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Nicola Beddall-Hill
Informatics ESRC PhD candidate
Attached to the TLRP TEL project
Ensemble
Workshop Session: Dealing with data Overload
The Retroductive Approach
Research2 PhD Forum on Research Methods Information Science at
Loughborough University: 9th July 2010
Workshop Session: Dealing with data Overload
The Retroductive Approach
Research2 PhD Forum on Research Methods Information Science at
Loughborough University: 9th July 2010
Supervisors: Prof. J., Raper; U., Patel; Prof. P., Carmichael & Prof. F., Webster
Retroductive approach
The basic task of social
enquiry is to explain…
regularities (R).
Explanation takes the
form of positing some
underlying mechanism
(M) which generated the
regularity....
How the workings of
such mechanisms are
contingent and
conditional (C).
Retroductive
Aim To discover underlying mechanisms to
explain observed regularities
From Document & model a regularity
Construct a hypothetical model of a
mechanism
To Find the real mechanism by
observation &/or experiment
Regularity = mechanism + Context
(Adapted from Pawson & Tilley (1997:72) in Blaikie (2000:112)
Regularity = mechanism + Context
(Adapted from Pawson & Tilley (1997:72) in Blaikie (2000:112)
(Adapted from Blaikie,2000:09)
• Ethnographic observation creating mixed data- audio visual,
audio, still, focus groups, field notes and GPS track logs
• The data is the observation of the life cycle of a student
project using technology to enhance learning
• Need to start at the beginning to understand the outcomes
• Mixed media taken simultaneously needs joining up
• 65GB of raw data!
RAW DATARAW DATA
DatabaseDatabaseTimeline
Level 1:
Organize raw data
Level 2:
Sort in database
Level 3:
Timeline critical
events
Level 4:
Make critical events
anonymous into
Fedora
Level 5:
Critical events in
ATLAS using
theoretical concepts
Level 6:
Create a model
Level 7:
Test model
DatabaseDatabase
RAW DATARAW DATA
Timeline
FEDORAFEDORA
Level 1:
Organize raw data
Level 2:
Sort in database
Level 3:
Timeline critical
events
Level 4:
Make critical events
anonymous into
Fedora
Level 5:
Critical events in
ATLAS using
theoretical concepts
Level 6:
Create a model
Level 7:
Test model
RAW DATARAW DATA
DatabaseDatabase
ATLAS ti.6ATLAS ti.6Concepts
to theorize
Concepts
to theorize
Timeline
FEDORAFEDORA
Field trip
test bed
Field trip
test bed
Level 1:
Organize raw data
Level 2:
Sort in database
Level 3:
Timeline critical
events
Level 4:
Make critical events
anonymous into
Fedora
Level 5:
Critical events in
ATLAS using
theoretical concepts
Level 6:
Create a model
Level 7:
Test model
Raw
data
Raw
data
Bento-files
linked & labeled
Bento-files
linked & labeled
When
software
fails!
When
software
fails!
Level 1Level 1
Level 2Level 2 Level 3Level 3
Email: nicola.beddall.1@city.ac.uk
Twitter: http://twitter.com/citymobileangel
Web: http://www.ensemble.ac.uk/
Nicola Beddall-Hill
ESRC PhD candidate – Informatics Dept.
TLRP TEL project Ensemble
Learning with mobile devices in the field
Email: nicola.beddall.1@city.ac.uk
Twitter: http://twitter.com/citymobileangel
Web: http://www.ensemble.ac.uk/
Nicola Beddall-Hill
ESRC PhD candidate – Informatics Dept.
TLRP TEL project Ensemble
Learning with mobile devices in the field

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Loughborough research forum 2010 data overload presentation

  • 1. Nicola Beddall-Hill Informatics ESRC PhD candidate Attached to the TLRP TEL project Ensemble Workshop Session: Dealing with data Overload The Retroductive Approach Research2 PhD Forum on Research Methods Information Science at Loughborough University: 9th July 2010 Workshop Session: Dealing with data Overload The Retroductive Approach Research2 PhD Forum on Research Methods Information Science at Loughborough University: 9th July 2010 Supervisors: Prof. J., Raper; U., Patel; Prof. P., Carmichael & Prof. F., Webster
  • 2. Retroductive approach The basic task of social enquiry is to explain… regularities (R). Explanation takes the form of positing some underlying mechanism (M) which generated the regularity.... How the workings of such mechanisms are contingent and conditional (C). Retroductive Aim To discover underlying mechanisms to explain observed regularities From Document & model a regularity Construct a hypothetical model of a mechanism To Find the real mechanism by observation &/or experiment Regularity = mechanism + Context (Adapted from Pawson & Tilley (1997:72) in Blaikie (2000:112) Regularity = mechanism + Context (Adapted from Pawson & Tilley (1997:72) in Blaikie (2000:112) (Adapted from Blaikie,2000:09)
  • 3. • Ethnographic observation creating mixed data- audio visual, audio, still, focus groups, field notes and GPS track logs • The data is the observation of the life cycle of a student project using technology to enhance learning • Need to start at the beginning to understand the outcomes • Mixed media taken simultaneously needs joining up • 65GB of raw data!
  • 4. RAW DATARAW DATA DatabaseDatabaseTimeline Level 1: Organize raw data Level 2: Sort in database Level 3: Timeline critical events Level 4: Make critical events anonymous into Fedora Level 5: Critical events in ATLAS using theoretical concepts Level 6: Create a model Level 7: Test model
  • 5. DatabaseDatabase RAW DATARAW DATA Timeline FEDORAFEDORA Level 1: Organize raw data Level 2: Sort in database Level 3: Timeline critical events Level 4: Make critical events anonymous into Fedora Level 5: Critical events in ATLAS using theoretical concepts Level 6: Create a model Level 7: Test model
  • 6. RAW DATARAW DATA DatabaseDatabase ATLAS ti.6ATLAS ti.6Concepts to theorize Concepts to theorize Timeline FEDORAFEDORA Field trip test bed Field trip test bed Level 1: Organize raw data Level 2: Sort in database Level 3: Timeline critical events Level 4: Make critical events anonymous into Fedora Level 5: Critical events in ATLAS using theoretical concepts Level 6: Create a model Level 7: Test model
  • 7.
  • 8. Raw data Raw data Bento-files linked & labeled Bento-files linked & labeled When software fails! When software fails! Level 1Level 1 Level 2Level 2 Level 3Level 3
  • 9. Email: nicola.beddall.1@city.ac.uk Twitter: http://twitter.com/citymobileangel Web: http://www.ensemble.ac.uk/ Nicola Beddall-Hill ESRC PhD candidate – Informatics Dept. TLRP TEL project Ensemble Learning with mobile devices in the field
  • 10. Email: nicola.beddall.1@city.ac.uk Twitter: http://twitter.com/citymobileangel Web: http://www.ensemble.ac.uk/ Nicola Beddall-Hill ESRC PhD candidate – Informatics Dept. TLRP TEL project Ensemble Learning with mobile devices in the field