International trends in learning analytics (SAHELA conference)
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International trends in learning analytics was presented by Dr. Doug Clow of the Open University UK. The Open University has over 200,000 students, 5,000 tutors, and 1,000 academic staff. It analyzes over 1 billion views and 3 million transactions per day. Learning analytics is defined as measuring, collecting, analyzing, and reporting data about learners and contexts to understand and optimize learning. International activities in learning analytics include conferences, workshops, and publications. Trends from the 2014 Learning Analytics Summer Institute included a focus on privacy, ethics, readiness, technology, research issues, and new contexts like MOOCs.
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International trends in learning analytics (SAHELA conference)
- 1. International trends in learning analytics Dr Doug Clow Institute of Educational Technology The Open University, UK
- 2. The Open University • Largest university in the UK • 200,000 students • > 5,000 tutors • > 1,000 academic staff • Supported open learning • OpenLearn, YouTube, iTunesU, FutureLearn Milton Keynes
- 3. At scale, each year • ~400 courses • 200,000 students • > 1 million assignments • > 1 billion views of OU/BBC coproductions • > 3 million Moodle transactions per day Photo (cc) Marieke IJsendoorn-Kuijpers http://www.flickr.com/photos/mape_s/333862026//
- 5. 1. learning analytics 2. international activities 3. trends from LASI 14
- 7. What is learning analytics? • the measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimising learning and the environments in which it occurs – First International Conference on Learning Analytics And Knowledge (LAK11), Banff, Alberta, Feb 27-Mar 1, 2011 Photo (CC)-BY Cris: http://flickr.com/photos/chrismatos/6917786197/
- 8. “collecting traces that learners leave behind and using those traces to improve learning” - Erik Duval http://erikduval.wordpress.com/2012/01/30/learning-analytics- and-educational-data-mining/ Photo public domain: http://commons.wikimedia.org/wiki/File:DESYNebelkammer.jpg
- 9. “feeding back the data exhaust” Big Data in Education Photo (CC)-BY Iain Watson http://www.flickr.com/photos/dagoaty/3329699788/
- 11. • Predictive modeling, datamining (Blackboard) • Place students in one of three risk groups => traffic light / signal / robot • Trigger for intervention emails • Dramatic retention improvements • Consistent grade performance improvement
- 13. • LAK conferences • LASI workshops • Flare local meetings • Storm PhD training • Journal of LA • … and more! www.solaresearch.org
- 14. International Educational Data Mining Society Annual conference IEDMS Journal of EDM www.educationaldatamining.org/
- 15. Learning Analytics Masters Program (LAMP) Open Learning Analytics (OLA) Photo (CC)-BY J. Aaron Farr on Flickr https://www.flickr.com/photos/jaaronfarr/2372892211
- 16. www.laceproject.eu Learning Analytics Community Exchange (FP7) • Evidence Hub • Events: SoLAR Flare, 24 Oct 14 • Publications, briefings, webinars
- 17. 3. trends from LASI 14
- 18. Public domain photo by Mancala http://en.wikipedia.org/wiki/File:HarvardYard.jpg
- 19. Photo (CC)-BY-NC-SA Trevor Patt on Flickr https://www.flickr.com/photos/trevorpatt/9978972256
- 20. • Privacy • Data protection • Ethics • Transparency Glasswinged butterfly, ? Greta oro Principles Photo (CC)-BY-NC-ND by Greg Foster on Flickr http://www.flickr.com/photos/gregfoster/3365801458/
- 21. Readiness • Policy, leadership, governance • Learning analytics professionals & teams – Multi-skilled Photo (CC)-BY Blair Gannon on Flickr https://www.flickr.com/photos/blairgannon/14223294295
- 22. Technology • Systems for implementation • Analysis tools and techniques • Machine learning Photo (CC)-BY-NC-SA Moon Lee on Flickr https://www.flickr.com/photos/imagezen/65199660
- 23. Research issues • Theory vs data • Learning sciences • Educational research Photo (CC)-BY Karen Roe on Flickr http://www.flickr.com/photos/karen_roe/4916422687/
- 24. New contexts • Blended learning • Informal learning • MOOCs Massive Open Online Courses cc licensed ( BY) flickr photo by Randy Robertson: http://www.flickr.com/photos/randysonofrobert/337922766/
- 25. final words
- 26. catnip for senior managers Photo (CC)-BY Dylan Ashe https://www.flickr.com/photos/ackook/3929957511/
- 27. Photo (CC)-BY kaybee07 on Flickr https://www.flickr.com/photos/kurtbudiarto/7026555821
- 28. Thanks to: People: •OU Learning Analytics: IET Student Statistics and Survey Team, Gill Kirkup and the other Data Wranglers, Kevin Mayles, Belinda Tynan, Simon Buckingham Shum, Rebecca Ferguson, Bart Rientes, Sharon Slade, many others •LACE: Rebecca Ferguson, Simon Cross, Michelle Bailey, Rebecca Wilson, Evaghn De Souza, project partners. •The learning analytics community, including SoLAR, IEDMS, those I’ve met at LAK and LASI Funders: • LACE: European Commission 619424-FP7-ICT-2013-11
- 29. Doug Clow @dougclow dougclow.org doug.clow@open.ac.uk This work is licensed under a Creative Commons Attribution 3.0 Unported License
- 30. cc licensed ( BY ) flickr photo by David Goehring: http://flickr.com/photos/carbonnyc/33413040/
Notas del editor
- Like Unisa, but smaller (funding cuts) and more British
- Transactions figure from 2011! Second-largest Moodle installation in the world. We are big, but we care.
- Better than Horizon Report or Gartner or your money back.
- Data mining, academic analytics, learner analytics – focus here is on the learning, not the management and administration of learning
- Photo: Cloud Chamber at the German Electron Synchrotron DESY
- Our data isn’t big. Most fits in Excel! Small data = Excel, Medium = laptop with R or other stats, Big = need special servers/cloud services
- Without interventions: still good stuff: computer science, educational research, business intelligence But only LA if fed back. Speed and length of cycles: instant feedback as you learn, through to govt policy
- Concrete example
- LAMP: Shared curriculum development. Online. OLA: open source learning analytics products and services. Interop …
- Personal influence!
- LASI14, Harvard. Cambridge, Mass. Old, beautiful buildings in leafy surroundings.
- Also some not so old & beautiful buildings, including the Gutman Library where we were. Some of the themes – personal view.
- Data protection – longstanding EU legislation; POPI Protn of Persl Info Act here newer. Ethics vast, complex, tricky. 1% chance succeed. Vs ignoring info could help success. Ethics critical path. Sharon Slade leading at OU, tomorrow keynote. Transparency – to learners, but to the outside. Shared processes.
- Statistical understanding. OU has senior leadership, PVC(Academic) championing, VC keen. Who do you need to do this stuff? Quantitative skills. But also educational understanding. Systems integration. Communication. Data scientist is a statistician with a Mac.
- Enterprise level, Data Warehousing. Dashboards. R, Python – sexy, open; SPSS, SAS, widespread but closed. Excel! Machine learning. Want to understand LA, learn about machine learning. Predictions, classifiers, recommenders.
- Futurelearn!
- Senior managers care about bums on seats and money. They’re paid to. The good ones – most of them – also care about other things. You care about teaching and learning. Get involved!
- There’s a lot that looks impressive, but less elegant beneath the surface. Swan metaphor Learning analytics is a new field.
- Big thanks in small fonts