.-Support. Collab. Learn. (IF 5.611) Pub Date : 2021-12-03 Michael J. Baker, Baruch B. Schwarz, Sten R. Ludvigsen
We present a critical perspective on the current state of research on educational dialogues, within and without Computer-Supported Collaborative Learning environments, in order to propose research perspectives in the intersection of these two domains. Our main proposal is that in order to integrate different types of human or machine analyzed data over different timescales, it is necessary to do so
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Modelling diffusion in computer-supported collaborative learning: a large scale learning analytics study Intern. J. Comput.-Support. Collab. Learn. (IF 5.611) Pub Date : 2021-12-02 Mohammed Saqr, Sonsoles López-Pernas
This study empirically investigates diffusion-based centralities as depictions of student role-based behavior in information exchange, uptake and argumentation, and as consistent indicators of student success in computer-supported collaborative learning. The analysis is based on a large dataset of 69 courses (n = 3,277 students) with 97,173 total interactions (of which 8,818 were manually coded). We
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A theory-driven reflection on context-aware support for collaborative discussions in light of analytics, affordances, and platforms Intern. J. Comput.-Support. Collab. Learn. (IF 5.611) Pub Date : 2021-12-01 Carolyn Rosé,Sanna Järvelä
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The impact of a gamified mobile question-asking app on museum visitor group interactions: an ICAP framing Intern. J. Comput.-Support. Collab. Learn. (IF 5.611) Pub Date : 2021-09-09 Ha, Jesse, Pérez Cortés, Luis E., Su, Man, Nelson, Brian C., Bowman, Catherine, Bowman, Judd D.
Mobile devices and apps have become a standard for the museum experience. Many studies have begun to explore the impact mobile apps may have on user experience and informal learning. However, there has been relatively little research on how visitor groups interact collaboratively while using these devices in computer-supported collaborative learning (CSCL) environments. In this paper, we explore the
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Socio-technical configurations for productive talk Intern. J. Comput.-Support. Collab. Learn. (IF 5.611) Pub Date : 2021-09-01 Peter Reimann
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Deconstructing orchestration load: comparing teacher support through mirroring and guiding Intern. J. Comput.-Support. Collab. Learn. (IF 5.611) Pub Date : 2021-08-20 Amarasinghe, Ishari, Hernández-Leo, Davinia, Ulrich Hoppe, H.
Under the notion of “CSCL scripts”, different pedagogical models for structuring and supporting collaboration in the classroom have been proposed. We report on a practical experience with scripts based on the Pyramid collaborative learning flow pattern supported by a specific classroom tool and a teacher-facing dashboard that implements mirroring and guiding support. The input data of our analysis
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Prompting collaborative and exploratory discourse: An epistemic network analysis study Intern. J. Comput.-Support. Collab. Learn. (IF 5.611) Pub Date : 2021-08-07 Vandenberg, Jessica, Zakaria, Zarifa, Tsan, Jennifer, Iwanski, Anna, Lynch, Collin, Boyer, Kristy Elizabeth, Wiebe, Eric
By encouraging elementary students to work collaboratively, they can gain essential skills such as perspective taking, conflict negotiation, and asking for and receiving assistance. Epistemic Network Analysis (ENA) is an analytic technique that provides an alternative to more typical approaches to analyzing and synthesizing coded dialogue. This study used an easy-to-implement prompting intervention
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Net.Create: Network Visualization to Support Collaborative Historical Knowledge Building Intern. J. Comput.-Support. Collab. Learn. (IF 5.611) Pub Date : 2021-07-09 Kalani Craig, Joshua Danish, Megan Humburg, Cindy Hmelo-Silver, Maksymilian Szostalo, Ann McCranie
Students across disciplines struggle with sensemaking when they are faced with the need to understand and analyze massive amounts of information. This is particularly salient in the disciplines of both history and data science. Our approach to helping students build expertise with complex information leverages activity theory to think about the design of a classroom activity system integrated with
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Guidance in computer-supported collaborative inquiry learning: Capturing aspects of affect and teacher support in science classrooms Intern. J. Comput.-Support. Collab. Learn. (IF 5.611) Pub Date : 2021-06-15 Tarja Pietarinen, Tuire Palonen, Marja Vauras
Technology-enhanced collaborative inquiry learning has gained a firm position in curricula across disciplines and educational settings and has become particularly pervasive in science classrooms. However, understanding of the teacher’s role in this context is limited. This study addresses the real-time shifts in focus and distribution of teachers’ guidance and support of different student groups during
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Initiating scientific collaborations across career levels and disciplines – a network analysis on behavioral data Intern. J. Comput.-Support. Collab. Learn. (IF 5.611) Pub Date : 2021-06-15 Julia Eberle, Karsten Stegmann, Alain Barrat, Frank Fischer, Kristine Lund
Collaborations are essential in research, especially in answering increasingly complex questions that require integrating knowledge from different disciplines and that engage multiple stakeholders. Fostering such collaboration between newcomers and established researchers helps keep scientific communities alive while opening the way to innovation. But this is a challenge for scientific communities
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Improving learning and writing outcomes: Influence of cognitive and behavioral group awareness tools in wikis Intern. J. Comput.-Support. Collab. Learn. (IF 5.611) Pub Date : 2021-06-01 Lisa Ollesch,Sven Heimbuch,Daniel Bodemer
AbstractGroup awareness (GA) tools can facilitate learning processes and outcomes by visualizing different social attributes, such as cognitive and behavioral information about group members. To assist learning and writing in social media, combining various types of awareness information may foster learning processes due to challenges, which are difficult to address by one type of GA information alone
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Forms of collaboration matters: CSCL across the contexts Intern. J. Comput.-Support. Collab. Learn. (IF 5.611) Pub Date : 2021-06-01 Sanna Järvelä,Carolyn Rosé
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Social sensitivity: a manifesto for CSCL research Intern. J. Comput.-Support. Collab. Learn. (IF 5.611) Pub Date : 2021-05-25 Jaana Isohätälä, Piia Näykki, Sanna Järvelä, Michael J. Baker, Kristine Lund
Technologies for computer-supported collaborative learning (CSCL) are playing an increasingly prominent role in educational contexts, especially as teachers and students strive to deal with pandemic-related constraints. However, the technologies being used for collaboration on a daily basis are not sufficiently equipped to promote collaborative learning as both a cognitive and a socio-emotional process