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Applying Quantified Self Approaches
to Support Reflective Learning
V. Rivera-Pelayo, V. Zacharias, L. Müller, and S. Braun
FZI Research Center for Information Technologies, Karlsruhe, Germany
LAK Conference 2012 – Vancouver, Canada
30th April 2012
Agenda
Introduction
Background
Theoretical: Reflective Learning
Pragmatical: The Quantified Self
Motivation
A Framework to Apply QS Approaches to support Reflective Learning
Tracking Cues
Triggering
Recalling and Revisiting Experiences
Conclusions
09.05.2012 © FZI Forschungszentrum Informatik 2
Learn by observing others and from experiences
Support learning-on-the-job and experience sharing
Learning by reflection on observed practices and collected data
Focus on acquisition of tacit knowledge
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Reflective Learning at Work
http://mirror-project.eu
Reflective Learning
Returning to and evaluating past work performances and personal
experiences in order to promote continuous learning and improve
future experiences.
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D. Boud, R. Keogh, and D. Walker. Reflection: Turning Experience into Learning, chapter Promoting Reflection in Learning: a
Model., pages 18-40. Routledge Falmer, New York, 1985.
The Quantified Self (QS)
Collaboration of users and tool makers
Self-knowledge through self-tracking
Tools to collect personally relevant information
Gaining self-knowledge about one‘s experiences, behaviors,
habits and thoughts
09.05.2012 © FZI Forschungszentrum Informatik 5 http://quantifiedself.com http://nikeplus.com/ http://moodscope.com/ http://rescuetime.com/
Learning Analytics
For a particular model of learning
For a particular class of support tools
Beyond classroom settings in daily life
Quantified Self Tools
Motivation
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Learning processes
Rich source of data for LA
Awareness augmentation
Analysis of data
Quantification of abstract measures
E
A Framework to Apply QS Approaches to support
Reflective Learning
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Theory: Cognitive process
E
A Framework to Apply QS Approaches to support
Reflective Learning
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Theory: Cognitive process Tools: Experimentation
E
E
A Framework to Apply QS Approaches to support
Reflective Learning
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Theory: Cognitive process Tools: Experimentation
Survey of
several QS
tools
Model analysis
and information
needs
A Framework to Apply QS Approaches to support
Reflective Learning
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Tracking Cues
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Tracking Cues
Tracking means
Software sensors: applications – experiences not directly measurable
Hardware sensors: devices – automatic capture
environmental & physiological
Tracked aspects/object
Emotional aspects: mood, stress, interest, anxiety.
Private and work data: photos, browser's history, music.
Physiological data: physical activity and health.
General activity: #cigarettes, cups of coffee, hours spent in a certain activity.
Purposes
the goal which the user tries to achieve by using it.
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Triggering
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Triggering
Active
Notification or catching of the user’s attention explicitly.
Passive
No identification of experiences or no active contact to the user.
09.05.2012 © FZI Forschungszentrum Informatik 14 http://rescuetime.com/
http://daytum.com/
Recalling and Revisiting Experiences
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Recalling and Revisiting Experiences (I)
Contextualizing
Social Context
relationship and comparison to others
Spacial Context
Location in terms of city, street, room…
Historical Context
Evolution of the data in time
Item Metadata
Extra information and meaning
Context from other datasets
Weather, work schedules...
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Recalling and Revisiting Experiences (II)
Data fusion
Data analysis: Aggregation, Averages, etc.
Visualization
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Objective Self
Peer Group
http://dub.washington.edu/projects/ubifit
http://moodmap.apps.mirror-demo.eu/
Design and implementation of new
QS tools
Validate the framework to support reflective learning
Conclusions
A framework for the application of QS tools
to support reflective learning
Structured review of this strand of research
Understand the design space of QS tools for reflective learning
Understanding which parts have not been addressed by research
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THANK YOU!
Any questions?
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SOME MORE INFORMATION
About the tools and Related Work
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RescueTime
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http://rescuetime.com
MoodMap App
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http://moodmap.apps.mirror-demo.eu
MoodMap App
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http://moodmap.apps.mirror-demo.eu
Nike +
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http://nikeplus.com
Daytum
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http://daytum.com
http://daytum.com/
Ubifit
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http://dub.washington.edu/projects/ubifit
Related Work
Few related work on QS approaches towards reflection
Li et al. [1,2]
HCI design perspective
Stage-based Model of Personal Informatics
Physical activity (sport and diseases)
IMPACT System
Fleck and Fitzpatrick [3]
Psychological perspective
Design landscape and guiding questions
SenseCam – passive image capture
09.05.2012 © FZI Forschungszentrum Informatik
[1] I. Li, A. Dey, and J. Forlizzi. A stage-based Model of Personal Informatics Systems. In Proceedings of the 28th international conference on
Human Factors in computing systems, CHI '10, pages 557-566, New York, NY, USA, 2010. ACM.
[2] I. Li, A. K. Dey, and J. Forlizzi. Understanding my Data, Myself: Supporting Self-reflection with Ubicomp Technologies. In Proceedings of
the 13th international conference on Ubiquitous computing, UbiComp '11, pages 405-414, New York, NY, USA, 2011. ACM.
[3] R. Fleck and G. Fitzpatrick. Reflecting on reflection: framing a design landscape. In Proceedings of the 22nd Conference of the Computer-
Human Interaction Special Interest Group of Australia on Computer-Human Interaction, OZCHI '10, pages 216-223, New York, NY, USA,
2010. ACM.
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Five-stage model of personal informatics systems
[Li et al.]
09.05.2012 © FZI Forschungszentrum Informatik
[1] I. Li, A. Dey, and J. Forlizzi. A stage-based Model of Personal Informatics Systems. In Proceedings of the 28th international conference on
Human Factors in computing systems, CHI '10, pages 557-566, New York, NY, USA, 2010. ACM.
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Reflecting on Reflection
[Fleck and Fitzpatrick]
Aspects of reflection
Purpose of reflection
Conditions of reflection
Levels of reflection
Teachers’ reflective practices
Trainee teachers’ reflection on practice (Use Case)
SenseCam – passive image capture
09.05.2012 © FZI Forschungszentrum Informatik
[1] R. Fleck and G. Fitzpatrick. Reflecting on reflection: framing a design landscape. In Proceedings of the 22nd Conference of the Computer-
Human Interaction Special Interest Group of Australia on Computer-Human Interaction, OZCHI '10, pages 216-223, New York, NY, USA,
2010. ACM.
[2] Fleck R, Fitzpatrick G. Teachers' and tutors' social reflection around SenseCam images. Int. J. Hum.- Comput. Stud. 67 (2009) 1024-
1036.
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