Using Social Network Analysis to Understand Sense of Community in an Online Learning Environment

2008 ◽  
Vol 39 (1) ◽  
pp. 17-36 ◽  
Author(s):  
Demei Shen ◽  
Piyanan Nuankhieo ◽  
Xinxin Huang ◽  
Christopher Amelung ◽  
James Laffey
2020 ◽  
pp. 204275302095497
Author(s):  
Jiaming Cheng ◽  
Jing Lei

Student-student interaction can benefit learning as well as provide a sense of community in online courses. Blogging is a common approach to provide opportunities for students to communicate with each other. This study used Social Network Analysis to depict commenting behaviour between students in an online graduate-level course. By examining the weekly interaction data, the results revealed how students’ commenting behaviours changed during the semester. Student participation and interaction in the blogging activity was influenced by the various pedagogical elements that were either directly or indirectly related to the blogging activity.


2015 ◽  
Vol 13 (10) ◽  
pp. 3482-3487 ◽  
Author(s):  
A.S. Silva ◽  
S.R. Brito ◽  
N.L. Vijaykumar ◽  
C.A.J. Rocha ◽  
J.C.W.A. Costa ◽  
...  

Author(s):  
Robert A Ellis ◽  
Ana-Maria Bliuc ◽  
Feifei Han

The ability to collaborate effectively face-to-face and online represents a critical skill for university graduates. However, there are still challenges regarding how to accurately assess this skill through traditional student learning measures. To better understand the nature of effective collaboration of university students in blended courses, the current study drew on the student approaches to learning framework and social network analysis techniques. We examined how student approaches to inquiry, approaches to online learning technologies, perceptions of the blended learning environment, different learning outcomes and configurations of collaboration are related. The methodologies commonly used in student approaches to learning research identified deep and surface approaches to inquiry and technologies, positive and negative perceptions of the integration of the learning environment, and of online workload, which also showed logical alignment with relatively better and poorer academic achievement in the course. Based on approaches, perceptions, and learning outcomes, students were divided into groups orientated towards understanding versus reproducing learning. The social network analysis techniques revealed features of different configurations of collaborations by different groups of students and their choices as to whether and with whom to collaborate during the learning process. Nuanced differences were found amongst different configurations of collaborations. Implications for practice or policy: When assessing student experience of collaboration, social network analysis techniques may be able to describe nuanced differences amongst different collaborative configurations. To encourage students’ collaboration, assessment tasks involving a large proportion of mandatory collaborative activities should be considered. To help student improve experience of collaboration, teachers may consider pairing students with a reproducing learning orientation with those having a deep disciplinary understanding.


Sign in / Sign up

Export Citation Format

Share Document