Sensemaking of social network analysis for the study of learning

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The presentation offers an introduction into week 4 of DALMOOC and it is dedicated to sensemaking of social network analysis for the study of learning

Week 4: Sensemaking of
Social Network Analysis for
the Study of Learning
Dragan Gašević
@dgasevic

Connection with
educational research and practice
Gašević, D., Dawson, S., Siemens, G. (2015). Let’s not forget: Learning analytics are about learning.
TechTrends (in press), https://bit.ly/techtrends2015

Question-driven
Data-driven analytics
Gašević, D., Dawson, S., Siemens, G. (2015). Let’s not forget: Learning analytics are about learning.
TechTrends (in press), https://bit.ly/techtrends2015

What data sources for
network extraction to use?
Discussion boards, course enrollments, and
Twitter

Which educational constructs to use?
Learning design, sense of community,
creative potential, social presence,
academic performance,
distributed (MOOC) pedagogy

What additional data to collect?
Course enrollments, grades, self-reports,
quantitative content analysis codes, course design

To do in this week
Hands-on activities and assignments
Integration with knowledge gained in weeks 1-2

More than welcome
The use of your data
Discussion of questions of direct interest for you

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Sensemaking of social network analysis for the study of learning

1. Week 4: Sensemaking of Social Network Analysis for the Study of Learning Dragan Gašević @dgasevic

2. Connection with educational research and practice Gašević, D., Dawson, S., Siemens, G. (2015). Let’s not forget: Learning analytics are about learning. TechTrends (in press), https://bit.ly/techtrends2015

3. Question-driven Data-driven analytics Gašević, D., Dawson, S., Siemens, G. (2015). Let’s not forget: Learning analytics are about learning. TechTrends (in press), https://bit.ly/techtrends2015

4. Case studies discussed

5. How questions are formulated?

6. What data sources for network extraction to use? Discussion boards, course enrollments, and Twitter

7. Which educational constructs to use? Learning design, sense of community, creative potential, social presence, academic performance, distributed (MOOC) pedagogy

8. What additional data to collect? Course enrollments, grades, self-reports, quantitative content analysis codes, course design

9. To do in this week Hands-on activities and assignments Integration with knowledge gained in weeks 1-2

10. More than welcome The use of your data Discussion of questions of direct interest for you

Sensemaking of social network analysis for the study of learning

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