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.
http://alandix.com/academic/talks/Stories-of-Flipping-Brunel-2015/
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.
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
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?
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?
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
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
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
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