A review of methodological applications of social network analysis in computer-supported collaborative learning
Publication date: November 2017 Source:Educational Research Review, Volume 22 Author(s): Marielle Dado, Daniel Bodemer Social network analysis (SNA) is a promising research method for analyzing relational ties in computer-supported collaborative learning (CSCL)—activities in which learners interact towards a common learning goal with the aid of computers—because they share the same underlying assumption that learning and behavior are influenced by one's relations. This methodological review examines whether CSCL research (n = 89) (1) reflects the diversity of actors (learners and artifacts) and relational ties that are important in CSCL environments; and (2) relates these relational ties as measured by SNA indices to CSCL learning outcomes. The results suggest that SNA applications in CSCL (1) do not reflect this diversity of CSCL actors and relational ties, investigating only one-mode networks of learners connected by communication-based relational ties; and (2) are limited to a descriptive reporting of SNA results. Future directions for CSCL are focused on filling these gaps by (1) integrating technical, instructional and knowledge artifacts as SNA actors, and (2) relating SNA findings to cognitive, social and motivational CSCL outcomes using statistical analysis.
Conclusion: These results indicate that MALAT1/MDM2/p53 signaling pathway axis may provide more effective clinical therapeutic strategy for patients with ischemic stroke.Cell Physiol Biochem 2018;50:2216 –2228
Conclusion: Interaction between suicide and SUD seems to influence the expression of genes involved in glial proliferation and glutamatergic neurotransmission. These results highlight, for the first time, that suicides with SUD have a gene expression profile distinct from that of subjects with only one of these disorders.Mol Neuropsychiatry
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