pushing the mooc envelope with learning analytics
DESCRIPTION
How can Learning Analytics be used to bring about the true revolution traditionally assumed for MOOCs? With audiences in the thousands of users, the key is massive personalization, and Learning Analytics privide an ideal paradigm for this.TRANSCRIPT
Pushing the MOOC envelopewith Learning Analytics
Seminar on the Future of MOOCsand Digital LibrariesFukuoka, 24 February 2013
Abelardo Pardo (@abelardopardo)The University of Sydney
www.slideshare.net/abelardo_pardo
thisisbossiflickr.com
Abelardo Pardo Pushing the MOOC envelope with Learning Analytics 2
DarrelB
irkettFlickr
Associate Head of Teaching andLearning
Two coursesGrad/Undergrad
Active learning
Use of technology
Tech to empowerindividuals andcommunities
Behavioral analytics
User validation
Abelardo Pardo Pushing the MOOC envelope with Learning Analytics 3
Sim
onovflickr.com
Where: MOOC Scenario
What: Challenges
How: Solutions
Abelardo Pardo Pushing the MOOC envelope with Learning Analytics 4
Sim
onovflickr.com
Where: MOOC Scenario
MOOCsCourse in a stadium
Abelardo Pardo Pushing the MOOC envelope with Learning Analytics 5
IAN
RA
NS
LEY
DE
SIG
N+
ILLUS
TRATIO
Nflickr.com
Abelardo Pardo Pushing the MOOC envelope with Learning Analytics 6
Em
orseflickr.com
Overcome initialsurprise!
(Guthrie, 2012)
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Daikrieg
flickr.com
Why should we be impressedthat an online course can reach100,000 students at once?
Abelardo Pardo Pushing the MOOC envelope with Learning Analytics 8
danceintheskyflickr.com
MOOCs changeinteraction radically
Some interactions do not scale!
Deep and meaningful formal learning occurs ifone of the interactions is at a high level
Abelardo Pardo Pushing the MOOC envelope with Learning Analytics 9
(Anderson, 2003)
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nateOne
flickr.com
Say Hi!
1,200emails
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Curiousbut...
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paddynapperFlickr.com
Discussion board
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HikingA
rtist.comFlickr.com
Massive activity misfit!
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Secretlondon123
Flickr.com
Ideal for polls
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Sim
onovflickr.com
Where: MOOC Scenario
What: Challenges
Size vs Interactivity
Number of students
Leve
l of in
tera
ctio
n
Trivialcourse Low effort
Intensecourse
Higheffort MOOCs
xMOOCs
cMOOCs
Abelardo Pardo Pushing the MOOC envelope with Learning Analytics 16
Transition toMOOC easierwhen lowinteractivity
Size vs Tutoring
Number of students
Tuto
ring inte
nsi
ty
Trivialcourse Low effort
Intensecourse
Higheffort MOOCs
ManuallyUnfeasible
TechnologicallyChallenging
Lear
nin
g A
nal
ytic
s
Abelardo Pardo Pushing the MOOC envelope with Learning Analytics 17
Technologicalintervention isessential!
Scope vs Automation
Level of automation
Sco
pe
of in
terv
ention
Intelligent Tutoring Systems
MOOCs
Lear
ning
Ana
lytic
s
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LearningAnalytics allowmore genericinterventions
Abelardo Pardo Pushing the MOOC envelope with Learning Analytics 19
Chandra
Marsono
Flickr.com
Massive automaticassessment
Abelardo Pardo Pushing the MOOC envelope with Learning Analytics 20
JoeFlickr.com
Early drop-outdetection
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dklimke
Flickr.com
Erraticengagement
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Quinn.A
nyaFlickr.com
FocusAttention
Connect priorknowledge
Process, digest,summarize, apply
Feedback
Interaction with others(Svinicki, 2012)
Abelardo Pardo Pushing the MOOC envelope with Learning Analytics 23
Sim
onovflickr.com
Where: MOOC Scenario
What: Challenges
How: Solutions
Abelardo Pardo Pushing the MOOC envelope with Learning Analytics 24
WernerK
unzFlickr.com
(Campbell, De Blois, Oblinger 2007)
Collect
Report
Predict
Act
Refine
The five stepsof analytics
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Abelardo Pardo Pushing the MOOC envelope with Learning Analytics 26
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Abelardo Pardo Pushing the MOOC envelope with Learning Analytics 28
burge5kFlickr.com
Microscopicview of learning
events
A clearly identifiedenvironment within
your computer
Abelardo Pardo Pushing the MOOC envelope with Learning Analytics 29
Riccardo
CecchiFlickr.com
(Romero-Zaldívar et al., 2012)
Track App Usage
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kvnmclFlickr.com
Collect interactionevents
Automatic discoveryof complementarylearning resources
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Sean
Dreilingerflickr.com
(Romero-Zaldívar et al., 2011)
Unobtrusive Collection
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Embedded Question
EffortEffortCollect feedback
(Pardo et al., 2012)
Monitor Writing
Abelardo Pardo Pushing the MOOC envelope with Learning Analytics 33
(Calvo et al., 2011)
Measure Engagement
Abelardo Pardo Pushing the MOOC envelope with Learning Analytics 34(Liu et al., 2013, To appear)
Abelardo Pardo Pushing the MOOC envelope with Learning Analytics 35
EleafFlickr.com
Automatic Question Generation
What evidence is provided to ...?
What are the strength andlimitations of ...?
(Liu et al., 2010)
Facial Expressions
Detect emotions
Abelardo Pardo Pushing the MOOC envelope with Learning Analytics 36(Monkaresi et al., 2012)
Abelardo Pardo Pushing the MOOC envelope with Learning Analytics 37
robpatrickFlickr.com
MassivePersonalization of
Interactions
Abelardo Pardo Pushing the MOOC envelope with Learning Analytics 38
Mary
Witzig
Flickr.comMassively Personalized Online Open Course
Abelardo Pardo Pushing the MOOC envelope with Learning Analytics 39
ribarnicaFlickr.com
Massive Hyper-Personalization“The Snowflake Effect”
(Duval & Hodgins, 2006)
Personalize Everything
Which notifications?Work individually? Collaboratively?Reduce interaction to a small groupHierarchical summaries of contributions
Abelardo Pardo Pushing the MOOC envelope with Learning Analytics 40
woody1778a
Flickr.com
Abelardo Pardo Pushing the MOOC envelope with Learning Analytics 41
pylbugFlickr.com
Learning Analytics
Pushing the MOOC envelopewith Learning Analytics
Seminar on the Future of MOOCsand Digital LibrariesFukuoka, 24 February 2013
Abelardo Pardo (@abelardopardo)The University of Sydney
www.slideshare.net/abelardo_pardo
thisisbossiflickr.com
ReferencesDogh Guthrie, 2012.Jump Off the Coursera WagonThe Chronicle of Higher Education, 17 December 2012
T. Anderson, 2003.Getting the Mix Right Again: An updated and theoretical rationale for interaction Equivalency of InteractionThe International Review of Research in Open and Distance Learning, 4 (2)
Academic AnalyticsCampbell J., DeBlois P., Oblinger D.EDUCAUSE White paper, 2007
MOOCs: What Part of Learning Goes on Where and How?Marilla SvinickiThe National Teaching and Learning Forum, Dec, 2012http://ntlf.com/sample-articles/moocs-what-part-of-learning-goes-on-where-and-how.aspx
The signal projectPurdue Universityhttp://www.itap.purdue.edu/studio/signals/Last accessed February 2013
Blackboard AnalyticsBlackboard Inc.http://www.blackboard.com/Platforms/Analytics/Overview.aspxLast accessed February 2013
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References (II)Desire2Learn AnalyticsDesire2Learnhttp://www.desire2learn.com/products/analytics/Last accessed February 2013
Romero-Zaldívar, V.A., Crespo García, R., Burgos, D., Delgado Kloos, C., Pardo, A., 2012Automatic Discovery of Complementary Learning ResourcesEuropean Conference on Technology Enhanced Learning, 2011
Romero-Zaldívar, V.A., Pardo, A., Burgos, D., Delgado Kloos, C., 2012Monitoring Student Progress Using Virtual Appliances: A Case StudyComputer & Education, 58(4):10580–1067, 2012
Pardo, A., Pérez-Sanagustín, M., Parada G., H., Leony, D. 2012Flip with CareSoLAR Southern Flare Conference, November, 2012
Calvo, R., O’Rourke, S.T., Jones, J., Yacef, K., Reimann, P., 2011Collaborative Writing Support Tools on the CloudIEEE Transactions on Learning Technologies, 4(1):88–97
Liu M., Calvo, R.; Pardo, A., 2013Visualizing the effect of actions in personal informatics systemsWorkshop on Personal Informatics, CHI’13
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References (III)
Liu M., Calvo, R.; Rus, V., 2010Automatic Question Generation for Literature Review Writing SupportIntelligent Tutoring Systems 2010
Monkaresi, H., Hussain, M. S., Calvo, R., 2012A dynamic approach for detecting naturalistic affective states from facial videos during HCIAustralasian Joint Conference on Artificial Intelligence, Sydney, Australia. LNAI, Springer 2012, pp.170-181
Duval, E., Hodgins, W., 2006Standardized Uniqueness: Oxymoron or Vision of the Future?IEEE Computer, 32(3):96-98
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