Data Visualisation: An OER Taster

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This document discusses data visualization of Open Educational Resources (OER) projects. It describes using Google Refine to reconcile OER records from a repository by institution name in order to analyze contributions by institution and location. Visualizations were created using tools like Google Spreadsheets and Timemap.js to combine page views, social shares, and other data about the OERs. The document provides an overview of various tools and libraries that can be used for data visualization and analysis.

Education Technology

Intro Data Visualisation Kitchen

Data Visualisation: An OER Taster
Martin Hawksey (@mhawksey) This work is licensed under a Creative
Commons Attribution 3.0 Unported
License. CC-BY Martin Hawksey

This work is licensed under a Creative
Commons Attribution 3.0 Unported
License. CC-BY Martin Hawksey

http://bit.ly/iwmw12P3

This work is licensed under a Creative
Commons Attribution 3.0 Unported
License. CC-BY Martin Hawksey

Analytics

"Analytics is the process of developing actionable
insights through problem definition and the
application of statistical models and analysis
against existing and/or simulated future data.“
Adam Cooper
http://blogs.cetis.ac.uk/adam/2012/04/27/analytics-and-big-data-reflections-from-the-teradata-
universe-conference-2012/

This work is licensed under a Creative
http://mashe.hawksey. Commons Attribution 3.0 Unported
License. CC-BY Martin Hawksey

Data Scientist

"a business analyst who lives in California“

“someone who: wants to know what the question
should be; embodies a combination of curiosity,
data gathering skills, statistical and modelling
expertise and strong communication skills”
Adam Cooper
http://blogs.cetis.ac.uk/adam/2012/04/27/analytics-and-big-data-reflections-from-the-
teradata-universe-conference-2012/

This work is licensed under a Creative
http://mashe.hawksey. Commons Attribution 3.0 Unported
License. CC-BY Martin Hawksey

Background

 To „visualise‟ the JISC/HEA Open Educational
Resources (OER) Phase 1 & 2

 Summary post with links http://bit.ly/OERVis

This work is licensed under a Creative
http://mashe.hawksey. Commons Attribution 3.0 Unported
License. CC-BY Martin Hawksey

Refining Jorum/OAI Harvesting

 Details of everything I‟m about to show you is
here

http://bit.ly/refinejorum

This work is licensed under a Creative
http://mashe.hawksey. Commons Attribution 3.0 Unported
License. CC-BY Martin Hawksey

http://dspace.jorum.ac.uk/xmlui/handle/123456789/15853

This work is licensed under a Creative
Commons Attribution 3.0 Unported
License. CC-BY Martin Hawksey

This work is licensed under a Creative
http://mashe.hawksey. Commons Attribution 3.0 Unported
License. CC-BY Martin Hawksey

Google Refine and OAI-PMH

This work is licensed under a Creative
http://mashe.hawksey. Commons Attribution 3.0 Unported
License. CC-BY Martin Hawksey

forEach(value.parseHtml().select("dc|
creator"),v,v.htmlText()).join(",")

This work is licensed under a Creative
http://mashe.hawksey. Commons Attribution 3.0 Unported
License. CC-BY Martin Hawksey

if(contains(value.toLowercase(),"univ
ersity"),filter(value.toLowercase().s
plit(/[-
,.;()]|(s+for+s)+/),v,contains(v,
"university"))[0].trim(),if(contains(
value.toLowercase(),"centre"),value.t
oLowercase(),""))

This work is licensed under a Creative
http://mashe.hawksey. Commons Attribution 3.0 Unported
License. CC-BY Martin Hawksey

Reconciliation

This work is licensed under a Creative
Commons Attribution 3.0 Unported
License. CC-BY Martin Hawksey

What was achieved

 Jorum contains 9,502 unique records containing
„ukoer‟ of which 8,859 can be reconciled against
institution names
 With institution name
A. Can see contributions per institution
B. Can get location data

This work is licensed under a Creative
Commons Attribution 3.0 Unported
License. CC-BY Martin Hawksey

Combine

 Pages access counts
 Social share counts (very little sharing or
repository records)

This work is licensed under a Creative
http://mashe.hawksey. Commons Attribution 3.0 Unported
License. CC-BY Martin Hawksey

http://bit.ly/jorumspreadsheet
http://mashe.hawksey. This work is licensed under a Creative
Commons Attribution 3.0 Unported
License. CC-BY Martin Hawksey

http://nyti.ms/c2C09A

This work is licensed under a Creative
Commons Attribution 3.0 Unported
License. CC-BY Martin Hawksey

Tools/Libraries

• Tools • Libraries
– Google Refine – timemap.js
– Google – RaphaelJS
Spreadsheets – d3
– R/RStudio – SIMILE Timeline
– NodeXL & Gephi – Google
– Gource Visualisation

This work is licensed under a Creative
http://mashe.hawksey. Commons Attribution 3.0 Unported
License. CC-BY Martin Hawksey

Data Use == Data
Validation

This work is licensed under a Creative
http://mashe.hawksey. Commons Attribution 3.0 Unported
License. CC-BY Martin Hawksey

Questions?

Martin Hawksey
@mhawksey

Summary post with links http://bit.ly/OERVis

This work is licensed under a Creative
Commons Attribution 3.0 Unported
License. CC-BY Martin Hawksey

There has been much research in the use of social media to support learning and teaching. In many instances it is argued that it enables a decentralization of learning moving towards a distributed model which has many benefits including supporting a stronger foundation for lifelong learning. Twitter is one service that has been widely used within this context. The introduction of hashtags as a mechanism to allow communities to form and contribute to a topic is now a well established model within both formal and informal education as well as in society in general. The use of Twitter in this way removes boundaries extending the opportunities for co-learning, in particular, discussions can become less siloed, every contribution to a hashtag community is potentially another opportunity for someone else to join the conversation. The thinning of the walls in this way is not without it implications and the vulnerability of being a learner should never be underestimated. Another consideration is that Twitter has been adopted as a tool to support learning in this way rather than being designed for this purpose. As a result exploring and finding understanding within hashtag communities can be problematic and with many open learning contexts individuals can end up feeling lost. This conversation will explore approaches to help learners and educators gain more insight and a feeling of place within hashtag communities. As part of this we will look at TAGS and TAGSExplorer tools (https://tags.hawksey.info) which have been developed with educators and learners in mind to help support the collection, analysis and exploration of Twitter hashtag communities. These free tools provide a means to collect data from Twitter searches and analysis the results either in Google Sheets, where the data is collected, or visualized in the companion TAGSExplorer web interface. As part of this conversation we will touch upon the limitation of data collection from Twitter and issues around data protection and privacy. We will also provide some examples of where TAGS/TAGSExplorer has been used within an educational context.

TEL Quality and Innovation: What can be learned from the history of computer ...

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Presented at ILTA EdTech 2017, Sligo, Ireland Supporting posthttps://mashe.hawksey.info/?p=17538 Patterns are left behind. Whether it be replies to a discussion forums, interactions on social media or ingredients in cocktails links can be made and the data used for actionable insight. Network science is one approach that takes these seemingly complex connections and through the use of mathematical methods make it easier to understand. Network science is a well established discipline and it’s origins can be traced to 1736 and the work of Leonhard Euler. The area of social network analysis is a more recent development established in work by Moreno and Jennings in the 1930s. Accessibility to affordable computing in the 1990s combined with data from early social networks like IRC has led to an explosion of interest in social network analysis. This has continued with the emergence of social networking sites like Facebook and Twitter combined with accessibility to the underlying data. The use of network science and social network analysis within educational contexts has seen similar growth. The emergence of ‘Learning Analytics’ as a field of study has highlighted how data can be used to enhance learning and teaching. With social network analysis we can take seemingly complex relationships and making them less complicated. Common applications of network analysis in this area include: identification of isolated students within group activities; identification of people or concepts which are ‘network bridges’; clustering of categorisation of topics; plus numerous other applications. This presentation is designed to be an introduction into network analysis allowing delegates the opportunity to understand the underlying structure of the graph as well as some of the tools that can be used to construct them. The session will begin with an introduction to key network analysis terms and go on to introduce some of the tools and techniques for social network analysis, specifically looking at how data can be collected and analysed from Twitter using tools like TAGS and NodeXL.

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Google Apps Script the Authentic{ated} Mobile Playground

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Using CiviCRM in Google Drive with the new CiviService Google Script Library

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Learning analytics gaining good actionable insight

Martin Hawksey

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Breaking the Cell #WebExpo

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ocTEL and Open Badges #altc

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Data Visualisation: An OER Taster

1. Intro Data Visualisation Kitchen Data Visualisation: An OER Taster Martin Hawksey (@mhawksey) This work is licensed under a Creative Commons Attribution 3.0 Unported License. CC-BY Martin Hawksey

2. This work is licensed under a Creative Commons Attribution 3.0 Unported License. CC-BY Martin Hawksey

3. http://bit.ly/iwmw12P3 This work is licensed under a Creative Commons Attribution 3.0 Unported License. CC-BY Martin Hawksey

4. Analytics "Analytics is the process of developing actionable insights through problem definition and the application of statistical models and analysis against existing and/or simulated future data.“ Adam Cooper http://blogs.cetis.ac.uk/adam/2012/04/27/analytics-and-big-data-reflections-from-the-teradata- universe-conference-2012/ This work is licensed under a Creative http://mashe.hawksey. Commons Attribution 3.0 Unported License. CC-BY Martin Hawksey

5. Data Scientist "a business analyst who lives in California“ “someone who: wants to know what the question should be; embodies a combination of curiosity, data gathering skills, statistical and modelling expertise and strong communication skills” Adam Cooper http://blogs.cetis.ac.uk/adam/2012/04/27/analytics-and-big-data-reflections-from-the- teradata-universe-conference-2012/ This work is licensed under a Creative http://mashe.hawksey. Commons Attribution 3.0 Unported License. CC-BY Martin Hawksey

6. Background  To „visualise‟ the JISC/HEA Open Educational Resources (OER) Phase 1 & 2  Summary post with links http://bit.ly/OERVis This work is licensed under a Creative http://mashe.hawksey. Commons Attribution 3.0 Unported License. CC-BY Martin Hawksey

7. Refining Jorum/OAI Harvesting  Details of everything I‟m about to show you is here http://bit.ly/refinejorum This work is licensed under a Creative http://mashe.hawksey. Commons Attribution 3.0 Unported License. CC-BY Martin Hawksey

8. http://dspace.jorum.ac.uk/xmlui/handle/123456789/15853 This work is licensed under a Creative Commons Attribution 3.0 Unported License. CC-BY Martin Hawksey

9. This work is licensed under a Creative http://mashe.hawksey. Commons Attribution 3.0 Unported License. CC-BY Martin Hawksey

10. Google Refine and OAI-PMH This work is licensed under a Creative http://mashe.hawksey. Commons Attribution 3.0 Unported License. CC-BY Martin Hawksey

11. This work is licensed under a Creative Commons Attribution 3.0 Unported License. CC-BY Martin Hawksey

12. This work is licensed under a Creative Commons Attribution 3.0 Unported License. CC-BY Martin Hawksey

13. forEach(value.parseHtml().select("dc| creator"),v,v.htmlText()).join(",") This work is licensed under a Creative http://mashe.hawksey. Commons Attribution 3.0 Unported License. CC-BY Martin Hawksey

14. if(contains(value.toLowercase(),"univ ersity"),filter(value.toLowercase().s plit(/[- ,.;()]|(s+for+s)+/),v,contains(v, "university"))[0].trim(),if(contains( value.toLowercase(),"centre"),value.t oLowercase(),"")) This work is licensed under a Creative http://mashe.hawksey. Commons Attribution 3.0 Unported License. CC-BY Martin Hawksey

15. Reconciliation This work is licensed under a Creative Commons Attribution 3.0 Unported License. CC-BY Martin Hawksey

16. This work is licensed under a Creative Commons Attribution 3.0 Unported License. CC-BY Martin Hawksey

17. What was achieved  Jorum contains 9,502 unique records containing „ukoer‟ of which 8,859 can be reconciled against institution names  With institution name A. Can see contributions per institution B. Can get location data This work is licensed under a Creative Commons Attribution 3.0 Unported License. CC-BY Martin Hawksey

18. Combine  Pages access counts  Social share counts (very little sharing or repository records) This work is licensed under a Creative http://mashe.hawksey. Commons Attribution 3.0 Unported License. CC-BY Martin Hawksey

19. This work is licensed under a Creative Commons Attribution 3.0 Unported License. CC-BY Martin Hawksey

20. This work is licensed under a Creative Commons Attribution 3.0 Unported License. CC-BY Martin Hawksey

21. This work is licensed under a Creative http://mashe.hawksey. Commons Attribution 3.0 Unported License. CC-BY Martin Hawksey

22. This work is licensed under a Creative http://mashe.hawksey. Commons Attribution 3.0 Unported License. CC-BY Martin Hawksey

23. This work is licensed under a Creative Commons Attribution 3.0 Unported License. CC-BY Martin Hawksey

24. http://bit.ly/jorumspreadsheet http://mashe.hawksey. This work is licensed under a Creative Commons Attribution 3.0 Unported License. CC-BY Martin Hawksey

25. http://nyti.ms/c2C09A This work is licensed under a Creative Commons Attribution 3.0 Unported License. CC-BY Martin Hawksey

26. Tools/Libraries • Tools • Libraries – Google Refine – timemap.js – Google – RaphaelJS Spreadsheets – d3 – R/RStudio – SIMILE Timeline – NodeXL & Gephi – Google – Gource Visualisation This work is licensed under a Creative http://mashe.hawksey. Commons Attribution 3.0 Unported License. CC-BY Martin Hawksey

27. Data Use == Data Validation This work is licensed under a Creative http://mashe.hawksey. Commons Attribution 3.0 Unported License. CC-BY Martin Hawksey

28. Questions? Martin Hawksey @mhawksey Summary post with links http://bit.ly/OERVis This work is licensed under a Creative Commons Attribution 3.0 Unported License. CC-BY Martin Hawksey

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