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Stories of-flipping-brunel-2015


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Talk at Brunel University, 7th October 2015.

We are in the midst of a time of change in higher education, it is hard to distinguish hype from innovation. Based on my own experience and the literature I will explore aspects of pedagogy, economics and data around the growing trend towards 'flipped class' teaching.

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Stories of-flipping-brunel-2015

  1. 1. Stories of Flipping: + Data Matters Alan Dix Talis & University of Birmingham
  2. 2. about me …
  3. 3. University of Birmingham Tiree Tiree Tech Wave 22-26 October 2015
  4. 4. today I am not talking about … • intelligent internet interfaces • visualisation and sampling • situated displays, eCampus, small device – large display interactions • fun and games, virtual crackers, artistic performance, slow time • creativity and Bad Ideas • modelling dreams and regret and the emergence of self …
  5. 5. … or even lots of lights http:/
  6. 6. I am talking about … Flipping – costs of online and reuse of MOOCs – five shades of flipping – learning analytics and the academic life Data Matters (if time) – long tail of small data, REF, open data islands, etc.
  7. 7. five shades of flipping
  8. 8. loads of experience … early adopter use of web in teaching & teaching about learning technology textbook author online material even a MOOC
  9. 9. but never flipped
  10. 10. why flip? R&D reuse MOOC materials Talis lighthouse trial
  11. 11. why flip? R&D reuse MOOC materials Talis lighthouse trial
  12. 12. online HCI course ran early 2013 to gain experience with ‘MOOCs’ and reusable materials Human–Computer Interaction
  13. 13. HCIcourse – content talk-over slides video + additional resources
  14. 14. HCIcourse – experience low-quality video is still a lot of work attrition: 1000s of interest 100+ formal sign up 2 completed
  15. 15. HCIcourse – legacy loads of videos course now hosted at OER site
  16. 16. why flip? R&D reuse MOOC materials Talis lighthouse trial
  17. 17. lighthouse pilot universal player micro-analytics … individual course resource student
  18. 18. why flip? pedagogy Pros better use of face-to-face time greater student autonomy more flexible learning etc., etc., etc., … Cons lots more work  visibiity & control will they do it? panic!!!!!!
  19. 19. why flip? pedagogy Pros better use of face-to-face time greater student autonomy more flexible learning etc., etc., etc., … Cons lots more work  visibiity & control will they do it? panic!!!!!!
  20. 20. autonomous learning? Programm#/media/File:Erasmus_party.JPG
  21. 21. starting small … Autumn 2014 course (& 2015 starting now) mix of UG3 & MSc portion of course (4 weeks) mixing video with face-to-face Spring 2015 course masters students only single session
  22. 22. different mixes basics + integration preparatory videos on ‘basics’ followed by integrative lecture (chalk & talk!) 2 fully flipped videos followed by discoursive F2F videos followed by group discussions 2 part & part all material on video, some also taught in class N.B. noticable attendance fall-off when told in advance! 70 students 20 students
  23. 23. … a quick dip into the past
  24. 24. p-learning and e-learning
  25. 25. p-learning (physical learning) • lectures • tutorials and labs (20-30) • small groups tutorials ? • individual tutorials
  26. 26. p-learning e-learning • lectures web • labs ? • tutorials bulletin boards & chat • individual one-to-one email
  27. 27. deconstruction and reconstruction p-learning e-learning deconstruction reconstruction
  28. 28. deconstruction find the real objectives • lecture • information, motivation, demonstration • group tutorial • collaboration, individual feedback • lab + personal experience, physical materials
  29. 29. reconstruction • take delivery ecology e-learning: web, CD-ROM, video, email, webcam, bulletin boards, chat, streaming video/audio p-learning: weekend course, monthly evening meeting, summer camp, paper materials and books m-learning: PDA, mobile phone, WAP, SMS, 3G • match with objectives e.g. information -> web good motivation? … face to face sessions tutorial feedback?
  30. 30. online costs
  31. 31. reuse and online ’content’ online ‘content delivery’: senior mgt pressure since 1990s principally for cost saving! reuse: LOs, SCORM, Tin-Can API we all know it’s good  in HE use still limited Jorum
  32. 32. every one loves a MOOC (well they did in 2013!) but what does it cost?
  33. 33. effort: Glasgow University FutureLearn two courses: Right vs Might 360 hours academic + 800 hrs learning technologist (development only) 2.5 hours of video + supporting resources 656 participants (first run) Genomics 2236 hours academic (development only) 6 hours video + supporting resources 747 participants (first run) Source: Building and Executing MOOCs: A practical review of Glasgow’s first two M J. Kerr, S. Houston, L. Marks, A. Richford (2015)
  34. 34. comparison • MOOCs – 400 hours development time per hour video – 700 participants per run (time amortised) – £29 statement of participation (~15% takeup) • Traditional classroom – 2–4 hours preparation per hour lecture – 50-200 students per lecture (time repeated) – £9000 fees (for ~ 200-300 hours lectures)
  35. 35. bottom line MOOCs vs classroom 10 times as many students 100 times the effort 1/30 payment / student–hour
  36. 36. other estimates? $39K to $325K per MOOC $74-$272 per completer Source: Resource Requirements and Costs of Developing and Delivering MOOCs. Hollands and Tirthali (2014) Udacity ~ $200K per course EdX ~ $250K design + $50K per run Source: Why MOOCs Aren't So Cheap ... for Colleges. Fiscal Times (2013) High quality video ~ $4K per hour (1) ~ $2.5K–10K per minute (2) Source: (1) MOOCs: Expectations and Reality Hollands and Tirthali (2014) (2) What does a corporate web video cost? Fox (2010)
  37. 37. benefits brand awareness (overseas student recruitment) development consultancy (platform providers) democratisation of education (… but who pays?) sustainable?
  38. 38. reuse in face to face? amortise over online and F2F delivery MOOC materials: – self-contained units – learner-centric design ? Issues of level (most MOOCs pretty intro)
  39. 39. small is beautiful video length: often suggested 4 mins or even 2 mins smaller resources improve engagement (Ferriday) we saw 10 mins OK  but 20 mins too long  => need better ways to create, edit and manage smaller videos
  40. 40. small things matter sharing portions not just whole videos => added end as well as start times to Player need better audio fade-in – fade-out simple sequencing units vs narrative?
  41. 41. learning analytics
  42. 42. learning analytics …. not just traffic lights!
  43. 43. analytics – who read/viewed what typically about 1/3 watch everything, 1/3 some, 1/3 none at all! used stats to ‘encourage’ students in class N.B. did not look at individual student analytics students did not seem phased by this level of analytics
  44. 44. analytics – how much journal paper PDF recommended reading most students just read beginning in class explained structure of paper
  45. 45. world organisational social & political context direct interaction data visualisation visual analytics the big picture decision action processing
  46. 46. simple model: actors, agents and events individual resources structures & courses repository ? ? ? ? academic life student life learning support systems creation & reuse delivery peer interaction community of practice feedback tutor – student interactions analytics
  47. 47. analytics and action action ? ? ? recognise issues current course future course allow Macawber management analytics visualisation automatic drivers capability value career development resources time course materials communication
  48. 48. time frames for learning analytics days and hours email, during lectures and labs, student meetings, gaps week preparing for teaching, exercises months/mid-semester reporting points, staff meetings, cohort/student progress end of semester/term/year exams, exam boards, course review, start of semester/term/year preparing for new courses or re-runs, rollover! years new courses, professional development, appraisal, promotion
  49. 49. main points so far many different ways to use online materials – fully flipped, remedial, extension, … online is costly – reuse essential … but may need new tools learning analytics – new opportunities from detailed LA … but must fit with academic work patterns
  50. 50. data matters
  51. 51. REF analysis
  52. 52. REF data loads in the public domain  … especially computing – ACM area codes, Morris’ sub-area profiles citation analysis and metrics – bad for assessment (volume, special cases) … but good to validate assessment
  53. 53. Citation Analysis my own analysis (all public domain data) large apparent sub-area and institutional bias factor of five to ten! may be due to SP11’s unusual methods HEFCE’s report gender differences in Computing femail staff 30% less likely to get 4* … may be implicit bias from the other effects
  54. 54. long tail of small data
  55. 55. Big Data everyone is talking about it Twitter, Google, Facebook, NSA, universities, … and funding Big Data does it with MapReduce Semantic Data does it with RDF
  56. 56. the long tail size of data set a few very large data sets e.g. Twitter, streams, Open Govt., OS, geonames, dbpedia the small data of ordinary life: from local bus timetables to squash club league tables
  57. 57. stories of small data … Walking Wales Learning analytics Open Data Islands and Communities Musicology