(Created page with "==1 Title, abstract and keywords<!-- Your document should start with a concise and informative title. Titles are often used in information-retrieval systems. Avoid abbreviatio...")
 
 
(One intermediate revision by the same user not shown)
Line 1: Line 1:
−
==1 Title, abstract and keywords<!-- Your document should start with a concise and informative title. Titles are often used in information-retrieval systems. Avoid abbreviations and formulae where possible. Capitalize the first word of the title.
+
The effect of centralization and cohesion on the social construction of knowledge in discussion forums
−
 
+
−
Provide a maximum of 6 keywords, and avoiding general and plural terms and multiple concepts (avoid, for example, 'and', 'of'). Be sparing with abbreviations: only abbreviations firmly established in the field should be used. These keywords will be used for indexing purposes.
+
−
 
+
−
An abstract is required for every document; it should succinctly summarize the reason for the work, the main findings, and the conclusions of the study. Abstract is often presented separately from the article, so it must be able to stand alone. For this reason, references and hyperlinks should be avoided. If references are essential, then cite the author(s) and year(s). Also, non-standard or uncommon abbreviations should be avoided, but if essential they must be defined at their first mention in the abstract itself. -->==
+
−
 
+
−
 
+
  
 +
Interactive relationships in online learning communities can influence the process and quality of knowledge building. The aim of this study is to empirically investigate the relationships between network structures and social knowledge building in an asynchronous writing environment through discussion forums in a learning management system. The quality of the knowledge construction process is evaluated through content analysis, and the network structures are analyzed using a social network analysis of the response relations among participants during online discussions. Structural equation modeling is used to analyze relations between network structures and knowledge construction. Working on data extracted from a 6-week distance-learning experiment, we analyzed how 10 groups developed collaborative learning social networks when participants worked together on case resolution. The results show a positive correlation between cohesion and centralization, and the positive influence of the cohesion index and the centralization index on social presence and cognitive presence in knowledge building. However, this must be understood within the context of social networks in which messages sent to all group members occupy the center. This underlines the need for reinforcing participations that are directed to the group as a whole, and the importance of the fact the network contains both central and intermediate members. By contrast, we propose that the combination of analysis techniques used is a good option for this type of study while recognizing that it is necessary to continue validating the instruments in terms of their own theoretical suppositions.
  
 
==2 The main text<!-- You can enter and format the text of this document by selecting the ‘Edit’ option in the menu at the top of this frame or next to the title of every section of the document. This will give access to the visual editor. Alternatively, you can edit the source of this document (Wiki markup format) by selecting the ‘Edit source’ option.
 
==2 The main text<!-- You can enter and format the text of this document by selecting the ‘Edit’ option in the menu at the top of this frame or next to the title of every section of the document. This will give access to the visual editor. Alternatively, you can edit the source of this document (Wiki markup format) by selecting the ‘Edit source’ option.

Latest revision as of 08:31, 17 April 2019

The effect of centralization and cohesion on the social construction of knowledge in discussion forums

Interactive relationships in online learning communities can influence the process and quality of knowledge building. The aim of this study is to empirically investigate the relationships between network structures and social knowledge building in an asynchronous writing environment through discussion forums in a learning management system. The quality of the knowledge construction process is evaluated through content analysis, and the network structures are analyzed using a social network analysis of the response relations among participants during online discussions. Structural equation modeling is used to analyze relations between network structures and knowledge construction. Working on data extracted from a 6-week distance-learning experiment, we analyzed how 10 groups developed collaborative learning social networks when participants worked together on case resolution. The results show a positive correlation between cohesion and centralization, and the positive influence of the cohesion index and the centralization index on social presence and cognitive presence in knowledge building. However, this must be understood within the context of social networks in which messages sent to all group members occupy the center. This underlines the need for reinforcing participations that are directed to the group as a whole, and the importance of the fact the network contains both central and intermediate members. By contrast, we propose that the combination of analysis techniques used is a good option for this type of study while recognizing that it is necessary to continue validating the instruments in terms of their own theoretical suppositions.

2 The main text

3 Bibliography

4 Acknowledgments

5 References

Back to Top
GET EPUB

Document information

Published on 01/01/2012

DOI: 10.1080/10494820.2012.745437
Licence: CC BY-NC-SA license

Web of Science Core Collection® Times cited: 22
Crossref Cited-by Times cited: 17
OpenCitations.net Times cited: 13

Document Score

0

Times cited: 22
Views 8
Recommendations 0

Share this document

Keywords

• • • •

claim authorship

Are you one of the authors of this document?

I am an author