Example of International Journal of Computer-Supported Collaborative Learning format
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Example of International Journal of Computer-Supported Collaborative Learning format Example of International Journal of Computer-Supported Collaborative Learning format Example of International Journal of Computer-Supported Collaborative Learning format Example of International Journal of Computer-Supported Collaborative Learning format Example of International Journal of Computer-Supported Collaborative Learning format Example of International Journal of Computer-Supported Collaborative Learning format Example of International Journal of Computer-Supported Collaborative Learning format Example of International Journal of Computer-Supported Collaborative Learning format Example of International Journal of Computer-Supported Collaborative Learning format Example of International Journal of Computer-Supported Collaborative Learning format Example of International Journal of Computer-Supported Collaborative Learning format Example of International Journal of Computer-Supported Collaborative Learning format Example of International Journal of Computer-Supported Collaborative Learning format Example of International Journal of Computer-Supported Collaborative Learning format Example of International Journal of Computer-Supported Collaborative Learning format Example of International Journal of Computer-Supported Collaborative Learning format Example of International Journal of Computer-Supported Collaborative Learning format Example of International Journal of Computer-Supported Collaborative Learning format
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Example of International Journal of Computer-Supported Collaborative Learning format Example of International Journal of Computer-Supported Collaborative Learning format Example of International Journal of Computer-Supported Collaborative Learning format Example of International Journal of Computer-Supported Collaborative Learning format Example of International Journal of Computer-Supported Collaborative Learning format Example of International Journal of Computer-Supported Collaborative Learning format Example of International Journal of Computer-Supported Collaborative Learning format Example of International Journal of Computer-Supported Collaborative Learning format Example of International Journal of Computer-Supported Collaborative Learning format Example of International Journal of Computer-Supported Collaborative Learning format Example of International Journal of Computer-Supported Collaborative Learning format Example of International Journal of Computer-Supported Collaborative Learning format Example of International Journal of Computer-Supported Collaborative Learning format Example of International Journal of Computer-Supported Collaborative Learning format Example of International Journal of Computer-Supported Collaborative Learning format Example of International Journal of Computer-Supported Collaborative Learning format Example of International Journal of Computer-Supported Collaborative Learning format Example of International Journal of Computer-Supported Collaborative Learning format
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International Journal of Computer-Supported Collaborative Learning — Template for authors

Publisher: Springer
Categories Rank Trend in last 3 yrs
Education #14 of 1319 up up by 16 ranks
Human-Computer Interaction #12 of 120 up up by 5 ranks
journal-quality-icon Journal quality:
High
calendar-icon Last 4 years overview: 67 Published Papers | 607 Citations
indexed-in-icon Indexed in: Scopus
last-updated-icon Last updated: 23/06/2020
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Journal Performance & Insights

Impact Factor

CiteRatio

Determines the importance of a journal by taking a measure of frequency with which the average article in a journal has been cited in a particular year.

A measure of average citations received per peer-reviewed paper published in the journal.

4.028

83% from 2018

Impact factor for International Journal of Computer-Supported Collaborative Learning from 2016 - 2019
Year Value
2019 4.028
2018 2.206
2017 3.273
2016 3.469
graph view Graph view
table view Table view

9.1

15% from 2019

CiteRatio for International Journal of Computer-Supported Collaborative Learning from 2016 - 2020
Year Value
2020 9.1
2019 7.9
2018 6.2
2017 5.7
2016 5.5
graph view Graph view
table view Table view

insights Insights

  • Impact factor of this journal has increased by 83% in last year.
  • This journal’s impact factor is in the top 10 percentile category.

insights Insights

  • CiteRatio of this journal has increased by 15% in last years.
  • This journal’s CiteRatio is in the top 10 percentile category.

SCImago Journal Rank (SJR)

Source Normalized Impact per Paper (SNIP)

Measures weighted citations received by the journal. Citation weighting depends on the categories and prestige of the citing journal.

Measures actual citations received relative to citations expected for the journal's category.

2.394

14% from 2019

SJR for International Journal of Computer-Supported Collaborative Learning from 2016 - 2020
Year Value
2020 2.394
2019 2.772
2018 1.853
2017 1.588
2016 1.568
graph view Graph view
table view Table view

2.25

26% from 2019

SNIP for International Journal of Computer-Supported Collaborative Learning from 2016 - 2020
Year Value
2020 2.25
2019 3.06
2018 1.891
2017 1.888
2016 2.035
graph view Graph view
table view Table view

insights Insights

  • SJR of this journal has decreased by 14% in last years.
  • This journal’s SJR is in the top 10 percentile category.

insights Insights

  • SNIP of this journal has decreased by 26% in last years.
  • This journal’s SNIP is in the top 10 percentile category.

International Journal of Computer-Supported Collaborative Learning

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Springer

International Journal of Computer-Supported Collaborative Learning

IJCSCL is a refereed, international, multidisciplinary journal dedicated to research on and practice in all aspects of learning and education with the aid of computers and computer networks in synchronous and asynchronous distributed and non-distributed groups. IJCSCL addresse...... Read More

Education

Human-Computer Interaction

Social Sciences

i
Last updated on
23 Jun 2020
i
ISSN
1556-1607
i
Impact Factor
High - 2.256
i
Open Access
No
i
Sherpa RoMEO Archiving Policy
Green faq
i
Plagiarism Check
Available via Turnitin
i
Endnote Style
Download Available
i
Bibliography Name
SPBASIC
i
Citation Type
Author Year
(Blonder et al, 1982)
i
Bibliography Example
Beenakker CWJ (2006) Specular andreev reflection in graphene. Phys Rev Lett 97(6):067,007, URL 10.1103/PhysRevLett.97.067007

Top papers written in this journal

open accessOpen access Journal Article DOI: 10.1007/S11412-018-9277-Y
From Cognitive Load Theory to Collaborative Cognitive Load Theory
Paul A. Kirschner1, Paul A. Kirschner2, John Sweller3, Femke Kirschner4, R Jimmy Zambrano

Abstract:

Cognitive load theory has traditionally been associated with individual learning. Based on evolutionary educational psychology and our knowledge of human cognition, particularly the relations between working memory and long-term memory, the theory has been used to generate a variety of instructional effects. Though these inst... Cognitive load theory has traditionally been associated with individual learning. Based on evolutionary educational psychology and our knowledge of human cognition, particularly the relations between working memory and long-term memory, the theory has been used to generate a variety of instructional effects. Though these instructional effects also influence the efficiency and effectiveness of collaborative learning, be it computer supported or face-to-face, they are often not considered either when designing collaborative learning situations/environments or researching collaborative learning. One reason for this omission is that cognitive load theory has only sporadically concerned itself with certain particulars of collaborative learning such as the concept of a collective working memory when collaborating along with issues associated with transactive activities and their concomitant costs which are inherent to collaboration. We illustrate how and why cognitive load theory, by adding these concepts, can throw light on collaborative learning and generate principles specific to the design and study of collaborative learning. read more read less

Topics:

Collaborative learning (71%)71% related to the paper, Computer-supported collaborative learning (68%)68% related to the paper, Cognitive load (65%)65% related to the paper, Educational technology (62%)62% related to the paper, Transactive memory (59%)59% related to the paper
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213 Citations
Journal Article DOI: 10.1007/S11412-017-9267-5
Visions of CSCL: eight provocations for the future of the field
Alyssa Friend Wise1, Baruch B. Schwarz2

Abstract:

The field of CSCL is at a critical moment in its development. Internally we face issues of fragmentation and questions about what progress is being made. Externally the rise of social media and a variety of research communities that study the interactions within it raise questions about our unique identity and larger impact o... The field of CSCL is at a critical moment in its development. Internally we face issues of fragmentation and questions about what progress is being made. Externally the rise of social media and a variety of research communities that study the interactions within it raise questions about our unique identity and larger impact on the world. To illuminate the complex issues involved and the multiple perspectives that exist on them, we conducted an iterative and generative consultation with members of the CSCL community through individual interviews and public interactive presentations. The result is a series of eight provocations for the field, each presented as a dialogue between the Provocateur/Provocatrice (who seeks to shake up the status quo) and the Conciliator (who seeks to build on the achievements of our current traditions). The provocations address the debated need for six things: one conceptual framework to unite our diverse tools and theories (#1), prioritization of learner agency over collaborative scripting (#2), scrupulous scrutiny of when “collaboration” and “community” are said to exist (#3), the pursuit of computational approaches to understand collaborative learning (#5), learning analytics and adaptive support to be a top priority in the field (#6), and the expansion of our focus to seriously address social media and large-scale learning environments (#7). In addition, the provocations highlight two areas in which perhaps we should desist: the attempt to reconcile analytical and interpretative approaches to understanding collaboration (#4), and the goal of achieving tangible change in the education system (#8). There are no resolutions offered in this paper; the interchanges presented are designed to lay out the complex constellation of issues involved and can be considered a dialogue that we are still in the process of having with ourselves as individuals and together as a community. We stress the urgency and importance for the field of CSCL to take up these questions and tensions, and critically, to work towards decisions and resultant actions. Our future as a scientific community — our very existence and identity, depends on it. read more read less

Topics:

Collaborative learning (54%)54% related to the paper, Computer-supported collaborative learning (53%)53% related to the paper, Mass collaboration (51%)51% related to the paper, Agency (sociology) (51%)51% related to the paper, Learning analytics (51%)51% related to the paper
129 Citations
open accessOpen access Journal Article DOI: 10.1007/S11412-018-9292-Z
When Coding-and-Counting Is Not Enough: Using Epistemic Network Analysis (ENA) to Analyze Verbal Data in CSCL Research.

Abstract:

Research on computer-supported collaborative learning (CSCL) is often concerned with the question of how scaffolds or other characteristics of learning may affect learners’ social and cognitive engagement. Such engagement in socio-cognitive activities frequently materializes in discourse. In quantitative analyses of discourse... Research on computer-supported collaborative learning (CSCL) is often concerned with the question of how scaffolds or other characteristics of learning may affect learners’ social and cognitive engagement. Such engagement in socio-cognitive activities frequently materializes in discourse. In quantitative analyses of discourse, utterances are typically coded, and differences in the frequency of codes are compared between conditions. However, such traditional coding-and-counting-based strategies neglect the temporal nature of verbal data, and therefore provide limited and potentially misleading information about CSCL activities. Instead, we argue that analyses of the temporal proximity, specifically temporal co-occurrences of codes, provide a more appropriate way to characterize socio-cognitive activities of learning in CSCL settings. We investigate this claim by comparing and contrasting a traditional coding-and-counting analysis with epistemic network analysis (ENA), a discourse analysis technique that models temporal co-occurrences of codes in discourse. We apply both methods to data from a study that compared the effects of individual vs. collaborative problem solving. The results suggest that compared to a traditional coding-and-counting approach, ENA provides more insight into the socio-cognitive learning activities of students. read more read less

Topics:

Collaborative learning (58%)58% related to the paper, Cooperative learning (52%)52% related to the paper, Discourse analysis (50%)50% related to the paper
View PDF
96 Citations
open accessOpen access Journal Article DOI: 10.1007/S11412-019-09313-2
Capturing the dynamic and cyclical nature of regulation: Methodological Progress in understanding socially shared regulation in learning
Sanna Järvelä1, Hanna Järvenoja1, Jonna Malmberg1

Abstract:

Self-regulation is critical for successful learning, and socially shared regulation contributes to productive collaborative learning. The problem is that the psychological processes at the foundation of regulation are invisible and, thus, very challenging to understand, support, and influence. The aim of this paper is to revi... Self-regulation is critical for successful learning, and socially shared regulation contributes to productive collaborative learning. The problem is that the psychological processes at the foundation of regulation are invisible and, thus, very challenging to understand, support, and influence. The aim of this paper is to review the progress in socially shared regulation research data collection methods for trying to understand the complex process of regulation in the social learning context, for example, collaborative learning and computer-supported collaborative learning. We highlight the importance of tracing the sequential and temporal characteristics of regulation in learning by focusing on data for individual- and group-level shared regulatory activities that use technological research tools and by gathering in-situ data about students’ challenges that provoke regulation of learning. We explain how we understand regulation in a social context, argue why methodological progress is needed, and review the progress made in researching regulation of learning. read more read less

Topics:

Collaborative learning (63%)63% related to the paper, Social learning (60%)60% related to the paper, Educational technology (59%)59% related to the paper, Context (language use) (50%)50% related to the paper
View PDF
69 Citations
Journal Article DOI: 10.1007/S11412-018-9279-9
Challenges in online collaboration: effects of scripting shared task perceptions
Allyson F. Hadwin1, Aishah Bakhtiar1, Mariel Miller1

Abstract:

Difficulties with planning, such as negotiating task understandings and goals, can have a profound effect on regulation and task performance when students work collaboratively (Miller and Hadwin, Computers in Human Behaviour, 52, 573-588, 2015a). Despite planning being a common challenge, teams often fail to identify strategi... Difficulties with planning, such as negotiating task understandings and goals, can have a profound effect on regulation and task performance when students work collaboratively (Miller and Hadwin, Computers in Human Behaviour, 52, 573-588, 2015a). Despite planning being a common challenge, teams often fail to identify strategies for addressing those challenges successfully. The purpose of this study was to examine the effect of team planning support in the form of awareness visualizations (quantified, nominal, and no visualization of individual planning perceptions summarized across group members) on the challenges students face during collaboration, and the ways they report regulating in the face of those challenges. Findings revealed differences across conditions. Individuals in the no visualization condition (a) rated planning as more problematic, and (b) were likely to encounter doing the task, checking progress, and group work challenges when they encounter planning challenges, (c) reported more time and planning main challenges compared to doing the task and group work challenges, and (d) reported that planning strategies (adopted as a team) were most effective for addressing planning challenges, followed by teamwork strategies which were less effective. In contrast, individuals belonging to groups who received one of the two visualizations (a) reported that both planning and teamwork strategies to be equally effective for addressing planning challenges, and (b) reported higher levels of success with their strategies than groups without a visualization support. Findings attest to the importance of supporting group planning with planning visualizations. read more read less

Topics:

Teamwork (56%)56% related to the paper, Group work (53%)53% related to the paper, Task (project management) (50%)50% related to the paper
65 Citations
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13. What is Sherpa RoMEO Archiving Policy for International Journal of Computer-Supported Collaborative Learning?

SHERPA/RoMEO Database

We extracted this data from Sherpa Romeo to help researchers understand the access level of this journal in accordance with the Sherpa Romeo Archiving Policy for International Journal of Computer-Supported Collaborative Learning. The table below indicates the level of access a journal has as per Sherpa Romeo's archiving policy.

RoMEO Colour Archiving policy
Green Can archive pre-print and post-print or publisher's version/PDF
Blue Can archive post-print (ie final draft post-refereeing) or publisher's version/PDF
Yellow Can archive pre-print (ie pre-refereeing)
White Archiving not formally supported
FYI:
  1. Pre-prints as being the version of the paper before peer review and
  2. Post-prints as being the version of the paper after peer-review, with revisions having been made.

14. What are the most common citation types In International Journal of Computer-Supported Collaborative Learning?

The 5 most common citation types in order of usage for International Journal of Computer-Supported Collaborative Learning are:.

S. No. Citation Style Type
1. Author Year
2. Numbered
3. Numbered (Superscripted)
4. Author Year (Cited Pages)
5. Footnote

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