Example of Journal of Computer Assisted Learning format
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Example of Journal of Computer Assisted Learning format Example of Journal of Computer Assisted Learning format Example of Journal of Computer Assisted Learning format Example of Journal of Computer Assisted Learning format Example of Journal of Computer Assisted Learning format Example of Journal of Computer Assisted Learning format Example of Journal of Computer Assisted Learning format Example of Journal of Computer Assisted Learning format Example of Journal of Computer Assisted Learning format
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Example of Journal of Computer Assisted Learning format Example of Journal of Computer Assisted Learning format Example of Journal of Computer Assisted Learning format Example of Journal of Computer Assisted Learning format Example of Journal of Computer Assisted Learning format Example of Journal of Computer Assisted Learning format Example of Journal of Computer Assisted Learning format Example of Journal of Computer Assisted Learning format Example of Journal of Computer Assisted Learning format
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Journal of Computer Assisted Learning — Template for authors

Publisher: Wiley
Categories Rank Trend in last 3 yrs
Education #53 of 1319 up up by 13 ranks
Computer Science Applications #140 of 693 up up by 3 ranks
journal-quality-icon Journal quality:
High
calendar-icon Last 4 years overview: 272 Published Papers | 1606 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.

2.126

13% from 2018

Impact factor for Journal of Computer Assisted Learning from 2016 - 2019
Year Value
2019 2.126
2018 2.451
2017 1.859
2016 1.253
graph view Graph view
table view Table view

5.9

13% from 2019

CiteRatio for Journal of Computer Assisted Learning from 2016 - 2020
Year Value
2020 5.9
2019 5.2
2018 4.4
2017 4.2
2016 5.7
graph view Graph view
table view Table view

insights Insights

  • Impact factor of this journal has decreased by 13% in last year.
  • This journal’s impact factor is in the top 10 percentile category.

insights Insights

  • CiteRatio of this journal has increased by 13% 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.

1.583

3% from 2019

SJR for Journal of Computer Assisted Learning from 2016 - 2020
Year Value
2020 1.583
2019 1.54
2018 1.382
2017 1.397
2016 1.724
graph view Graph view
table view Table view

2.212

16% from 2019

SNIP for Journal of Computer Assisted Learning from 2016 - 2020
Year Value
2020 2.212
2019 1.91
2018 2.354
2017 1.893
2016 2.344
graph view Graph view
table view Table view

insights Insights

  • SJR of this journal has increased by 3% in last years.
  • This journal’s SJR is in the top 10 percentile category.

insights Insights

  • SNIP of this journal has increased by 16% in last years.
  • This journal’s SNIP is in the top 10 percentile category.
Journal of Computer Assisted Learning

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Wiley

Journal of Computer Assisted Learning

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 w...... Read More

Education

Computer Science Applications

Social Sciences

i
Last updated on
22 Jun 2020
i
ISSN
0266-4909
i
Impact Factor
High - 2.204
i
Acceptance Rate
Not provided
i
Frequency
Not provided
i
Open Access
Yes
i
Sherpa RoMEO Archiving Policy
Yellow faq
i
Plagiarism Check
Available via Turnitin
i
Endnote Style
Download Available
i
Bibliography Name
apa
i
Citation Type
Numbered
[25]
i
Bibliography Example
Beenakker, C.W.J. (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

Journal Article DOI: 10.1111/J.1365-2729.2010.00387.X
The Effect of Twitter on College Student Engagement and Grades
Reynol Junco1, Greg Heiberger2, Eric Loken3

Abstract:

Despite the widespread use of social media by students and its increased use by instructors, very little empirical evidence is available concerning the impact of social media use on student learning and engagement. This paper describes our semester-long experimental study to determine if using Twitter – the microblogging and ... Despite the widespread use of social media by students and its increased use by instructors, very little empirical evidence is available concerning the impact of social media use on student learning and engagement. This paper describes our semester-long experimental study to determine if using Twitter – the microblogging and social networking platform most amenable to ongoing, public dialogue – for educationally relevant purposes can impact college student engagement and grades. A total of 125 students taking a first year seminar course for pre-health professional majors participated in this study (70 in the experimental group and 55 in the control group). With the experimental group, Twitter was used for various types of academic and co-curricular discussions. Engagement was quantified by using a 19-item scale based on the National Survey of Student Engagement. To assess differences in engagement and grades, we used mixed effects analysis of variance (ANOVA) models, with class sections nested within treatment groups. We also conducted content analyses of samples of Twitter exchanges. The ANOVA results showed that the experimental group had a significantly greater increase in engagement than the control group, as well as higher semester grade point averages. Analyses of Twitter communications showed that students and faculty were both highly engaged in the learning process in ways that transcended traditional classroom activities. This study provides experimental evidence that Twitter can be used as an educational tool to help engage students and to mobilize faculty into a more active and participatory role. read more read less

Topics:

National Survey of Student Engagement (67%)67% related to the paper, Student engagement (65%)65% related to the paper, Social media (57%)57% related to the paper, Microblogging (54%)54% related to the paper, Collaborative learning (51%)51% related to the paper
1,425 Citations
Journal Article DOI: 10.1111/J.1365-2729.1991.TB00230.X
Why is science difficult to learn? Things are seldom what they seem
Alex H. Johnstone1

Abstract:

The difficulties of learning science are related to the nature of science itself and to the methods by which science is customarily taught without regard to what is known about children's learning. An information processing model is proposed to guide thinking and research in this area. The difficulties of learning science are related to the nature of science itself and to the methods by which science is customarily taught without regard to what is known about children's learning. An information processing model is proposed to guide thinking and research in this area. read more read less

Topics:

Nature of Science (62%)62% related to the paper, Science education (61%)61% related to the paper, Learning sciences (60%)60% related to the paper
1,045 Citations
Journal Article DOI: 10.1111/J.1365-2729.2005.00129.X
Using mobile phones in English education in Japan
Patricia Thornton1, Chris Houser1

Abstract:

We present three studies in mobile learning First, we polled 333 Japanese university students regarding their use of mobile devices One hundred percent reported owning a mobile phone Ninety-nine percent send e-mail on their mobile phones, exchanging some 200 e-mail messages each week Sixty-six percent e-mail peers about cl... We present three studies in mobile learning First, we polled 333 Japanese university students regarding their use of mobile devices One hundred percent reported owning a mobile phone Ninety-nine percent send e-mail on their mobile phones, exchanging some 200 e-mail messages each week Sixty-six percent e-mail peers about classes; 44% e-mail for studying In contrast, only 43% e-mail on PCs, exchanging an average of only two messages per week Only 20% had used a personal digital assistant Second, we e-mailed 100-word English vocabulary lessons at timed intervals to the mobile phones of 44 Japanese university students, hoping to promote regular study Compared with students urged to regularly study identical materials on paper or Web, students receiving mobile e-mail learned more (P<005) Seventy-one percent of the subjects preferred receiving these lessons on mobile phones rather than PCs Ninety-three percent felt this a valuable teaching method Third, we created a Web site explaining English idioms Student-produced animation shows each idiom's literal meaning; a video shows the idiomatic meaning Textual materials include an explanation, script, and quiz Thirty-one Japanese college sophomores evaluated the site using video-capable mobile phones, finding few technical difficulties, and rating highly its educational effectiveness read more read less

Topics:

Mobile phone (59%)59% related to the paper, Electronic mail (53%)53% related to the paper
849 Citations
Journal Article DOI: 10.1111/J.1365-2729.2012.00487.X
Technological pedagogical content knowledge – a review of the literature
Joke Voogt1, Petra Fisser1, N.N. Pareja Roblin2, Jo Tondeur3, J. van Braak2

Abstract:

Technological Pedagogical Content Knowledge (TPACK) has been introduced as a conceptual framework for the knowledge base teachers need to effectively teach with technology. The framework stems from the notion that technology integration in a specific educational context benefits from a careful alignment of content, pedagogy a... Technological Pedagogical Content Knowledge (TPACK) has been introduced as a conceptual framework for the knowledge base teachers need to effectively teach with technology. The framework stems from the notion that technology integration in a specific educational context benefits from a careful alignment of content, pedagogy and the potential of technology, and that teachers who want to integrate technology in their teaching practice therefore need to be competent in all three domains. This study is a systematic literature review about TPACK of 55 peer-reviewed journal articles (and one book chapter), published between 2005 and 2011. The purpose of the review was to investigate the theoretical basis and the practical use of TPACK. Findings showed different understandings of TPACK and of technological knowledge. Implications of these different views impacted the way TPACK was measured. Notions about TPACK in subject domains were hardly found in the studies selected for this review. Teacher knowledge (TPACK) and beliefs about pedagogy and technology are intertwined. Both determine whether a teacher decides to teach with technology. Active involvement in (re)design and enactment of technology-enhanced lessons was found as a promising strategy for the development of TPACK in (student-)teachers. Future directions for research are discussed read more read less

Topics:

Technology integration (55%)55% related to the paper, Teacher education (51%)51% related to the paper, Knowledge base (51%)51% related to the paper
722 Citations
open accessOpen access Journal Article DOI: 10.1111/J.1365-2729.2010.00360.X
Beyond the ‘digital natives’ debate: Towards a more nuanced understanding of students' technology experiences
Sue Bennett1, Karl Maton2

Abstract:

The idea of the ‘digital natives’, a generation of tech-savvy young people immersed in digital technologies for which current education systems cannot cater, has gained widespread popularity on the basis of claims rather than evidence. Recent research has shown flaws in the argument that there is an identifiable generation or... The idea of the ‘digital natives’, a generation of tech-savvy young people immersed in digital technologies for which current education systems cannot cater, has gained widespread popularity on the basis of claims rather than evidence. Recent research has shown flaws in the argument that there is an identifiable generation or even a single type of highly adept technology user. For educators, the diversity revealed by these studies provides valuable insights into students’ experiences of technology inside and outside formal education. While this body of work provides a preliminary understanding, it also highlights subtleties and complexities that require further investigation. It suggests, for example, that we must go beyond simple dichotomies evident in the digital natives debate to develop a more sophisticated understanding of our students’ experiences of technology. Using a review of recent research findings as a starting point, this paper identifies some key issues for educational researchers, offers new ways of conceptualizing key ideas using theoretical constructs from Castells, Bourdieu and Bernstein, and makes a case for how we need to develop the debate in order to advance our understanding. read more read less

Topics:

Digital native (58%)58% related to the paper
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614 Citations
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Frequently asked questions

1. Can I write Journal of Computer Assisted Learning in LaTeX?

Absolutely not! Our tool has been designed to help you focus on writing. You can write your entire paper as per the Journal of Computer Assisted Learning guidelines and auto format it.

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Yes, the template is compliant with the Journal of Computer Assisted Learning guidelines. Our experts at SciSpace ensure that. If there are any changes to the journal's guidelines, we'll change our algorithm accordingly.

3. Can I cite my article in multiple styles in Journal of Computer Assisted Learning?

Of course! We support all the top citation styles, such as APA style, MLA style, Vancouver style, Harvard style, and Chicago style. For example, when you write your paper and hit autoformat, our system will automatically update your article as per the Journal of Computer Assisted Learning citation style.

4. Can I use the Journal of Computer Assisted Learning templates for free?

Sign up for our free trial, and you'll be able to use all our features for seven days. You'll see how helpful they are and how inexpensive they are compared to other options, Especially for Journal of Computer Assisted Learning.

5. Can I use a manuscript in Journal of Computer Assisted Learning that I have written in MS Word?

Yes. You can choose the right template, copy-paste the contents from the word document, and click on auto-format. Once you're done, you'll have a publish-ready paper Journal of Computer Assisted Learning that you can download at the end.

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7. Where can I find the template for the Journal of Computer Assisted Learning?

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SciSpace's Journal of Computer Assisted Learning is currently available as an online tool. We're developing a desktop version, too. You can request (or upvote) any features that you think would be helpful for you and other researchers in the "feature request" section of your account once you've signed up with us.

10. I cannot find my template in your gallery. Can you create it for me like Journal of Computer Assisted Learning?

Sure. You can request any template and we'll have it setup within a few days. You can find the request box in Journal Gallery on the right side bar under the heading, "Couldn't find the format you were looking for like Journal of Computer Assisted Learning?”

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12. Is Journal of Computer Assisted Learning's impact factor high enough that I should try publishing my article there?

To be honest, the answer is no. The impact factor is one of the many elements that determine the quality of a journal. Few of these factors include review board, rejection rates, frequency of inclusion in indexes, and Eigenfactor. You need to assess all these factors before you make your final call.

13. What is Sherpa RoMEO Archiving Policy for Journal of Computer Assisted 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 Journal of Computer Assisted 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 Journal of Computer Assisted Learning?

The 5 most common citation types in order of usage for Journal of Computer Assisted Learning are:.

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

15. How do I submit my article to the Journal of Computer Assisted Learning?

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16. Can I download Journal of Computer Assisted Learning in Endnote format?

Yes, SciSpace provides this functionality. After signing up, you would need to import your existing references from Word or Bib file to SciSpace. Then SciSpace would allow you to download your references in Journal of Computer Assisted Learning Endnote style according to Elsevier guidelines.

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