Technologies for Seamless Learning Analytics

prof. dr. marcus specht

Centre for Learning Sciences and Technologies

Open Universiteit Nederland

marcus.specht@ou.nl

twitter, flickr, facebook: marcuspecht

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# 1 T H E R E A R E S E A M S I N T O D AY ’ S L E A R N I N G S U P P O R T

no sync, no br

idges

S E A M S I N L E A R N I N G S U P P O R T ( W O N G E T A L , 2 0 0 9 )

• (MSL1) Formal and informal learning;

• (MSL2) Personalized and social learning;

• (MSL3) Across time;

• (MSL4) Across locations;

• (MSL7) Combined use of multiple device types;

• …

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# 2 T R E N D S A N D O P P O R T U N I T I E S O F N E W T E C H N O L O G I E S

#lots of data and more sensors

http://quantifiedself.com/���6

wearable sensors, up

#display technology can create feedback loops ...

Goetz, T. (2011). Harnessing the Power of Feedback Loops | Magazine. wired.com. Retrieved August 22, 2011, from http://www.wired.com/magazine/2011/06/ff_feedbackloop/5/ ���7

#visualisation and LA can support personal sense making

Heer, J., Shneiderman, B. (2012). Interactive Dynamics for Visual Analysis. Communications of the ACM. Vol 55. No 04. pp. 45-54. ���8

#potenial van Learning Analytics SURF SIG GCM Study

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<  10  years >  10  years

Teacher  empowerment Teacher  empowerment

Research  &  Learning  DesignResearch  &  Learning  Design

PersonalisationPersonalisation

Feedback  &  Performance Feedback  &  Performance

Students  empowerment

Students  empowerment

Management  &  Economics

Management  &  Economics

Risks Risks

3.10 2.77

3.76 3.88

r  =  0.99

Teacher EmpowermentResearch & Design

PersonalisationStudent Empowerment

Management &Economics

Risks

Feedback & Performance

# 3 F E AT U R E S O F T E C H N O L O G I E S A N D H U M A N L E A R N I N G A N D C O G N I T I O N

H U M A N S C O N N E C T E P I S O D E S . . .

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enhanced

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Learning

Technology

Mobile, Seamless, Ubiquitous

Personalised and Context-Aware

Sensors, BigData, and Analytics

ReflectionAwareness EpisodesCuriosity ...

…

!13personal and multifunction ...

!14sensing and augmenting...

!15networked ...

!16tracked ...

fb twitter sensors

!17analyzed ...

# 4 L I N K E D D ATA A N D S E A M L E S S L E A R N I N G A N A LY T I C S

Linked Data …M E TA D ATA I S U S E D T O M A K E D ATA S PA C E S E X P L O R A B L E

!20distributed synced data ...

M U LT I - D E V I C E O U T P U T

personal and social views ...

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embedded in real world …

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dynamic artefacts ...

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real world mashups ...

# 5 S O M E T E C H N O L O G I E S F O R C O N T E X T- A W A R E , C R O S S - C O N T E X T, P E R S O N A L I Z E D , A N D F L E X I B L E O U T P U T

ARLearn Framework, VR and AR

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!

!

http://code.google.com/p/arlearn/

mixed reality ga

mes

excursies and

location-based,

mobile multi-pla

yer

ARLearn, Mozilla Badges, Signage System

http://code.google.com/p/arlearn/

multi-output,

gamification and

cross-context

support

context notific

ation and

experience sam

pling

Personal Context Notifications

Learning  Analytics  Framework

Greller,  W.  &  Drachsler,  H.  (2012).Translating  Learning  into  Numbers:  Toward  a  Generic  Framework  for  Learning  Analytics,  In:  JETS  15/3:  Special  Issue  on  Learning  Analytics  (edt.  George  Siemens)  !Drachsler,  H.,  &  Greller,  W.  (2012).  The  pulse  of  learning  analytics.  Understandings  and  expectations  from  the  stakeholders.  In  S.  Buckingham  Shum,  D.  Gasevic,  &  R.  Ferguson  (Eds.),  2nd  International  Conference  Learning  Analytics  &  Knowledge  (pp.  120-­‐129).  April,  29-­‐May,  02,  2012,  Vancouver,  BC,  Canada.

Context Indicators

Reflection Amplifiers

R E F L E C T I O N A N D D A S H B O A R D S

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performance analytics ...

S O …

• #1 There are seams between the different learning contexts, location, time, social context, …

• #2 There are opportunities with new technologies that are open, ubiquitous, context-aware, and personalized.

• … >

S O …

• #3 Seamless Learning Analytics should support ubiquitous open content access, sensor data aggregation, adaptation (to context and person), and flexible aggregation, visualization and output indicators (ambient displays).

T H A N K Y O U !

M . M . S P E C H T