This document discusses research approaches for studying emerging e-learning practices and technologies. It focuses on learning analytics and social network analysis. Learning analytics can help understand learning behavior, provide evidence for improving learning environments, and support assessment/feedback, enquiry/sensemaking, and discourse. Examples discussed include open feedback tools, social networks to support knowledge construction, and discourse analysis. Combining different data sources through powerful analytics tools can provide insights. Resources on learning analytics and social network analysis of OER communities are also listed.

1. Researching with and
through technologies
Gráinne Conole
PhD Research Day
University of Leicester
14th September 2012

2. landscape
Emergent technologies
Theory and methodology
E-pedagogies, strategies
and affordances
and learning design
Resources, OER and
Pedagogical Patterns
Evaluations Interventions

3. What is needed in a world
of new and proliferating e-
learning practices are
research approaches that
are multiple and varied
and that recognise their
heterogeneity explicitly.
(Friesen, 2009)
From Web pages and
forums to complex
online interactions
Are we up for the challenge???

4. Examples
• Learning
analytics
• Social Network
Analysis

5. Learning Analytics
Measurement, collection,
analysis and reporting of data
about learners and their
contexts, for the purposes of
understanding and optimising
learning and the environments in
which it occurs
US Department of Education

6. We leave trails
everywhere we
go and that data
is valuable
(George
Siemens)

10. Erik Duval

12. Contribution
• Learning analytics:
• as a tool to understand learning
behaviour
• to provide evidence to support design
of more effective learning
environments
• to make effective use of social and
participatory media

13. Pedagogies
• Learning analytics to foster:
• Assessment and feedback
• Enquiry and sensemaking
• Discourse

14. Assessment &
feedback
• Importance of assessment and
feedback as part of the learning
process
• Issues around markingand workload
• Open Mentor and Open Comment:
feedback through reflection and social
networking
• Coding of feedback comments and
power of Bale’s categories of group
interaction Whitelock

15. Enquiry and
sensemaking like
• New social networking spaces
Cloudworks to support dialogue and
knowledge construction
• Cloudworks: object- rather than ego
centric, collective aggregation and
improvement, supporting collective
intelligence and distribution cognition
(Salomon, 1983)
• Disputational, cumulative and exploratory
talk
Ferguson

16. Discourse
• Cohere: structured discourse and
knowledge construction
• Discourse as an indicator of learning
• Language as social action
• Visualisation both as an analytic tool
and a means of supporting
sensemaking
Buckingham Shum

17. Putting it all together
• Combining different forms of data analytics
• VLE stats
• Library analytics
• Sitewide tracking
• Course analytics
• Powerful new analytics tools to understand
data and network connections
• Making sense of Massive Open Online
Courses Hirst

18. Resources
• LAK11 conference
https://tekri.athabascau.ca/analytics/
• Special issue of
ETShttp://www.learninganalytics.net/
• Definitionshttp://learninganalytics.net/LearningAnal
yticsDefinitionsProcessesPotential.pdf
• Siemens: presentation
http://www.slideshare.net/gsiemens/learning-
analytics-educause

19. Social Network Analysis

20. OER communities
• 7 in-depth case studies
• Articulate the nature of the OER communities
and the patterns of user behaviour
• Using the LOOK SNA tool
• Relationships between individuals and
themes

21. LOOK tool
• Interviews
• Thematic analysis
• Key themes
• Filter by user and
theme connections