Authors:
M. E. Sousa-Vieira
;
J. C. López-Ardao
and
M. Fernández-Veiga
Affiliation:
University of Vigo, Spain
Keyword(s):
Online Social Networks, Collaborative Learning, Social Networks Analysis.
Related
Ontology
Subjects/Areas/Topics:
Computer-Supported Education
;
e-Learning
;
Game-Based and Simulation-Based Learning
;
Information Technologies Supporting Learning
;
Learning Analytics
;
Learning/Teaching Methodologies and Assessment
Abstract:
The widespread use of computing and communications technologies has enabled the popularity of social networks
oriented to learn. In a previous work, we studied the nature and strength of associations between
undergraduate students of an introductory course on computer networks, using an online social network embedded
in a learning management system. With datasets from two offerings of the same course, we mined the
sequences of questions and answers posted by the students to identify structural properties of the social graph,
patterns of collaboration among students and factors influencing the final achievements, concluding that the
structural properties most correlated to the final academic results are robust measures of centrality (degree and
eigenvector), which are already detectable since the first weeks of the course. In this work, we apply SNA to
graduate engineering students enrolled in a master level course in computer networks. The results obtained
show that quality
participation in the social activities appears to be correlated with the final outcome of the
course, and that good students tend to show denser egonetworks. Our analysis contributes to the understanding
of the role of social learning among highly educated students.
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