learning analytics and quantified self approaches for reflective learning

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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

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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.

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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

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[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.]

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[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

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[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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