MOOCs and the Funnel of Participation
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Presentation at LAK13, the Third Conference on Learning Analytics and Knowledge, Leuven, Belgium, April 2013. Full paper and other details at doug.clow/mooc-funnel
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MOOCs and the Funnel of Participation
- 1. MOOCs and the Funnel of Participation dougclow.org/mooc-funnel Doug Clow, Institute of Educational Technology, The Open University, UK Third International Conference on Learning Analytics and Knowledge LAK13, April 2013, Leuven
- 2. Overview • MOOC dropout • This is not new • Here is some actual empirical data on a MOOC • Dangerous aim: To change the way you think about MOOCs and dropout. With a funnel. Photo (cc) Nina Hale http://www.flickr.com/photos/94693506@N00/614751836/
- 4. Just say no! to antediluvian, ineffective, unsophisticaed epistemologies of pedagogical ontology
- 5. “Fonske” Fons sapientiae Fountain of Knowledge Photo (cc) Dogfael http://www.flickr.com/photos/dogfael/3143968066/
- 6. Photo (cc) Dogfael http://www.flickr.com/photos/dogfael/3143968066/
- 7. Cartoon (c) Oglaf http://oglaf.com/fountain-of-doubt/
- 8. • What’s a MOOC? xMOOC vs cMOOC • “Officially the buzzword of 2012” • Field moving very fast • Learning analytics on MOOCs is hard: – Technical challenges – Theoretical challenges – Philosophical challenges – Resource challenges Honeybees Apis mellifera Photo (cc) David Goehring http://www.flickr.com/photos/carbonnyc/5041997785/
- 10. Main findings of MOOC research • People drop out • People drop out a lot • More research required • People really do drop out a lot Photo (cc) jeroen bennink http://www.flickr.com/photos/jeroenbennink/2355768494/
- 11. State of the art in MOOC Completion Rates Nov 2012 CCK08 PLENK2010 MITx Coursera Circuits & Software Electronics Engineerin g Registered 2,200 1,641 150,000 50,000 Completed At least 16 40-60 7,157 3,500 ‘active’ Competion Not Not 7% 7% rate definable definable Photo (cc) Seth Tisue http://www.flickr.com/photos/tisue/254308538/
- 12. MOOC Completion Rates April 2013 http://www.katyjordan.com/MOOCproject.html
- 13. Awareness Interest Desire the marketing funnel Purchase
- 14. Awareness Registration Activity the funnel of participation Progress
- 15. steep drop off from one stage to the next funnel of participation = + highly unequal participation pattern
- 16. it’s not a power law
- 17. iSpot Cloudworks openED Visits 1,100,000 275,000 30,000 Unique visitors 390,000 165,000 15,500 (35%) (60%) (52%) Registrations 21,000 5,239 1,429 (5%) (3%) (9%) Contributors 9,000 1,750 198 (43%) (33%) (14%) Data from respective site launch to 7 November 2012
- 18. iSpot Cloudworks openED Visits 1,100,000 275,000 30,000 Unique visitors 390,000 165,000 15,500 (35%) (60%) (52%) Registrations 21,000 5,239 1,429 (5%) (3%) (9%) Contributors 9,000 1,750 198 (43%) (33%) (14%) Data from respective site launch to 7 November 2012
- 19. • http://www.open-ed.eu • Free, open, online, OER, CC BY-SA • Seven EU partners • Three presentations, 2009-2012 • Joomla, email, IRC, Elluminate • Explored business models, found none
- 20. Log plot of the number of visits to openED per user, ranked by number of visits.
- 21. it’s not a power law
- 22. Log plot of the number of forum posts on openED per user, ranked by number of forum posts
- 23. it’s not a power law
- 24. Visits vs forum posts made by individual openED users R = 0.86, p < 0.0001
- 25. Distance / Elite Mass open / university university online MOOCs university Representative completion rate ~ 90% ~ 60% ~ 35% < 10% Photo (cc) Walt Hubis http://www.flickr.com/photos/walthubis/4346378552/
- 26. steep drop off from one stage to the next funnel of participation = + highly unequal participation pattern
- 27. Put your thinking funnel on • Think less about total dropout • Think more about why participation reduces at each stage • Think about patterns of participation • Benchmark whether it’s a problem • Pour more in the top, or widen the funnel Photo (cc) Tom Bayly http://www.flickr.com/photos/tombayly13/6006166585/
- 28. Thanks for support from: •James Aczel, Simon Cross, •openED partners and learners • everyone who gave me data • European Commission funding for openED project 505667-LLP-1-2009-1-PT-KA3-KA3MP Photo (cc) wales_gibbons
- 29. Doug Clow @dougclow doug.clow@open.ac.uk dougclow.org/mooc-funnel This work is licensed under a Creative Commons Attribution 3.0 Unported License
Editor's Notes
- I’m following a really great paper, and a really funny person. And I’m standing between you and leaving. We’re all tired. So I’ll be animated and flash lots of things past you really quickly and maybe we can have some talk over beer.
- First presentation had more data. Although the MOOC was more an OOC – only 200 weren’t disengaging.
- 600 year old idea like KU Leuven
- He’s reading about happiness – and it’s a mathematical formula. As we all know, great mathematics gives great happiness.
- Fountain of Doubt
- Technical The diversity of online tools often employed can make it hard to collect and process data; the disconnection from formal educational systems means that much useful data - such as demographics, previous experience, other courses being studied, etc - is unavailable. Theoretical To date, MOOCs have not led directly to the award of credit, so analytics in these terms is problematic: endpoints, progress and feedback are different. Philosophical For connectivist MOOCs, the idea of defining learning endpoints ahead of time, let alone tracking and measuring progress towards them, is anathema. Resource An important factor in the rapid spread of MOOCs is their low cost base: this means there is far less resource available per student for analytics activities – and, more importantly, far less for human mediation of analytics feedback
- Things have changed in last four/five months – FutureLearn is new. A word from my sponsors. New. British accents. Pedagogy. Tell us how to do it.
- This slide has become outdated during the course of this session.
- This *was* the state of the art.
- One of our graduate students has done the job properly. The scale only goes up to 20%.
- Buy a degree gag Big drop each time
- Drop off each time
- Highly unequal, steeply unequal. A few people do lots, lots of people do a little. It can be exponential fall off – or steeper than that. But IT’S NOT A POWER LAW. You need a lot of data.
- Three examples. See the drop at each stage.
- Compare those to 7% dropout … but this is the people who started at all.
- Steep drop off, highly unequal. A few students visiting thousands of times, most visit a few times … but …
- Again, one or two posted hundreds of forum posts., hundreds posted once. (this is starting new threads)
- This took so much effort to make – no way should it have been so hard to collate visit data to forum posts. But it was a bloody nightmare. And then I chopped it from my paper for space reasons. So just look at it for a minute, in honour of all the work that went in to it. But it tells us little so we move on.
- Stanford/Oxford/MIT. Community college, post-92. OU, U Phoenix. The traditional universities – mass, distance/open/online - are doing something right that MOOCs are not doing. All that work on student support is not wasted. Commitment too. We can’t not care about drop out.
- But not a power law!