Personal Informatics+Context

   Using Context to Reveal Factors that Affect Behavior


   Ian Li
                        ...
Alice
                                             •  20 years old
                                             •  Family ...
Ian Li   Personal Informatics+Context   Thesis Proposal
   3
Mon   
1573
                                                           Tue   
4392
                                       ...
Transcribe to Excel




                                        M
     T
 W Th
 F
 Sa
 Su
 M
   T



Ian Li   Personal Inf...
Active



                                 Inactive
                           Inactive



                               ...
Factors
  •  Lack of time
  •  Lack of motivation
  •  Activities
                                                        ...
Location
                  Activity
   People
                                 Office
                    Shopping
   Famil...
Location
                  Activity
   People

  Problem
  Pedometer only recorded one type of
  information.




Ian Li  ...
Physical Activity

  Finance

  Electricity

  Diabetes

  Health

  Mood


              http://personalinformatics.org/t...
Thesis
  A personal informatics system 

  that allows users to associate 

  context with behavioral information 

  can ...
Thesis Questions
  Is a PI system with context better at
  revealing factors that affect behavior?
  •  YES, I will show t...
Location
                  Activity
   People




                                                 Location: Park
        ...
Location
                      Activity
   People




                                                            UbiComp
...
Thesis Questions
  How do we build a PI system with context?
  •  Alice had to do a lot to get data and reflect
     on the...
Introduction
   Stage-Based Model of PI
   Prototypes
     
Diary Study
     
IMPACT 1.0
     
IMPACT 2.0
   Proposed Work...
Introduction
   Stage-Based Model of PI
   Prototypes
     
Diary Study
     
IMPACT 1.0
     
IMPACT 2.0
   Proposed Work...
Thesis Questions
  Is a PI system with context better at
  revealing factors that affect behavior?

  How do we build a PI...
Survey and Interviews
  68 people who use personal informatics

  Advertised the survey in blogs about
  personal informat...
Sample Questions
  •  How difficult is it to collect this personal
     information?
  •  How do you explore this collected...
Analysis
  Identified barriers that people experienced.

  Affinity diagrams to identify themes. 

  Derived a model compose...
5 Stages
             PREPARATION      COLLECTION         INTEGRATION   REFLECTION   ACTION




Ian Li   Personal Informat...
5 Stages
             PREPARATION      COLLECTION         INTEGRATION   REFLECTION   ACTION




Ian Li   Personal Informat...
PREPARATION    COLLECTION   INTEGRATION   REFLECTION   ACTION




                                               Alice
   ...
PREPARATION    COLLECTION   INTEGRATION   REFLECTION   ACTION




                                                        ...
PREPARATION    COLLECTION   INTEGRATION   REFLECTION   ACTION




  Transcribe to Excel




                              ...
PREPARATION    COLLECTION   INTEGRATION   REFLECTION   ACTION




                                                        ...
PREPARATION    COLLECTION   INTEGRATION   REFLECTION   ACTION




  The stage when people
  choose what they are going
  t...
PREPARATION    COLLECTION   INTEGRATION   REFLECTION   ACTION




  Other research have explored these different
  stages ...
PREPARATION    COLLECTION   INTEGRATION   REFLECTION   ACTION




  1. Barriers cascade.
  2. Stages are iterative.




Ia...
1. Barriers Cascade.
  Problems in the earlier stages can affect the
  later stages.




Ian Li   Personal Informatics+Con...
1. Barriers Cascade.
                                Location
                  Activity
   People
                       ...
1. Barriers Cascade.
  Problems in the earlier stages can affect the
  later stages.

  → Consider all the stages when des...
2. Stages are Iterative.
  Users may need to incorporate new types of
  data, tools, and processes as they
  progressed th...
2. Stages are Iterative.
                                Location
                  Activity
   People




               ...
2. Stages are Iterative.
  Users may need to incorporate new types of
  data, tools, and processes as they progress
  thro...
PREPARATION    COLLECTION   INTEGRATION   REFLECTION   ACTION




  1. Barriers cascade.
  2. Stages are iterative.
  3. U...
3. User- vs. System-driven
  The stages can be user-driven, system-
  driven, or a combination of both.




Ian Li   Perso...
3. User- vs. System-driven
                                                                     Mon   
1573
              ...
3. User- vs. System-driven
  Collection
  System-driven

  Integration
  System-driven

  Reflection
  System-driven
Ian Li...
3. User- vs. System-driven
  The stages can be user-driven, system-
  driven, or a combination of both.

  → Explore the t...
Uni- vs. Multi-faceted
  Most personal informatics are uni-faceted.

  Some personal informatics systems have
  multi-face...
Uni- vs. Multi-faceted
  Users expressed desire to see associations
  between different facets of their lives.
  •  “To un...
Uni- vs. Multi-faceted
                                Location
                  Activity
   People
                     ...
Uni- vs. Multi-faceted
  Most personal informatics are uni-faceted.

  → Explore support for multiple facets
    throughou...
Thesis Questions
  Is a PI system with context better at
  revealing factors that affect behavior?

  How do we build a PI...
Introduction
   Stage-Based Model of PI
   Prototypes
     
Diary Study
     
IMPACT 1.0
     
IMPACT 2.0
   Proposed Work...
Thesis Questions
  Is a PI system with context better at
  revealing factors that affect behavior?
  → Deploy prototypes i...
Domain: Physical Activity




Ian Li   Personal Informatics+Context   Thesis Proposal
   49
Why Physical Activity?
  Lack of physical activity is a common
  problem that leads to obesity, diabetes, and
  high blood...
application. This is shown in Fig. 2c and d.                                         network. The network inputs are the s...
Research on Factors
  Physical activity is affected by lack of time,
  choice of activities, the environment, and
  social...
Activity


  Location


  People


  Physical Activity Level




Ian Li   Personal Informatics+Context   Thesis Proposal
 ...
Activities


  Location


  People


  Physical Activity Level




Ian Li   Personal Informatics+Context   Thesis Proposal...
Research on Factors
  Diabetes awareness of blood sugar level and
  food consumption (Frost & Smith ʼ03)
  •  Images of fo...
Research on Factors
  Asthma patients videotaping daily routines
  found that they are in the presence of harmful
  allerg...
Sedentary People and Walking
  Research suggests that they are less aware
  of their physical activity and how to become
 ...
Introduction
   Stage-Based Model of PI
   Prototypes
     
Diary Study
     
IMPACT 1.0
     
IMPACT 2.0
   Proposed Work...
Thesis Questions
  Is a PI system with context better at
  revealing factors that affect behavior?
  •  Run field studies w...
Introduction
   Stage-Based Model of PI
   Prototypes
     
Diary Study
     
IMPACT 1.0
     
IMPACT 2.0
   Proposed Work...
Thesis Questions
  Is a PI system with context better at
  revealing factors that affect behavior?

  Diary Study
  How wo...
Thesis Questions
  How do we build a PI system with context?
                                  Collection                 ...
Thesis Questions




            Time-Stamped
                                   Aggregated
              End-of-Day
     ...
Date:
                                                           Time    How active were you?   What?   Where?   With whom...
Tracking
                Booklet
                                                                                         ...
Setup
  4 female participants (A1-A4)
  •  Ages 25-50
  •  Sedentary. Pre-screened using Stages of
     Exercise Behavior ...
SenseWear Tracking


                                                   Booklet


            No                          ...
Results
  Excellent compliance over 3 weeks
  •  At least one activity recorded per hour




Ian Li   Personal Informatics...
In all phases, participants found factors
  that affected their physical activity.

  Week 1, A3:
  “Writing down had an e...
In all phases, participants found factors
  that affected their physical activity.

  Week 2, A1:
  “It was nice to see th...
FRI DEC 8, 2:03 ...                      Start Time

             Matching SenseWear graph printouts End Time
            ...
Matching SenseWear graph printouts
  with booklet entries.

  Week 3, A2:
  “The paper feedback [SenseWear] told me
  when...
Matching SenseWear graph
  printouts with booklet entries.


  Week 3, A1:
  “I had a lot of data, probably too much to
  ...
Detailed reflection
                               Immediate awareness




            Time-Stamped
                       ...
Thesis Questions
  Is a PI system with context better at
  revealing factors that affect behavior?

  •  Participants made...
Thesis Questions
  How do we build a PI system with context?
                                  Collection                 ...
IMPACT 1.0




Ian Li   Personal Informatics+Context   Thesis Proposal
   77
Thesis Questions
  Is a PI system with context better at
  revealing factors that affect behavior?

  Diary Study
  How wo...
Thesis Questions
  How do we build a PI system with context?
                                  Collection                 ...
Pedometer
                                      Booklet

Ian Li   Personal Informatics+Context   Thesis Proposal
         ...
Ian Li   Personal Informatics+Context   Thesis Proposal
   81
Plus-Context
                      e
  Day with "
  context labels



                      f
  Table and
  charts of step...
Pedometer
                  Booklet
     Web Site


  IMPACT 1.0



  Steps-Only
                                         ...
Setup
  30 participants (B1-B30)
  •  Sedentary. Pre-screened using Stages of
     Exercise Behavior Change (Marcus et al....
Steps-Only                        IMPACT 1.0
         Baseline




                               IMPACT 1.0              ...
Results
  Same level of physical activity awareness
  between Steps-Only and IMPACT




Ian Li   Personal Informatics+Cont...
Greater awareness of factors
  After using IMPACT, participants 

  self-reported greater awareness of factors
  that affe...
Greater awareness of factors
  Mentioned context
  •  “It has been interesting to see what times
     of the day I'm most ...
Greater awareness of factors
                                Mentioned Context                       Mentioned Context
   ...
IMPACT was rated most useful
  “The [context] I used the most was the one
  asking who I was with during my most active
  ...
But IMPACT was harder to use
  17 of 30 participants preferred Steps-Only.

  “IMPACT gave a lot of cool information, but
...
Problem can be fixed
  Those who preferred Steps-Only said:
  •  “There were times I wanted to explain my
     context.” B2...
Thesis Questions
  Is a PI system with context better at
  revealing factors that affect behavior?

  •  Context can incre...
Collection
                                                               Thesis Questions
                               ...
IMPACT 2.0




Ian Li   Personal Informatics+Context   Thesis Proposal
   95
Thesis Questions
  Is a PI system with context better at
  revealing factors that affect behavior?

  Diary Study
  How wo...
Thesis Questions
  How do we build a PI system with context?
                                  Collection                 ...
IMPACT 2.0




Ian Li   Personal Informatics+Context   Thesis Proposal
   98
IMPACT 2.0




                                                           Bluetooth GPS

Ian Li   Personal Informatics+Con...
IMPACT 2.0




                                                           Context Input

Ian Li   Personal Informatics+Con...
IMPACT 2.0




                                                  Bluetooth Sync

Ian Li   Personal Informatics+Context   T...
Ian Li   Personal Informatics+Context   Thesis Proposal
   102
Mobile Phone
                                  Web Site


  IMPACT 2.0
                                                   ...
Setup
  35 participants (C1-C35)
  •  Sedentary. Pre-screened using Stages of
     Exercise Behavior Change (Marcus et al....
Baseline Phase                                   Intervention Phase

                                                     ...
Results
  Complaints were not about the tedium of
  writing things down, but about having to carry
  multiple devices.
  •...
Awareness of factors increased for
  all groups between the phases
                                                      3...
Similar awareness of factors
                               Mentioned Context                   Mentioned Context
        ...
Long-term reflection
  What is the value of contextual information in
  the long-term?

  6-months later when they were mor...
Follow-Up Interviews
  Participants:
  •  Control (5)
  •  Steps-Only (6)
  •  IMPACT 2.0 (3)




Ian Li   Personal Inform...
Follow-Up Interviews
  Expressed interest in comparing over long
  periods of time.

  Curious about the peaks in physical...
Collection vs. Reflection
                                              Short-term   Long-term
                            ...
Thesis Questions
  Is a PI system with context better at
  revealing factors that affect behavior?

  Automation has an ef...
Diary                                               Thesis Questions
         Prototype                      user-driven  ...
Thesis Questions
  Is a PI system with context better at
  revealing factors that affect behavior?

  •  Diary Study and I...
Thesis Questions
  How do we build a PI system with context?
                   Collection Integration Reflection

       ...
Introduction
   Stage-Based Model of PI
   Completed Work
     
Diary Study
     
IMPACT 1.0
     
IMPACT 2.0
   Proposed ...
IMPACT 3.0?




Ian Li   Personal Informatics+Context   Thesis Proposal
   118
Thesis Questions
  Is a PI system with context better at
  revealing factors that affect behavior?
  •  How do people use ...
Thesis Questions
  How do we build a PI system with context?

  •  Reduce the cost of using personal
     informatics syst...
UNI-FACETED vs. MULTI-FACETED




                                         uni-faceted        multi-faceted




Ian Li   P...
Collection Integration Reflection

         Diary                                                              Need visual...
PREPARATION   COLLECTION   INTEGRATION




                              ITERATIVE




  Forced users to collect three typ...
PREPARATION   COLLECTION   INTEGRATION




                              ITERATIVE




  The prototypes did not support co...
PREPARATION   COLLECTION   INTEGRATION




                              ITERATIVE




  The prototypes did not count othe...
PREPARATION   COLLECTION   INTEGRATION




                              ITERATIVE




  •  Allow users to select factors ...
BARRIERS CASCADE




  The prototypes experienced several barriers
  that affected their usage.

  Subsequent prototypes a...
IMPACT 3.0 Requirements
  1.  Maintain immediate awareness in semi-
      automated collection.

  2.  Give choices for ot...
1. Maintain Immediate Awareness
  Low-cost manual collection where
  visualizations are shown after input. 

   (ES+feedba...
1. Maintain Immediate Awareness
  Encourage daily use of the visualizations.
  •  Alert the user of an interesting fact.
 ...
2. Other types of context and PA
  Integrate other sources of context
  •  Online weather information
  •  Event informati...
2. Other types of context and PA
  Allow logging of other physical activity.

  Equate amount of physical activity with
  ...
Personal Informatics Browser




Ian Li   Personal Informatics+Context   Thesis Proposal
   133
3. Explore Visualizations in Detail 
  Problems occurred in stages before
  Reflection, now I can explore this stage in
  d...
3. Explore Visualizations in Detail
                                        Housework
         Shopping




              ...
3. Explore Visualizations in Detail

                                                           Office

         Office




...
Setup
  40 participants
  •  Sedentary and active

  Questionnaires at the end of each phase




Ian Li   Personal Informa...
Baseline Phase                                   Intervention Phase


                                                    ...
Awareness Effects
  Higher awareness of factors that affect
  physical activity.

  Maintain immediate awareness even when...
Psychological Effects
  Higher locus of control

  Higher self-efficacy

  Self-reports of change in physical activity




...
Thesis Questions
  Is a PI system with context better at
  revealing factors that affect behavior?
  •  Deployment of a pe...
Thesis Questions
  How do we build a PI system with context?

  •  Designs that reduce the cost of using
     personal inf...
Limitation
  Focus on physical activity.
  •  PI systems share the same stages.
  •  Revealing factors that affect behavio...
Future Work
  Sharing data.
  •  Many PI systems allow sharing.
  •  Explore the quality of discussions when
     data is ...
Thesis Questions
  Is a PI system with context better at
  revealing factors that affect behavior?
  •  Showed that contex...
Thesis Questions
  How do we build a PI system with context?
  •  Created the stage-based model of PI as a
     framework ...
Schedule
                                                    2010
                         p
                        m
   ...
Thank you!
  To my advisors, Anind Dey and Jodi Forlizzi, and the rest of my
  committee, Niki Kittur and John Stasko.

  ...
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Personal Informatics and Context: Using Context to Reveal Factors that Affect Behavior

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Today, there is a personal informatics system for almost any behavior (see a list at http://personalinformatics.org/tools). These systems help people collect behavioral information to explore and reflect on. Because most systems only show behavioral information, finding factors that affect one's behavior is difficult. Incorporating contextual information, such as location, may help. To explore this, I developed prototypes of IMPACT, a system for physical activity awareness with support for contextual information. Previous deployments showed that context can increase people's awareness of opportunities for physical activity and automation facilitates long-term use but reduces immediate awareness. I will develop a third prototype that supports better selection of contextual information, maintenance of immediate awareness during automated collection, and improved visualizations. I will compare the prototype in a field study to a steps-only system and identify features critical to its effectiveness. I will take the lessons learned and describe how they may apply to supporting contextual information in personal informatics systems for other types of behaviors.

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Personal Informatics and Context: Using Context to Reveal Factors that Affect Behavior

  1. 1. Personal Informatics+Context
 Using Context to Reveal Factors that Affect Behavior Ian Li Anind Dey, CMU, Co-chair Jodi Forlizzi, CMU, Co-chair Niki Kittur, CMU John Stasko, Georgia Tech Ian Li Personal Informatics+Context Thesis Proposal
  2. 2. Alice •  20 years old •  Family history of heart disease •  Wants to be more active, but donʼt know how because sheʼs busy Ian Li Personal Informatics+Context Thesis Proposal 2
  3. 3. Ian Li Personal Informatics+Context Thesis Proposal 3
  4. 4. Mon 1573 Tue 4392 Wed 4537 Thu 5842 Fri 10258 Sat 7528 Sun 1368 Mon 1497 Tue 1837 Ian Li Personal Informatics+Context Thesis Proposal 4
  5. 5. Transcribe to Excel M T W Th F Sa Su M T Ian Li Personal Informatics+Context Thesis Proposal 5
  6. 6. Active Inactive Inactive M T W Th F Sa Su M T Ian Li Personal Informatics+Context Thesis Proposal 6
  7. 7. Factors •  Lack of time •  Lack of motivation •  Activities Active •  Location •  People Inactive Inactive M T W Th F Sa Su M T Ian Li Personal Informatics+Context Thesis Proposal 7
  8. 8. Location Activity People Office Shopping Family Active Inactive Inactive M T W Th F Sa Su M T Ian Li Personal Informatics+Context Thesis Proposal 8
  9. 9. Location Activity People Problem Pedometer only recorded one type of information. Ian Li Personal Informatics+Context Thesis Proposal 9
  10. 10. Physical Activity Finance Electricity Diabetes Health Mood http://personalinformatics.org/tools Ian Li Personal Informatics+Context Thesis Proposal 10
  11. 11. Thesis A personal informatics system 
 that allows users to associate 
 context with behavioral information 
 can better reveal factors that affect behavior, compared to systems that only show behavioral information. Ian Li Personal Informatics+Context Thesis Proposal 11
  12. 12. Thesis Questions Is a PI system with context better at revealing factors that affect behavior? •  YES, I will show this in 3 completed studies and my proposed work. Ian Li Personal Informatics+Context Thesis Proposal 12
  13. 13. Location Activity People Location: Park Activity: Hiking People: Friend Step counts: 7531 Ian Li Personal Informatics+Context Thesis Proposal 13
  14. 14. Location Activity People UbiComp Sensors Data mining Ian Li Personal Informatics+Context Thesis Proposal 14
  15. 15. Thesis Questions How do we build a PI system with context? •  Alice had to do a lot to get data and reflect on them. •  Issues collecting data? Reflecting on data? •  It is not as easy as just automating the system. •  Whether the system is manual or automated has an effect on the userʼs awareness. Ian Li Personal Informatics+Context Thesis Proposal 15
  16. 16. Introduction Stage-Based Model of PI Prototypes Diary Study IMPACT 1.0 IMPACT 2.0 Proposed Work Conclusion Ian Li Personal Informatics+Context Thesis Proposal 16
  17. 17. Introduction Stage-Based Model of PI Prototypes Diary Study IMPACT 1.0 IMPACT 2.0 Proposed Work Conclusion Ian Li Personal Informatics+Context Thesis Proposal 17
  18. 18. Thesis Questions Is a PI system with context better at revealing factors that affect behavior? How do we build a PI system with context? •  Create a framework as guide in designing personal informatics systems. •  Building a PI system involves many parts each with their own HCI issues. Ian Li Personal Informatics+Context Thesis Proposal 18
  19. 19. Survey and Interviews 68 people who use personal informatics Advertised the survey in blogs about personal informatics. What tools they use and their problems Ian Li Personal Informatics+Context Thesis Proposal 19
  20. 20. Sample Questions •  How difficult is it to collect this personal information? •  How do you explore this collected personal information? •  What patterns have you found? Transcript of the survey is at: http://personalinformatics.org/lab/survey Ian Li Personal Informatics+Context Thesis Proposal 20
  21. 21. Analysis Identified barriers that people experienced. Affinity diagrams to identify themes. Derived a model composed of: •  5 stages Ian Li Personal Informatics+Context Thesis Proposal 21
  22. 22. 5 Stages PREPARATION COLLECTION INTEGRATION REFLECTION ACTION Ian Li Personal Informatics+Context Thesis Proposal 22
  23. 23. 5 Stages PREPARATION COLLECTION INTEGRATION REFLECTION ACTION Ian Li Personal Informatics+Context Thesis Proposal 23
  24. 24. PREPARATION COLLECTION INTEGRATION REFLECTION ACTION Alice •  Wanted to become active •  Decided to track her physical activity •  Chose to track step counts using a pedometer Ian Li Personal Informatics+Context Thesis Proposal 24
  25. 25. PREPARATION COLLECTION INTEGRATION REFLECTION ACTION Mon 1573 Tue 4392 Wed 4537 Thu 5842 Fri 10258 Sat 7528 Sun 1368 Mon 1497 Tue 1837 Ian Li Personal Informatics+Context Thesis Proposal 25
  26. 26. PREPARATION COLLECTION INTEGRATION REFLECTION ACTION Transcribe to Excel M T W Th F Sa Su M T Ian Li Personal Informatics+Context Thesis Proposal 26
  27. 27. PREPARATION COLLECTION INTEGRATION REFLECTION ACTION Active Inactive Inactive M T W Th F Sa Su M T Ian Li Personal Informatics+Context Thesis Proposal 27
  28. 28. PREPARATION COLLECTION INTEGRATION REFLECTION ACTION The stage when people choose what they are going to do with their new-found understanding of themselves. •  Alerts •  Incentives •  Suggestions Ian Li Personal Informatics+Context Thesis Proposal 28
  29. 29. PREPARATION COLLECTION INTEGRATION REFLECTION ACTION Other research have explored these different stages in isolation •  Collection •  MyLifeBits (Gemmell et al. 2006) •  SenseCam (Hodges et al. 2006) •  Reflection •  Casual InfoVis (Pousman et al. 2007) Ian Li Personal Informatics+Context Thesis Proposal 29
  30. 30. PREPARATION COLLECTION INTEGRATION REFLECTION ACTION 1. Barriers cascade. 2. Stages are iterative. Ian Li Personal Informatics+Context Thesis Proposal 30
  31. 31. 1. Barriers Cascade. Problems in the earlier stages can affect the later stages. Ian Li Personal Informatics+Context Thesis Proposal 31
  32. 32. 1. Barriers Cascade. Location Activity People Office Shopping Family Active Inactive Inactive M T W Th F Sa Su M T Ian Li Personal Informatics+Context Thesis Proposal 32
  33. 33. 1. Barriers Cascade. Problems in the earlier stages can affect the later stages. → Consider all the stages when designing PI systems. Ian Li Personal Informatics+Context Thesis Proposal 33
  34. 34. 2. Stages are Iterative. Users may need to incorporate new types of data, tools, and processes as they progressed through the stages. Ian Li Personal Informatics+Context Thesis Proposal 34
  35. 35. 2. Stages are Iterative. Location Activity People Location: Park Activity: Hiking People: Friend Step counts: 7531 Ian Li Personal Informatics+Context Thesis Proposal 35
  36. 36. 2. Stages are Iterative. Users may need to incorporate new types of data, tools, and processes as they progress through the stages. → Flexibility is important, but consider user needs early to minimize missed data. Ian Li Personal Informatics+Context Thesis Proposal 36
  37. 37. PREPARATION COLLECTION INTEGRATION REFLECTION ACTION 1. Barriers cascade. 2. Stages are iterative. 3. User- or system-driven 4. Uni- or multi-faceted Ian Li Personal Informatics+Context Thesis Proposal 37
  38. 38. 3. User- vs. System-driven The stages can be user-driven, system- driven, or a combination of both. Ian Li Personal Informatics+Context Thesis Proposal 38
  39. 39. 3. User- vs. System-driven Mon 1573 Tue 4392 Collection Wed Thu 4537 5842 Fri 10258 Combination Sat Sun Mon 7528 1368 1497 Tue 1837 Integration Transcribe to Excel User-driven Reflection Excel graphs System-driven Ian Li Personal Informatics+Context Thesis Proposal 39
  40. 40. 3. User- vs. System-driven Collection System-driven Integration System-driven Reflection System-driven Ian Li Personal Informatics+Context Thesis Proposal 40
  41. 41. 3. User- vs. System-driven The stages can be user-driven, system- driven, or a combination of both. → Explore the tradeoffs between user-driven and system-driven stages. Ian Li Personal Informatics+Context Thesis Proposal 41
  42. 42. Uni- vs. Multi-faceted Most personal informatics are uni-faceted. Some personal informatics systems have multi-faceted collection, but only support uni-faceted reflection. Ian Li Personal Informatics+Context Thesis Proposal 42
  43. 43. Uni- vs. Multi-faceted Users expressed desire to see associations between different facets of their lives. •  “To understand trends in symptoms, behaviors, and circumstances.” P26 •  “If it were easily collected, information on food intake, calories, fat, etc., would make an interesting starting point for analysis.” P49 who tracks medication intake Ian Li Personal Informatics+Context Thesis Proposal 43
  44. 44. Uni- vs. Multi-faceted Location Activity People Office Shopping Family Active Inactive Inactive M T Th F Sa Su M T Ian Li Personal Informatics+Context Thesis Proposal 44
  45. 45. Uni- vs. Multi-faceted Most personal informatics are uni-faceted. → Explore support for multiple facets throughout the stages. •  I explore using contextual information. Ian Li Personal Informatics+Context Thesis Proposal 45
  46. 46. Thesis Questions Is a PI system with context better at revealing factors that affect behavior? How do we build a PI system with context? •  Created a framework to analyze PI systems. •  When designing, consider all the stages. Ian Li Personal Informatics+Context Thesis Proposal 46
  47. 47. Introduction Stage-Based Model of PI Prototypes Diary Study IMPACT 1.0 IMPACT 2.0 Proposed Work Conclusion Ian Li Personal Informatics+Context Thesis Proposal 47
  48. 48. Thesis Questions Is a PI system with context better at revealing factors that affect behavior? → Deploy prototypes in field studies. How do we build a PI system with context? → Build prototypes that explore different ways of supporting context. Ian Li Personal Informatics+Context Thesis Proposal 48
  49. 49. Domain: Physical Activity Ian Li Personal Informatics+Context Thesis Proposal 49
  50. 50. Why Physical Activity? Lack of physical activity is a common problem that leads to obesity, diabetes, and high blood pressure. Lack of awareness of physical activity is one reason why people are not active. Ian Li Personal Informatics+Context Thesis Proposal 50
  51. 51. application. This is shown in Fig. 2c and d. network. The network inputs are the sum of signal strength fluctuation across all monitored cells, and the number of 3.1 Sensing activity distinct cells monitored over a given time interval. The network consists of a single layer of eight hidden neurons; The current activity of the user is inferred using patterns of weights are learnt using back propagation. The network fluctuation in GSM signal strength and changes to the IDs outputs the currently sensed activity for the given input of detected cells. This method has been demonstrated as a values. The network is trained by repeatedly presenting data Physical Activity Awareness reliable and unobtrusive way of sensing current activity [2], and has the advantage over the more traditional approach of using an accelerometer in that it does not require additional sensor hardware as in Sensay [17] and the multimodal collected during each method of movement. The current activity of the user is conditionally depen- dent upon their previous activity. In order to provide instant feedback to the user interface, the neural network deliber- sensor board of [11]. Similarly, while the processing of ately does not model this behaviour. Instead, when deter- physiological and biometric data could complement our mining if any additional minutes have been earned, we approach, the benefits of encapsulating the system within a apply task knowledge based upon the output from the mobile phone would be lost. An alternative approach would neural network over the previous two and a half minutes. be to utilise the positioning information available from This enables noise to be filtered out and a more accurate some mobile phone networks, however this approach representation of the users’ activities achieved. For exam- Products frequently involves prohibitive cost, as well as depending upon much of the same technology as our client based monitoring. ple, periods of low signal strength fluctuation such as stopping at traffic lights whilst driving can be ignored when placed between periods of high fluctuation where many Rather like a traditional accelerometer, the levels of distinct neighbouring cells were monitored. It could be signal strength fluctuation change when a mobile phone is argued that activity would be more accurately inferred if a moved. For example, Fig. 3 shows the total signal strength longer rolling filter had been applied to the GSM data. fluctuation across all monitored cells during successive 30-s Introducing longer filters would have increased the likeli- time periods whilst walking, remaining still and travelling hood of active minutes ‘disappearing’ from the users’ Fish’n’Steps: Encouraging Physical Activity with an Interactive Computer Game 1 2 Research 3 4 !! Fig. 1. One participant’s display after approximately two weeks into the trial in the Fish'n team-condition, also the public kiosk and pedometer platform, which rotated through e the team fish-tanks. The components of the personal display include: 1) Fish Tank - Th tank contains the virtual pets belong to the participant and his/her team members, 2) Virtu Figure 2 The phone interface. Images a and b show screens for examining relative – The participant’s own fish in alevels:view on the right side next to the fish tank, 3) Ca and individual activity frontal compare Daily Activity and This Week’s Activity Images. c and d show two of the screens showing the estimated current activity level: Stationary and progress bar, personal and team ra tions and feedback - improvement, burned calories, Walking UbiFit
 Shakra Fish ʻn Steps etc., 4) Chat window for communicating with team members. To evaluate the effect of Fish’n’Steps, we recruited 19 participants from the Consolvo et al. ʼ08 Maitland et al. ʻ06 Lin et al. ʻ06 of Siemens Corporate Research to participate in a 14-week study. Two experim conditions were designed to separately assess the impact of the virtual pet an social influences. Application of the TTM to assess behavior that changed durin study demonstrated that Fish’n’Steps was a catalyst of a positive change for 14 o 19 participants. This effect was evident in either an increase in their daily step Ian Li Personal Informatics+Context Thesis Proposal (for 4 participants), a change in their attitudes towards physical activity (for 3 pa 51 pants) or a combination of the two (for 7 participants). The greatest change in
  52. 52. Research on Factors Physical activity is affected by lack of time, choice of activities, the environment, and social influence. (Sallis & Hovell 1990) CDC suggests understanding of factors to circumvent barriers to physical activity. Ian Li Personal Informatics+Context Thesis Proposal 52
  53. 53. Activity Location People Physical Activity Level Ian Li Personal Informatics+Context Thesis Proposal 53
  54. 54. Activities Location People Physical Activity Level Ian Li Personal Informatics+Context Thesis Proposal 54
  55. 55. Research on Factors Diabetes awareness of blood sugar level and food consumption (Frost & Smith ʼ03) •  Images of food associated with blood sugar level. •  Used in a class where people discussed their images and blood sugar level. •  Made a prototype, but only tested with one person. Ian Li Personal Informatics+Context Thesis Proposal 55
  56. 56. Research on Factors Asthma patients videotaping daily routines found that they are in the presence of harmful allergens more often than they realized (Rich et al. ʻ00) •  Users videotaped daily routines, but a trained observer looked at the video for assessment. •  Matt Leeʼs embedded assessment work Ian Li Personal Informatics+Context Thesis Proposal 56
  57. 57. Sedentary People and Walking Research suggests that they are less aware of their physical activity and how to become active (Sallis & Hovell 1990) Focused on walking because it is easier to integrate into daily life. (Norman & Mills 2004) Ian Li Personal Informatics+Context Thesis Proposal 57
  58. 58. Introduction Stage-Based Model of PI Prototypes Diary Study IMPACT 1.0 IMPACT 2.0 Proposed Work Conclusion Ian Li Personal Informatics+Context Thesis Proposal 58
  59. 59. Thesis Questions Is a PI system with context better at revealing factors that affect behavior? •  Run field studies with prototypes. How do we build a PI system with context? •  Build several prototypes to try different ways of supporting context. Ian Li Personal Informatics+Context Thesis Proposal 59
  60. 60. Introduction Stage-Based Model of PI Prototypes Diary Study IMPACT 1.0 IMPACT 2.0 Proposed Work Conclusion Ian Li Personal Informatics+Context Thesis Proposal 60
  61. 61. Thesis Questions Is a PI system with context better at revealing factors that affect behavior? Diary Study How would people find factors using context? IMPACT 1.0 Would context reveal factors that affect behavior? IMPACT 2.0 What is the value of context in the long term? Ian Li Personal Informatics+Context Thesis Proposal 61
  62. 62. Thesis Questions How do we build a PI system with context? Collection Integration Reflection Diary Prototype user-driven user-driven user-driven IMPACT 1.0 user-driven user-driven system-driven IMPACT 2.0 combination system-driven system-driven Ian Li Personal Informatics+Context Thesis Proposal 62
  63. 63. Thesis Questions Time-Stamped Aggregated End-of-Day Real-time Ian Li Personal Informatics+Context Thesis Proposal 63
  64. 64. Date: Time How active were you? What? Where? With whom? Time How activ 6a: 1p: : : : : : : 7a: 2p: : : : : : : 8a: 3p: : : : : : : 9a: 4p: : : : : : : 10a: 5p: : : : : : : 11a: 6p: : : : : : : SenseWear Booklet 12p: 7p: : : : : : : Ian Li Personal Informatics+Context Thesis Proposal 64
  65. 65. Tracking Booklet Reflection Date: Time How active were you? What? Where? With whom? Time How active were you? What? Where? With whom? 6a: 1p: : : : : : : 7a: 2p: : : : : : : 8a: 3p: No Feedback : : No Feedback : : : : 9a: 4p: : : : : : : 10a: 5p: : : : : : : 11a: 6p: : : : : : : 12p: 7p: : : : : : : Continue to the next page.! Date: Time How active were you? What? Where? With whom? Time How active were you? What? Where? With whom? 6a: 1p: : : : : : : 7a: 2p: : : : : Aggregated : : 8a: 3p: : : : : : : 9a: 4p: : : : : : : 10a: 5p: : : Real-time : : : : 11a: 6p: : : : : : : 12p: 7p: : : : : : : Continue to the next page.! Date: Time How active were you? What? Where? With whom? Time How active were you? What? Where? With whom? 6a: 1p: : : : : : : 7a: 2p: : : : : Time-Stamped : : 8a: 3p: : : : : : : 9a: 4p: : : : : : : 10a: 5p: End-of-Day : : : : : : 11a: 6p: : : : : : : 12p: 7p: : : : : : : Continue to the next page.! Ian Li Personal Informatics+Context Thesis Proposal 65
  66. 66. Setup 4 female participants (A1-A4) •  Ages 25-50 •  Sedentary. Pre-screened using Stages of Exercise Behavior Change (Marcus et al. 1998) Audio-taped interviews every week Ian Li Personal Informatics+Context Thesis Proposal 66
  67. 67. SenseWear Tracking Booklet No Pedometer SenseWear Physical Activity Graph Printouts Information 1 2 3 Ian Li Personal Informatics+Context Thesis Proposal 67
  68. 68. Results Excellent compliance over 3 weeks •  At least one activity recorded per hour Ian Li Personal Informatics+Context Thesis Proposal 68
  69. 69. In all phases, participants found factors that affected their physical activity. Week 1, A3: “Writing down had an effect. I would think ʻOh good I have something active to write down.ʼ Like when I would carry my laundry to the Laundromat on foot.” Ian Li Personal Informatics+Context Thesis Proposal 69
  70. 70. In all phases, participants found factors that affected their physical activity. Week 2, A1: “It was nice to see that I walked more than I did. There was one day when I was babysitting. I walked so much with the baby. I walked all over campus.” Ian Li Personal Informatics+Context Thesis Proposal 70
  71. 71. FRI DEC 8, 2:03 ... Start Time Matching SenseWear graph printouts End Time - Fri Dec 8, 2006 05:14 AM Session end - Fri Dec 8, 2006 02:03 PM with booklet entries. End 2:03 PM FRI DEC 8, 2:03 ... Start Time - Fri Dec 8, 2006 05:14 AM End Time Session end - Fri Dec 8, 2006 02:03 PM Start End 5:14 AM 2:03 PM Active ... Physical Activity (2.5 ME... Step Count Lying Do... Sleep Duration of Vi... 438 cal 1 hr 43 m... 11346 Not detect... Not detect... 8 hrs 49 m... Ian Li Personal Informatics+Context Thesis Proposal 71
  72. 72. Matching SenseWear graph printouts with booklet entries. Week 3, A2: “The paper feedback [SenseWear] told me when the intensity was greater than other times, so I was able to gauge my activities like if I just walk upstairs…I was calling them in the diary ʻaerobic mini burstʼ.” Ian Li Personal Informatics+Context Thesis Proposal 72
  73. 73. Matching SenseWear graph printouts with booklet entries. Week 3, A1: “I had a lot of data, probably too much to decipher, but it was good. I didnʼt really compare everything to my booklet, only the peaks on the charts to see what I was doing.” Ian Li Personal Informatics+Context Thesis Proposal 73
  74. 74. Detailed reflection Immediate awareness Time-Stamped Aggregated End-of-Day Real-time Ian Li Personal Informatics+Context Thesis Proposal 74
  75. 75. Thesis Questions Is a PI system with context better at revealing factors that affect behavior? •  Participants made associations between their physical activity and contextual information helping them become aware of factors that affected their physical activity. → Can we do this in a field study of a prototype with more people? Ian Li Personal Informatics+Context Thesis Proposal 75
  76. 76. Thesis Questions How do we build a PI system with context? Collection Integration Reflection Diary Prototype user-driven user-driven user-driven IMPACT 1.0 → Help users make directuser-driven user-driven associations. system-driven → Value2.0 aggregated real-time info and IMPACT in end-of-day combination time-stamped info. system-driven system-driven Ian Li Personal Informatics+Context Thesis Proposal 76
  77. 77. IMPACT 1.0 Ian Li Personal Informatics+Context Thesis Proposal 77
  78. 78. Thesis Questions Is a PI system with context better at revealing factors that affect behavior? Diary Study How would people find factors using context? IMPACT 1.0 Would context reveal factors that affect behavior? IMPACT 2.0 What is the value of context in the long term? Ian Li Personal Informatics+Context Thesis Proposal 78
  79. 79. Thesis Questions How do we build a PI system with context? Collection Integration Reflection Diary Prototype user-driven user-driven user-driven IMPACT 1.0 user-driven user-driven system-driven IMPACT 2.0 combination system-driven system-driven Ian Li Personal Informatics+Context Thesis Proposal 79
  80. 80. Pedometer Booklet Ian Li Personal Informatics+Context Thesis Proposal 80
  81. 81. Ian Li Personal Informatics+Context Thesis Proposal 81
  82. 82. Plus-Context e Day with " context labels f Table and charts of steps and context g Steps by hour and by period of day Figure 3. a) Interface for recording steps. Steps-Only additions. Ian Li Personal Informatics+Context Thesis Proposal b) One day of steps. c) Week of steps by day. d) Week of steps for82
  83. 83. Pedometer Booklet Web Site IMPACT 1.0 Steps-Only Steps-Only Steps-Only Baseline Steps-Only No Vis Ian Li Personal Informatics+Context Thesis Proposal 83
  84. 84. Setup 30 participants (B1-B30) •  Sedentary. Pre-screened using Stages of Exercise Behavior Change (Marcus et al. 1998) Questionnaires at the end of each phase Ian Li Personal Informatics+Context Thesis Proposal 84
  85. 85. Steps-Only IMPACT 1.0 Baseline IMPACT 1.0 Steps-Only 1 2 3 4 5 6 7 Ian Li Personal Informatics+Context Thesis Proposal 85
  86. 86. Results Same level of physical activity awareness between Steps-Only and IMPACT Ian Li Personal Informatics+Context Thesis Proposal 86
  87. 87. Greater awareness of factors After using IMPACT, participants 
 self-reported greater awareness of factors that affect physical activity (5-point Likert scale) 3.93 (IMPACT) vs. 3.57 (Steps-Only) F[1,58] = 5.32, p < .05 Ian Li Personal Informatics+Context Thesis Proposal 87
  88. 88. Greater awareness of factors Mentioned context •  “It has been interesting to see what times of the day I'm most active.” B17 •  “It turns out I get the most walking done to and from work, which I can't say I wasn't expecting, but I also had no idea that walking around Squirrel Hill for just an hour or two made such a difference.” B24 Ian Li Personal Informatics+Context Thesis Proposal 88
  89. 89. Greater awareness of factors Mentioned Context Mentioned Context Excluding Time IMPACT 1.0 18 out of 30 13 Steps-Only 13 out of 30 7 Control 11 out of 30 6 Ian Li Personal Informatics+Context Thesis Proposal 89
  90. 90. IMPACT was rated most useful “The [context] I used the most was the one asking who I was with during my most active periods…I hadnʼt realized that I was so sedentary most of the time I spent with my friends.” B1 Ian Li Personal Informatics+Context Thesis Proposal 90
  91. 91. But IMPACT was harder to use 17 of 30 participants preferred Steps-Only. “IMPACT gave a lot of cool information, but having to input all the various factors was a hassle.” B4 Ian Li Personal Informatics+Context Thesis Proposal 91
  92. 92. Problem can be fixed Those who preferred Steps-Only said: •  “There were times I wanted to explain my context.” B22 •  “IMPACT should be provided as an option.” B30 90% reported they would continue using IMPACT if collection of context was automated. Ian Li Personal Informatics+Context Thesis Proposal 92
  93. 93. Thesis Questions Is a PI system with context better at revealing factors that affect behavior? •  Context can increase awareness of factors that affect physical activity. Ian Li Personal Informatics+Context Thesis Proposal 93
  94. 94. Collection Thesis Questions Integration Reflection Diary How do we build a PI system with context? Prototype Collection user-driven Integration user-driven Reflection user-driven IMPACT 1.0 Diary user-driven user-driven system-driven Prototype user-driven user-driven user-driven Visualizations IMPACT 2.0 IMPACT 1.0 combination system-driven system-driven → Users need help collecting and integrating user-driven user-driven system-driven IMPACT over a long period of time. data 2.0 combination system-driven system-driven Ian Li Personal Informatics+Context Thesis Proposal 94
  95. 95. IMPACT 2.0 Ian Li Personal Informatics+Context Thesis Proposal 95
  96. 96. Thesis Questions Is a PI system with context better at revealing factors that affect behavior? Diary Study How would people find factors using context? IMPACT 1.0 Would context reveal factors that affect behavior? IMPACT 2.0 What is the value of context in the long term? Ian Li Personal Informatics+Context Thesis Proposal 96
  97. 97. Thesis Questions How do we build a PI system with context? Collection Integration Reflection Diary Prototype user-driven user-driven user-driven IMPACT 1.0 user-driven user-driven system-driven IMPACT 2.0 combination system-driven system-driven Ian Li Personal Informatics+Context Thesis Proposal 97
  98. 98. IMPACT 2.0 Ian Li Personal Informatics+Context Thesis Proposal 98
  99. 99. IMPACT 2.0 Bluetooth GPS Ian Li Personal Informatics+Context Thesis Proposal 99
  100. 100. IMPACT 2.0 Context Input Ian Li Personal Informatics+Context Thesis Proposal 100
  101. 101. IMPACT 2.0 Bluetooth Sync Ian Li Personal Informatics+Context Thesis Proposal 101
  102. 102. Ian Li Personal Informatics+Context Thesis Proposal 102
  103. 103. Mobile Phone Web Site IMPACT 2.0 GPS Context Input Steps-Only Steps-Only Steps-Only Control Steps-Only No Vis Ian Li Personal Informatics+Context Thesis Proposal 103
  104. 104. Setup 35 participants (C1-C35) •  Sedentary. Pre-screened using Stages of Exercise Behavior Change (Marcus et al. 1998) Questionnaires at the end of each phase Ian Li Personal Informatics+Context Thesis Proposal 104
  105. 105. Baseline Phase Intervention Phase Control Control IMPACT 2.0 Steps-Only 1 2 3 4 5 6 7 8 Ian Li Personal Informatics+Context Thesis Proposal 105
  106. 106. Results Complaints were not about the tedium of writing things down, but about having to carry multiple devices. •  “I would not like carrying two devices (GPS and phone), that was too much.” C30 •  “I would use [the prototype] if I could use the software on my own cell phone.” C17 Ian Li Personal Informatics+Context Thesis Proposal 106
  107. 107. Awareness of factors increased for all groups between the phases 32,./2*" 4.)5(67,*8" -9:;3<"=#>" $" !"#$%&%''()*(+#,-)$'( %#$" %" !#$" !" &'()*+,)" -,.)/0),12," F[2,32] = 3.98, p = .0547 Ian Li Personal Informatics+Context Thesis Proposal 107
  108. 108. Similar awareness of factors Mentioned Context Mentioned Context Excluding Time IMPACT 2.0 8 out of 11 6 Steps-Only 8 out of 12 3 Control 6 out of 12 5 Ian Li Personal Informatics+Context Thesis Proposal 108
  109. 109. Long-term reflection What is the value of contextual information in the long-term? 6-months later when they were more likely to have forgotten the data Ian Li Personal Informatics+Context Thesis Proposal 109
  110. 110. Follow-Up Interviews Participants: •  Control (5) •  Steps-Only (6) •  IMPACT 2.0 (3) Ian Li Personal Informatics+Context Thesis Proposal 110
  111. 111. Follow-Up Interviews Expressed interest in comparing over long periods of time. Curious about the peaks in physical activity. But only those who collected contextual information had reminders of what happened during those peaks. Ian Li Personal Informatics+Context Thesis Proposal 111
  112. 112. Collection vs. Reflection Short-term Long-term Reflection Reflection Manual GOOD NOT GOOD Collection Automated NOT GOOD GOOD Collection Ian Li Personal Informatics+Context Thesis Proposal 112
  113. 113. Thesis Questions Is a PI system with context better at revealing factors that affect behavior? Automation has an effect: •  In the short term, reduced interaction with context data so not difference in awareness of factors. •  In the long term, users had data to effectively reflect on factors. Ian Li Personal Informatics+Context Thesis Proposal 113
  114. 114. Diary Thesis Questions Prototype user-driven user-driven user-driven How do we build a PI system with context? IMPACT 1.0 Collection user-driven Integration user-driven Reflection system-driven Diary IMPACT 2.0 Prototype combination user-driven system-driven user-driven system-driven user-driven IMPACT 1.0 •  Automation is valuable in the long term, user-driven user-driven system-driven IMPACT 2.0as useful in the short term. but not combination system-driven system-driven Ian Li Personal Informatics+Context Thesis Proposal 114
  115. 115. Thesis Questions Is a PI system with context better at revealing factors that affect behavior? •  Diary Study and IMPACT 1.0: YES
 Context can increase awareness of factors that affect physical activity. •  IMPACT 2.0: DEPENDS
 Automation reduces immediate awareness, but helps with long-term reflection. Ian Li Personal Informatics+Context Thesis Proposal 115
  116. 116. Thesis Questions How do we build a PI system with context? Collection Integration Reflection Diary Need visualization Prototype Support user-driven user-driven user-driven Need to reduce burden IMPACT 1.0 of Collection and user-driven user-driven system-driven Integration stages. Consider the effect of IMPACT 2.0 automation on combination system-driven system-driven immediate awareness. Ian Li Personal Informatics+Context Thesis Proposal 116
  117. 117. Introduction Stage-Based Model of PI Completed Work Diary Study IMPACT 1.0 IMPACT 2.0 Proposed Work Conclusion Ian Li Personal Informatics+Context Thesis Proposal 117
  118. 118. IMPACT 3.0? Ian Li Personal Informatics+Context Thesis Proposal 118
  119. 119. Thesis Questions Is a PI system with context better at revealing factors that affect behavior? •  How do people use context in the visualizations to find factors that affect behavior? •  How do we support comparison between different types of context? •  Infer cause-and-effect? Ian Li Personal Informatics+Context Thesis Proposal 119
  120. 120. Thesis Questions How do we build a PI system with context? •  Reduce the cost of using personal informatics system while increasing awareness of factors that affect physical activity. Ian Li Personal Informatics+Context Thesis Proposal 120
  121. 121. UNI-FACETED vs. MULTI-FACETED uni-faceted multi-faceted Ian Li Personal Informatics+Context Thesis Proposal 121
  122. 122. Collection Integration Reflection Diary Need visualization Prototype Support user-driven user-driven user-driven Need to reduce burden IMPACT 1.0 of Collection and user-driven user-driven system-driven Integration stages. Consider the effect of IMPACT 2.0 automation on combination system-driven system-driven immediate awareness. Design semi- IMPACT 3.0 automated collection combination system-driven system-driven without losing immediate awareness Ian Li Personal Informatics+Context Thesis Proposal 122
  123. 123. PREPARATION COLLECTION INTEGRATION ITERATIVE Forced users to collect three types of contextual information. •  Some of them may not have been useful, i.e. they are incurring a cost in Collection, but not providing a benefit during Reflection. Ian Li Personal Informatics+Context Thesis Proposal 123
  124. 124. PREPARATION COLLECTION INTEGRATION ITERATIVE The prototypes did not support context other than activity, location, and people. •  Weather •  Mood •  Nutrition •  Other data sources: calendar, email Ian Li Personal Informatics+Context Thesis Proposal 124
  125. 125. PREPARATION COLLECTION INTEGRATION ITERATIVE The prototypes did not count other types of physical activity. •  Swimming •  Biking •  Sports Ian Li Personal Informatics+Context Thesis Proposal 125
  126. 126. PREPARATION COLLECTION INTEGRATION ITERATIVE •  Allow users to select factors that is important to them. •  Support factors other than activity, location, and people. •  Count other types of physical activity. Ian Li Personal Informatics+Context Thesis Proposal 126
  127. 127. BARRIERS CASCADE The prototypes experienced several barriers that affected their usage. Subsequent prototypes addressed some of these barriers. Keep these in mind! Ian Li Personal Informatics+Context Thesis Proposal 127
  128. 128. IMPACT 3.0 Requirements 1.  Maintain immediate awareness in semi- automated collection. 2.  Give choices for other types of context and physical activity. 3.  Explore visualizations of context and physical activity. Ian Li Personal Informatics+Context Thesis Proposal 128
  129. 129. 1. Maintain Immediate Awareness Low-cost manual collection where visualizations are shown after input. 
 (ES+feedback, Hsieh et al. 2008) •  Once during the day, the system asks the user to input data manually. After, the user shows visualizations to the user of other automatically collected information. Ian Li Personal Informatics+Context Thesis Proposal 129
  130. 130. 1. Maintain Immediate Awareness Encourage daily use of the visualizations. •  Alert the user of an interesting fact. •  “You were active while walking in the park.” •  Make it easy for users to find what they are looking for. •  Direct users to the graph that would answer their question.
 Ian Li Personal Informatics+Context Thesis Proposal 130
  131. 131. 2. Other types of context and PA Integrate other sources of context •  Online weather information •  Event information from calendars •  Status updates •  Other personal informatics tools (e.g., MoodJam, your.flowingdata) Ian Li Personal Informatics+Context Thesis Proposal 131
  132. 132. 2. Other types of context and PA Allow logging of other physical activity. Equate amount of physical activity with amount of walking •  1 hour of softball = 30 minutes of walking Ian Li Personal Informatics+Context Thesis Proposal 132
  133. 133. Personal Informatics Browser Ian Li Personal Informatics+Context Thesis Proposal 133
  134. 134. 3. Explore Visualizations in Detail Problems occurred in stages before Reflection, now I can explore this stage in detail. •  Visualizations for comparing between instances of physical activity •  Visualizations for making cause-and-effect associations between context and physical activity Ian Li Personal Informatics+Context Thesis Proposal 134
  135. 135. 3. Explore Visualizations in Detail Housework Shopping Same Physical Activity Level
 Different Context Ian Li Personal Informatics+Context Thesis Proposal 135
  136. 136. 3. Explore Visualizations in Detail Office Office Different Physical Activity Level
 Same Context Ian Li Personal Informatics+Context Thesis Proposal 136
  137. 137. Setup 40 participants •  Sedentary and active Questionnaires at the end of each phase Ian Li Personal Informatics+Context Thesis Proposal 137
  138. 138. Baseline Phase Intervention Phase IMPACT 3.0 Control Steps-Only 1 2 3 4 5 6 7 8 Ian Li Personal Informatics+Context Thesis Proposal 138
  139. 139. Awareness Effects Higher awareness of factors that affect physical activity. Maintain immediate awareness even when collection is semi-automated. Increased interest in the visualizations Ian Li Personal Informatics+Context Thesis Proposal 139
  140. 140. Psychological Effects Higher locus of control Higher self-efficacy Self-reports of change in physical activity Ian Li Personal Informatics+Context Thesis Proposal 140
  141. 141. Thesis Questions Is a PI system with context better at revealing factors that affect behavior? •  Deployment of a personal informatics system that has minimal cost in collection without loss in benefit in reflection. •  Exploration of how people use context in visualizations to find factors that affect behavior. Ian Li Personal Informatics+Context Thesis Proposal 141
  142. 142. Thesis Questions How do we build a PI system with context? •  Designs that reduce the cost of using personal informatics system while increasing awareness of factors that affect physical activity. Ian Li Personal Informatics+Context Thesis Proposal 142
  143. 143. Limitation Focus on physical activity. •  PI systems share the same stages. •  Revealing factors that affect behavior benefits the user. •  Diabetes (Frost & Smith 2003) •  Early work on smart meters (Betz 2010) Ian Li Personal Informatics+Context Thesis Proposal 143
  144. 144. Future Work Sharing data. •  Many PI systems allow sharing. •  Explore the quality of discussions when data is shared with context. Ian Li Personal Informatics+Context Thesis Proposal 144
  145. 145. Thesis Questions Is a PI system with context better at revealing factors that affect behavior? •  Showed that context can increase awareness of factors that affect behavior. •  Automation reduces immediate awareness, but helps with long-term reflection. •  Deployed a system that doesnʼt sacrifice long-term for immediate, vice versa. Ian Li Personal Informatics+Context Thesis Proposal 145
  146. 146. Thesis Questions How do we build a PI system with context? •  Created the stage-based model of PI as a framework to analyze PI systems. •  Created prototypes that support context in field studies. •  Identified issues in supporting context and addressed them in subsequent prototypes. Ian Li Personal Informatics+Context Thesis Proposal 146
  147. 147. Schedule 2010 p m co I bi H U C Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Prototype Analysis IMPACT 3.0 Development Deployment Analysis Write Dissertation Ian Li Personal Informatics+Context Thesis Proposal 147
  148. 148. Thank you! To my advisors, Anind Dey and Jodi Forlizzi, and the rest of my committee, Niki Kittur and John Stasko. To people who have helped discussions, pilot studies:
 Gary Hsieh, Scott Davidoff, Erin Walker, Karen Tang, Matt Easterday, Amy Ogan, Amy Hurst, Ruth Wylie, Moira Burke, Matt Lee, Gabi Marcu, Queenie Kravitz, Min Kyung Lee, Turadg Aleahmad, Tawanna Dillahunt, Brian Lim, Chloe Fan, Jenn Marlow, Jason Wiese, Sunyoung Kim, Aubrey Shick, Chris Harrison, Julia Schwarz, Bilge Mutlu, Andy Ko, Johnny Lee, Ido Roll, Jeff Nichols, Jeff Wong, Sara Kiesler, Laura Dabbish, Scott Hudson, Tessa Lau, Jaime Teevan, Fernanda Viegas, Jon Froehlich, UISTʼ09 and UbiCompʼ09 Symposia attendants, Alexandra Carmichael, Gary Wolf, Nathan Yau, Nicholas Felton, Ellie Harrison, Edison Thomaz Ian Li Personal Informatics+Context Thesis Proposal 148

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