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Stories of Flipping:
+ Data Matters
Alan Dix
Talis & University of Birmingham
http://alandix.com/
about me …
University of
Birmingham
Tiree
Tiree Tech Wave
22-26 October 2015
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
…
… or even lots of lights
http:/www.hcibook.com/alan/projects/firefly/
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.
five shades of
flipping
loads of experience …
early adopter
use of web in teaching
&
teaching about learning
technology
textbook
author
online material
even a MOOC
but never flipped
why flip? R&D
reuse MOOC materials
Talis lighthouse trial
why flip? R&D
reuse MOOC materials
Talis lighthouse trial
online HCI course
ran early 2013
to gain experience
with ‘MOOCs’
and reusable
materials
Human–Computer
Interaction
HCIcourse – content
talk-over slides video
+ additional resources
HCIcourse – experience
low-quality video
is still a lot of work
attrition:
1000s of interest
100+ formal sign up
2 completed
HCIcourse – legacy
loads of videos
course now hosted
at OER site
interaction-design.org
why flip? R&D
reuse MOOC materials
Talis lighthouse trial
lighthouse pilot
universal player
micro-analytics …
individual course
resource
student
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!!!!!!
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!!!!!!
autonomous learning?
http://de.wikipedia.org/wiki/Erasmus-
Programm#/media/File:Erasmus_party.JPG
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
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
… a quick dip into
the past
p-learning and e-learning
p-learning
(physical learning)
• lectures
• tutorials and labs (20-30)
• small groups tutorials ?
• individual tutorials
p-learning e-learning
• lectures web
• labs ?
• tutorials bulletin boards & chat
• individual one-to-one email
deconstruction and reconstruction
p-learning
e-learning
deconstruction reconstruction
deconstruction
find the real objectives
• lecture
• information, motivation, demonstration
• group tutorial
• collaboration, individual feedback
• lab
+ personal experience, physical materials
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?
online costs
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
https://pixabay.com/en/headstone-cemetery-grave-graveyard-312540/
http://iwantmyanime.deviantart.com/art/Stork-Commission-180796355
every one loves a MOOC
(well they did in 2013!)
but what does it cost?
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)
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)
bottom line
MOOCs vs classroom
10 times as many students
100 times the effort
1/30 payment / student–hour
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)
benefits
brand awareness (overseas student recruitment)
development consultancy (platform providers)
democratisation of education (… but who pays?)
sustainable?
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)
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
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?
learning analytics
learning analytics ….
not just traffic lights!
http://en.wikipedia.org/wiki/Traffic_light#/media/File:LED_Traffic_Light.jpg
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
analytics – how much
journal paper PDF
recommended reading
most students just
read beginning
in class explained
structure of paper
world
organisational
social & political
context
direct
interaction
data visualisation
visual analytics the big picture
decision
action
processing
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
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
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
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
data matters
REF analysis
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
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
long tail of small data
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
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
stories of small data …
Walking Wales
Learning analytics
Open Data Islands and Communities
Musicology
Stories of-flipping-brunel-2015

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Stories of-flipping-brunel-2015

  • 1. Stories of Flipping: + Data Matters Alan Dix Talis & University of Birmingham http://alandix.com/
  • 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. … or even lots of lights http:/www.hcibook.com/alan/projects/firefly/
  • 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.
  • 8. loads of experience … early adopter use of web in teaching & teaching about learning technology textbook author online material even a MOOC
  • 10. why flip? R&D reuse MOOC materials Talis lighthouse trial
  • 11. why flip? R&D reuse MOOC materials Talis lighthouse trial
  • 12. online HCI course ran early 2013 to gain experience with ‘MOOCs’ and reusable materials Human–Computer Interaction
  • 13. HCIcourse – content talk-over slides video + additional resources
  • 14. HCIcourse – experience low-quality video is still a lot of work attrition: 1000s of interest 100+ formal sign up 2 completed
  • 15. HCIcourse – legacy loads of videos course now hosted at OER site interaction-design.org
  • 16. why flip? R&D reuse MOOC materials Talis lighthouse trial
  • 17. lighthouse pilot universal player micro-analytics … individual course resource student
  • 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. 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!!!!!!
  • 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. 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. … a quick dip into the past
  • 25. p-learning (physical learning) • lectures • tutorials and labs (20-30) • small groups tutorials ? • individual tutorials
  • 26. p-learning e-learning • lectures web • labs ? • tutorials bulletin boards & chat • individual one-to-one email
  • 28. deconstruction find the real objectives • lecture • information, motivation, demonstration • group tutorial • collaboration, individual feedback • lab + personal experience, physical materials
  • 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.
  • 32. 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 https://pixabay.com/en/headstone-cemetery-grave-graveyard-312540/ http://iwantmyanime.deviantart.com/art/Stork-Commission-180796355
  • 33. every one loves a MOOC (well they did in 2013!) but what does it cost?
  • 34. 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)
  • 35. 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)
  • 36. bottom line MOOCs vs classroom 10 times as many students 100 times the effort 1/30 payment / student–hour
  • 37. 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)
  • 38. benefits brand awareness (overseas student recruitment) development consultancy (platform providers) democratisation of education (… but who pays?) sustainable?
  • 39. 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)
  • 40. 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
  • 41. 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?
  • 42.
  • 44. learning analytics …. not just traffic lights! http://en.wikipedia.org/wiki/Traffic_light#/media/File:LED_Traffic_Light.jpg
  • 45. 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
  • 46. analytics – how much journal paper PDF recommended reading most students just read beginning in class explained structure of paper
  • 47. world organisational social & political context direct interaction data visualisation visual analytics the big picture decision action processing
  • 48. 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
  • 49. 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
  • 50. 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
  • 51.
  • 52. 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
  • 53.
  • 56. 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
  • 57. 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
  • 58.
  • 59. long tail of small data
  • 60. 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
  • 61. 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
  • 62. stories of small data … Walking Wales Learning analytics Open Data Islands and Communities Musicology