9th International Conference on Networked Learning, Edinburgh, United Kingdom, 7 - 09 April 2014, pp.1-5
It is obvious that, human life is being affected by the facilities of new technologies with all of its
aspects including learning and development. On the other hand, besides the increasing use of the
facilities, we have limited knowledge about the question of how social interaction and Web 2.0
technologies affect the training environments in workplace context. This study, which is a part of an
on-going doctoral research, aims at investigating the interactions among participants within the
networks constructed in an online learning environment in corporate training context (Sosyal 2.0)
while verifying network coding procedures and providing evidence for the methodological issues
regarding the use of SNA in combination with other methods in researching Networked Learning.
Training and adult learning literature is limited when compared to the areas of formal education,
teacher training or higher education. The current study, examining corporate training, aims at
contributing to the literature, as the field of NL research is untouched, especially in Turkey.
The study is conducted in cooperation with Enocta, an e-learning company in Turkey. The logs of
Enocta's LMS with social interaction capabilities, called "Sosyal 2.0", are used as the data source.
The members of Enocta who participate by using facilities of Sosyal 2.0 formed the actors of the
network. Networks are constructed according to different web 2.0 facilities in Sosyal 2.0: "wallpostcomment" (WPC), "wallpost-like" (WPL), "question-answer" (QA), "question-comment" (QC),
"question-like" (QL) and "blog post-like" (BPL) networks are constructed. To be able to examine the
interactions among participants Average Degree, Degree Centralization, Closeness Centralization,
Betweenness Centralization and Cohesion analysis are carried out using PAJEK Software.
The results revealed that the tightest interaction was constructed via wall platform in Sosyal 2.0 in
comparison to BPC, BPL, QL and QA platforms. The results of cohesive sub-groups reveal that, the
users of Sosyal 2.0 form a comparatively big community by using wall platform. On the other hand;
QAC, BPC and BPL networks had revealed weak components and small mutual relationships. These
findings indicate that the information sharing among participants are not dispersed into several,
middle sized sub groups in Sosyal 2.0. Rather it is more centralized in wall platform and mostly in
mutual level for the QAC, BPC and BPL networks. These findings deserve further investigation
including users' preferences and gratification and individual level network analysis methods.