SlideShare une entreprise Scribd logo
1  sur  35
Télécharger pour lire hors ligne
Display	
  Ma*ers:	
  	
  
A	
  Test	
  of	
  Visual	
  Display	
  Op6ons	
  in	
  a	
  
               Web-­‐Based	
  Survey	
  
   Jennifer	
  C.	
  Romano	
  Bergstrom1,	
  Jennifer	
  M.	
  Chen1,	
  	
  
                Timothy	
  R.	
  Gilbert2	
  &	
  Ma*	
  Jans1	
  
                1	
  Center	
  for	
  Survey	
  Measurement	
  
                 2	
  Demographic	
  Surveys	
  Division	
  


                           U.S.	
  Census	
  Bureau	
  
                       AAPOR	
  66th	
  Annual	
  Conference	
  	
  
                                 May	
  13,	
  2011	
  
Current	
  Survey	
  Environment	
  
•  Increasing	
  number	
  of	
  surveys	
  online	
  
•  Design	
  considera6ons	
  
   –  Naviga6on	
  methods	
  
   –  Presenta6on	
  of	
  response	
  op6ons	
  




                                                         2	
  
Current	
  Survey	
  Environment	
  
•  Increasing	
  number	
  of	
  surveys	
  online	
  
•  Design	
  considera6ons	
  
   –  Naviga6on	
  methods	
  
   –  Presenta6on	
  of	
  response	
  op6ons	
  




                                                         3	
  
Background	
  on	
  Next	
  and	
  Previous	
  
•  Next	
  should	
  be	
  on	
  the	
  leU	
  
    –  Reduces	
  the	
  amount	
  of	
  6me	
  to	
  move	
  cursor	
  to	
  
       primary	
  naviga6on	
  bu*on	
  (Couper,	
  2008)	
  
    –  Frequency	
  of	
  use	
  (Dillman	
  et	
  al.,	
  2009;	
  Faulkner,	
  
       1998;	
  Koyani	
  et	
  al.,	
  2004;	
  Wroblewski,	
  2008)	
  




                                                                                    4	
  
Background	
  on	
  Next	
  and	
  Previous	
  
•  Previous	
  should	
  be	
  on	
  the	
  leU	
  
    –  Web	
  applica6on	
  order	
  
    –  Everyday	
  devices	
  
    –  Logical	
  reading	
  order	
  




                                                      5	
  
Background	
  on	
  Next	
  and	
  Previous	
  
•  Previous	
  should	
  be	
  on	
  the	
  leU	
  
    –  Web	
  applica6on	
  order	
  
    –  Everyday	
  devices	
  
    –  Logical	
  reading	
  order	
  




                                                      6	
  
Background	
  on	
  Next	
  and	
  Previous	
  
•  Previous	
  should	
  be	
  below	
  Next	
  
   –  Bu*ons	
  can	
  be	
  closer	
  (Couper	
  et	
  al.,	
  2011;	
  
      Wroblewski,	
  2008)	
  




                                                                            7	
  
Background	
  on	
  Long	
  Lists	
  
•  One	
  column	
  
   –  Visually	
  appear	
  to	
  belong	
  to	
  one	
  group	
  
   –  When	
  there	
  are	
  two	
  columns,	
  2nd	
  one	
  may	
  not	
  be	
  
      seen	
  (Smyth	
  et	
  al.,	
  1997)	
  
•  Two	
  columns:	
  Double	
  banked	
  
   –  No	
  scrolling	
  
   –  See	
  all	
  op6ons	
  at	
  once	
  
   –  Appears	
  shorter	
  

                                                                                      8	
  
Measuring	
  “Best”	
  Design	
  
•  Typical:	
  In	
  the	
  Field	
  
     –  Drop-­‐off	
  rates	
  
     –  Keystrokes	
  
     –  Survey	
  comple6on	
  6mes	
  
•  Our	
  Study:	
  In	
  the	
  Lab	
  	
  
     –  User	
  sa6sfac6on	
  
     –  Eye-­‐tracking	
  data	
  
     –  Usability	
  metrics	
  

                                                 9	
  
Usability	
  
•  The	
  extent	
  to	
  which	
  a	
  product	
  can	
  be	
  used	
  by	
  
   specified	
  users	
  to	
  achieve	
  specified	
  goals	
  with	
  
   effec6veness,	
  efficiency,	
  and	
  sa6sfac6on.	
  ISO/
   TR	
  16982:2002	
  
•  For	
  web-­‐based	
  surveys,	
  the	
  design	
  must	
  
    –  Meet	
  respondents’	
  needs	
  
    –  Facilitate	
  easy	
  comple6on	
  
    –  Provide	
  a	
  sa6sfying	
  experience	
  
    –  Reduce	
  respondent	
  burden	
  
    –  Produce	
  high-­‐quality	
  data	
  
                                                                             10	
  
Na6onal	
  Survey	
  of	
  College	
  Graduates	
  
                     (NSCG)	
  
•    Collects	
  educa6on	
  and	
  job	
  informa6on	
  
•    Respondents	
  have	
  Bachelor’s	
  degree	
  
•    Was	
  available	
  in	
  PAPI	
  and	
  CATI	
  
•    Usability	
  study	
  for	
  a	
  web-­‐based	
  self-­‐
     administered	
  instrument	
  




                                                                11	
  
Method 	
  	
  
•    Lab-­‐based	
  usability	
  study	
  
•    TA	
  read	
  introduc6on	
  and	
  leU	
  le*er	
  on	
  desk	
  
•    Separate	
  rooms	
  
•    R	
  read	
  le*er	
  and	
  logged	
  in	
  to	
  survey	
  
•    Think	
  Aloud	
  (Olmsted-­‐Hawala	
  et	
  al.,	
  2010)	
  
•    Eye	
  Tracking	
  
•    Sa6sfac6on	
  Ques6onnaire	
  
•    Debriefing	
  

                                                                          12	
  
Par6cipants	
  


Gender	
     N	
      Age	
             N	
      Educa.on	
       N	
  
Male	
       14	
     <	
  30	
         8	
      Bachelor’s	
     21	
  
Female	
     16	
     31-­‐45	
         7	
      Master’s	
       6	
  
                      46-­‐60	
         10	
     Ph.D.	
          3	
  
                      >	
  60	
  	
     5	
  
                      Mean:	
  46	
  




                                                                           13	
  
Eye-­‐Tracking	
  Apparatus	
  




14	
  
Ques6ons	
  Eye	
  Tracking	
  Can	
  Answer	
  
•  Do	
  respondents	
  look	
  at	
  Next	
  and	
  Previous?	
  
•  What	
  do	
  they	
  look	
  at	
  first?	
  
•  Is	
  it	
  distrac6ng	
  when	
  Previous	
  is	
  located	
  in	
  a	
  
   par6cular	
  place	
  on	
  the	
  screen?	
  
•  How	
  long	
  does	
  it	
  take	
  respondents	
  to	
  see	
  the	
  
   Next	
  bu*on?	
  
•  Does	
  presenta6on	
  of	
  long	
  lists	
  affect	
  what	
  
   users	
  look	
  at	
  on	
  the	
  list?	
  
                                                                                15	
  
Previous	
  and	
  Next	
  Bu*ons	
  




16	
  
One	
  Column	
  vs.	
  Two	
  Columns	
  




17	
  
4	
  Versions	
  
            N_P1	
                                    N_P2	
  
  Next	
  bu*on	
  on	
  leU,	
  	
         Next	
  bu*on	
  on	
  leU,	
  	
  
  1-­‐column	
  job	
  code	
               2-­‐column	
  job	
  code	
  
            PN1	
                                     PN2	
  
Previous	
  bu*on	
  on	
  leU,	
  	
     Previous	
  bu*on	
  on	
  leU,	
  	
  
  1-­‐column	
  job	
  code	
               2-­‐column	
  job	
  code	
  




                                                                                18	
  
Results:	
  Sa6sfac6on	
  I	
  




                           *	
  p	
  <	
  0.0001	
  


                                                       19	
  
8.5	
  
                                               Results:	
  Sa6sfac6on	
  II	
  
                                                                                                                  8.5	
  
Mean	
  Sa.sfac.on	
  




                                                                                         Mean	
  Sa.sfac.on	
  
                            8	
  
                                                                                                                       8	
  
    Ra.ng	
  


                         7.5	
  




                                                                                             Ra.ng	
  
                                                                                                                  7.5	
  
                            7	
                                                                                        7	
  
                         6.5	
                                                                                    6.5	
  
                            6	
                                                                                        6	
  
                                     Mean	
            N_P	
             PN	
                                                  Mean	
          N_P	
         PN	
  
                                    Overall	
  reac6on	
  to	
  the	
  survey:	
  	
                                     Informa6on	
  displayed	
  on	
  the	
  screens:	
  	
  
                                    terrible	
  –	
  wonderful.	
  p	
  <	
  0.05.	
                                        inadequate	
  –	
  adequate.	
  p	
  =	
  0.07.	
  	
  
                         8.5	
  
                                                                                                                      8.5	
  
Mean	
  Sa.sfac.on	
  




                                                                                             Mean	
  Sa.sfac.on	
  
                            8	
  
                                                                                                                          8	
  
    Ra.ng	
  




                         7.5	
  



                                                                                                 Ra.ng	
  
                                                                                                                      7.5	
  
                            7	
                                                                                           7	
  
                         6.5	
                                                                                        6.5	
  
                            6	
                                                                                           6	
  
                                Mean	
              N_P	
                 PN	
                                                        Mean	
               N_P	
                PN	
  
                         Arrangement	
  of	
  informa6on	
  on	
  the	
  screens:	
                                                  Forward	
  naviga6on:	
  	
  
                                 illogical	
  –	
  logical.	
  p	
  =	
  0.19.	
                                                  impossible	
  –	
  easy.	
  p	
  =	
  0.13.	
  	
  


                                                                                                                                                                                         20	
  
Eye	
  Tracking:	
  Next	
  /	
  Previous	
  




21	
  
Eye	
  Tracking:	
  Previous	
  /	
  Next	
  




22	
  
 Eye	
  Tracking:	
  N_P	
  vs.	
  PN	
  
•  Par6cipants	
  looked	
  at	
  Previous	
  and	
  Next	
  in	
  PN	
  
   condi6ons	
  
•  Many	
  par6cipants	
  looked	
  at	
  Previous	
  in	
  the	
  
   N_P	
  condi6ons	
  
    –  Consistent	
  with	
  Couper	
  et	
  al.	
  (2011):	
  Previous	
  gets	
  
       used	
  more	
  when	
  it	
  is	
  on	
  the	
  right	
  




                                                                                 23	
  
 Eye	
  Tracking:	
  Time	
  to	
  First	
  Fixa6on	
  
                         8	
  
                      7.5	
  
                         7	
  
                      6.5	
  
        Seconds	
  




                         6	
                                                                     	
  	
  PN	
  
                      5.5	
                                                                      	
  	
  N_P	
  

                         5	
  
                      4.5	
  
                         4	
  
                                          Next	
                         Previous	
  

                      Mean	
  6me	
  to	
  first	
  look	
  at	
  the	
  naviga6on	
  bu*on	
  


                                                                                                                   24	
  
 N_P	
  vs.	
  PN:	
  Respondent	
  Debriefing	
  
•  N_P	
  version	
  
    –  Counterintui6ve	
  
    –  Don’t	
  like	
  the	
  “bu*ons	
  being	
  flipped.”	
  
    –  Next	
  on	
  the	
  leU	
  is	
  “really	
  irrita6ng.”	
  
    –  Order	
  is	
  “opposite	
  of	
  what	
  most	
  people	
  would	
  
       design.”	
  
•  PN	
  version	
  
    –  “Pre*y	
  standard,	
  like	
  what	
  you	
  typically	
  see.”	
  
    –  The	
  loca6on	
  is	
  “logical.”	
  

                                                                               25	
  
 1	
  Column	
  vs.	
  2	
  Column	
  




                                            26	
  
Time	
  to	
  First	
  Fixa6on	
  
              25	
  


              20	
  


              15	
  
Seconds	
  




                                                                                                 1	
  col	
   *	
  p	
  <	
  0.01	
  
              10	
                                                                               2	
  col	
  


                5	
  


                0	
  
                            First	
  half	
  of	
  list	
     Second	
  half	
  of	
  list	
  




                                                                                                                              27	
  
Total	
  Number	
  of	
  Fixa6ons	
  
                               40	
  

                               35	
  

                               30	
  
Number	
  of	
  Fixa.ons	
  




                               25	
  

                               20	
                                                                           1	
  col	
  
                               15	
                                                                           2	
  col	
  

                               10	
  

                                 5	
  

                                 0	
  
                                         First	
  half	
  of	
  list	
     Second	
  half	
  of	
  list	
  




                                                                                                                             28	
  
Time	
  to	
  Complete	
  Item	
  
              120	
  



              100	
  



                80	
  
Seconds	
  




                60	
  
                                                               1	
  col	
  
                                                               2	
  col	
  
                40	
  



                20	
  



                  0	
  

                           Mean	
          Min	
     Max	
  




                                                                              29	
  
 1	
  Col.	
  vs.	
  2	
  Col.:	
  Debriefing	
  
•  25	
  had	
  a	
  preference	
  
    –  6	
  preferred	
  one	
  column	
  
        •  They	
  had	
  received	
  the	
  one-­‐column	
  version	
  
    –  19	
  preferred	
  2	
  columns	
  
        •  7	
  had	
  received	
  the	
  one-­‐column	
  version	
  
        •  Prefer	
  not	
  to	
  scroll	
  
        •  Want	
  to	
  see	
  and	
  compare	
  everything	
  at	
  once	
  
        •  It	
  is	
  easier	
  to	
  “look	
  through,”	
  to	
  scan,	
  to	
  read	
  
        •  Re	
  one	
  column,	
  “How	
  long	
  is	
  this	
  list	
  going	
  to	
  be?”	
  


                                                                                                   30	
  
Conclusions	
  	
  
•  Par6cipants	
  were	
  more	
  sa6sfied	
  when	
  
   Previous	
  was	
  on	
  the	
  leU.	
  
•  Par6cipants	
  preferred	
  the	
  long	
  lists	
  in	
  two	
  
   columns.	
  
•  Par6cipants	
  looked	
  at	
  the	
  first	
  half	
  of	
  the	
  list	
  
   sooner	
  than	
  the	
  second	
  half	
  when	
  in	
  one	
  
   column.	
  
•  Par6cipants	
  looked	
  at	
  the	
  second	
  half	
  of	
  the	
  
   list	
  more	
  when	
  it	
  was	
  in	
  two	
  columns.	
  

                                                                                 31	
  
Bigger	
  Picture:	
  Recap	
  on	
  Next	
  and	
  Previous	
  
  •  Next	
  should	
  be	
  on	
  the	
  leU	
  
       –  Reduces	
  the	
  amount	
  of	
  6me	
  to	
  move	
  cursor	
  to	
  primary	
  
          naviga6on	
  bu*on	
  
       –  Tab	
  order	
  
       –  Frequency	
  of	
  use	
  
  •  Previous	
  should	
  be	
  on	
  the	
  leU	
  
       –  Web	
  applica6on	
  order	
  
       –  Everyday	
  devices	
  
       –  Logical	
  reading	
  order	
  
       –  People	
  are	
  more	
  sa6sfied	
  
       –  It	
  takes	
  longer	
  to	
  first	
  look	
  at	
  Previous	
  when	
  on	
  the	
  right	
  

                                                                                                            32	
  
Bigger	
  Picture:	
  Recap	
  on	
  Long	
  Lists	
  
•  One	
  column	
  
   –  Visually	
  appear	
  to	
  belong	
  to	
  one	
  group	
  
•  Two	
  columns:	
  Double	
  banked	
  
   –  No	
  scrolling	
  
   –  See	
  all	
  op6ons	
  at	
  once	
  
   –  Appears	
  shorter	
  
   –  Second	
  column	
  may	
  not	
  be	
  seen	
  
   –  People	
  look	
  at	
  the	
  second	
  half	
  more	
  
   –  People	
  look	
  at	
  the	
  first	
  half	
  sooner	
  when	
  it	
  is	
  in	
  one	
  
      column	
  
   –  People	
  prefer	
  two	
  columns	
  

                                                                                                   33	
  
Future	
  Direc6ons	
  	
  
•  This	
  is	
  just	
  a	
  small	
  nugget.	
  
•  N_P	
  vs.	
  P_N	
  study	
  in	
  progress	
  
    –  Same	
  layout	
  
    –  No	
  skip	
  pa*erns	
  
    –  Efficiency	
  measure	
  
•  Long	
  list	
  of	
  items	
  condi6on	
  
    –  Which	
  items	
  do	
  people	
  pick?	
  
    –  Alphabe6zed	
  vs.	
  random	
  order	
  

                                                      34	
  
Thank	
  you!	
  
For	
  more	
  informa6on,	
  please	
  contact	
  
       Jennifer	
  Romano	
  Bergstrom	
  
   Jennifer.C.Romano@gmail.com	
  
      Jennifer.Romano@census.gov	
  
          Twi*er:	
  @romanocog	
  




                                                      35	
  

Contenu connexe

Similaire à Display Matters: A Test of Visual Display Options in a Web-Based Survey

ION Ljubljana - Nathalie Trenaman: World IPv6 Launch and RIPE Atlas Visualisa...
ION Ljubljana - Nathalie Trenaman: World IPv6 Launch and RIPE Atlas Visualisa...ION Ljubljana - Nathalie Trenaman: World IPv6 Launch and RIPE Atlas Visualisa...
ION Ljubljana - Nathalie Trenaman: World IPv6 Launch and RIPE Atlas Visualisa...Deploy360 Programme (Internet Society)
 
RIPE NCC Measurements Tools
RIPE NCC Measurements ToolsRIPE NCC Measurements Tools
RIPE NCC Measurements ToolsRIPE NCC
 
Psychophysiology and Eyetracking in User Experience
Psychophysiology and Eyetracking in User ExperiencePsychophysiology and Eyetracking in User Experience
Psychophysiology and Eyetracking in User ExperienceDan Berlin
 
Benchmark Tutorial -- IV - Participation
Benchmark Tutorial -- IV - ParticipationBenchmark Tutorial -- IV - Participation
Benchmark Tutorial -- IV - Participationjdbess
 
2012 icse program comprehension
2012 icse program comprehension2012 icse program comprehension
2012 icse program comprehensionWalid Maalej
 
Summary of PERC activity.doc.doc
Summary of PERC activity.doc.docSummary of PERC activity.doc.doc
Summary of PERC activity.doc.docbutest
 
Tutorial 12 (click models)
Tutorial 12 (click models)Tutorial 12 (click models)
Tutorial 12 (click models)Kira
 
Assessment Model for Opportunistic Routing
Assessment Model for Opportunistic RoutingAssessment Model for Opportunistic Routing
Assessment Model for Opportunistic RoutingWaldir Moreira
 
Facilitating IPv6 Deployment
Facilitating IPv6 DeploymentFacilitating IPv6 Deployment
Facilitating IPv6 DeploymentRIPE NCC
 
Uk Research Infrastructure Workshop E-infrastructure Juan Bicarregui
Uk Research Infrastructure Workshop E-infrastructure Juan BicarreguiUk Research Infrastructure Workshop E-infrastructure Juan Bicarregui
Uk Research Infrastructure Workshop E-infrastructure Juan BicarreguiInnovate UK
 
Benchmark Education
Benchmark EducationBenchmark Education
Benchmark Educationjdbess
 
RIPE Labs Operator Tools, Ideas, Analysis
RIPE Labs Operator Tools, Ideas, AnalysisRIPE Labs Operator Tools, Ideas, Analysis
RIPE Labs Operator Tools, Ideas, AnalysisRIPE NCC
 
White Box Testing: It’s Not Just for Developers Any More
White Box Testing: It’s Not Just for Developers Any MoreWhite Box Testing: It’s Not Just for Developers Any More
White Box Testing: It’s Not Just for Developers Any MoreTechWell
 
Jillian ms defense-4-14-14-ja-novideo
Jillian ms defense-4-14-14-ja-novideoJillian ms defense-4-14-14-ja-novideo
Jillian ms defense-4-14-14-ja-novideoJillian Aurisano
 
Discovering emerging effects in Learning Networks with simulations Hendrik Dr...
Discovering emerging effects in Learning Networks with simulations Hendrik Dr...Discovering emerging effects in Learning Networks with simulations Hendrik Dr...
Discovering emerging effects in Learning Networks with simulations Hendrik Dr...Hendrik Drachsler
 
OpenNeuro: a free online platform for sharing and analysis of neuroimaging data
OpenNeuro: a free online platform for sharing and analysis of neuroimaging dataOpenNeuro: a free online platform for sharing and analysis of neuroimaging data
OpenNeuro: a free online platform for sharing and analysis of neuroimaging dataKrzysztof Gorgolewski
 
On the value of sampling and pruning for search-based software engineering
On the value of sampling and pruning for search-based software engineeringOn the value of sampling and pruning for search-based software engineering
On the value of sampling and pruning for search-based software engineeringJianfeng Chen
 
Comparing IPv6 and IPv4 Performance, by John Berg [APNIC 38 / IPv6 Plenary]
Comparing IPv6 and IPv4 Performance, by John Berg [APNIC 38 / IPv6 Plenary]Comparing IPv6 and IPv4 Performance, by John Berg [APNIC 38 / IPv6 Plenary]
Comparing IPv6 and IPv4 Performance, by John Berg [APNIC 38 / IPv6 Plenary]APNIC
 
From Zero to Nextflow 2017
From Zero to Nextflow 2017From Zero to Nextflow 2017
From Zero to Nextflow 2017Luca Cozzuto
 

Similaire à Display Matters: A Test of Visual Display Options in a Web-Based Survey (20)

ION Ljubljana - Nathalie Trenaman: World IPv6 Launch and RIPE Atlas Visualisa...
ION Ljubljana - Nathalie Trenaman: World IPv6 Launch and RIPE Atlas Visualisa...ION Ljubljana - Nathalie Trenaman: World IPv6 Launch and RIPE Atlas Visualisa...
ION Ljubljana - Nathalie Trenaman: World IPv6 Launch and RIPE Atlas Visualisa...
 
RIPE NCC Measurements Tools
RIPE NCC Measurements ToolsRIPE NCC Measurements Tools
RIPE NCC Measurements Tools
 
Psychophysiology and Eyetracking in User Experience
Psychophysiology and Eyetracking in User ExperiencePsychophysiology and Eyetracking in User Experience
Psychophysiology and Eyetracking in User Experience
 
Benchmark Tutorial -- IV - Participation
Benchmark Tutorial -- IV - ParticipationBenchmark Tutorial -- IV - Participation
Benchmark Tutorial -- IV - Participation
 
Mca sem1syll
Mca sem1syllMca sem1syll
Mca sem1syll
 
2012 icse program comprehension
2012 icse program comprehension2012 icse program comprehension
2012 icse program comprehension
 
Summary of PERC activity.doc.doc
Summary of PERC activity.doc.docSummary of PERC activity.doc.doc
Summary of PERC activity.doc.doc
 
Tutorial 12 (click models)
Tutorial 12 (click models)Tutorial 12 (click models)
Tutorial 12 (click models)
 
Assessment Model for Opportunistic Routing
Assessment Model for Opportunistic RoutingAssessment Model for Opportunistic Routing
Assessment Model for Opportunistic Routing
 
Facilitating IPv6 Deployment
Facilitating IPv6 DeploymentFacilitating IPv6 Deployment
Facilitating IPv6 Deployment
 
Uk Research Infrastructure Workshop E-infrastructure Juan Bicarregui
Uk Research Infrastructure Workshop E-infrastructure Juan BicarreguiUk Research Infrastructure Workshop E-infrastructure Juan Bicarregui
Uk Research Infrastructure Workshop E-infrastructure Juan Bicarregui
 
Benchmark Education
Benchmark EducationBenchmark Education
Benchmark Education
 
RIPE Labs Operator Tools, Ideas, Analysis
RIPE Labs Operator Tools, Ideas, AnalysisRIPE Labs Operator Tools, Ideas, Analysis
RIPE Labs Operator Tools, Ideas, Analysis
 
White Box Testing: It’s Not Just for Developers Any More
White Box Testing: It’s Not Just for Developers Any MoreWhite Box Testing: It’s Not Just for Developers Any More
White Box Testing: It’s Not Just for Developers Any More
 
Jillian ms defense-4-14-14-ja-novideo
Jillian ms defense-4-14-14-ja-novideoJillian ms defense-4-14-14-ja-novideo
Jillian ms defense-4-14-14-ja-novideo
 
Discovering emerging effects in Learning Networks with simulations Hendrik Dr...
Discovering emerging effects in Learning Networks with simulations Hendrik Dr...Discovering emerging effects in Learning Networks with simulations Hendrik Dr...
Discovering emerging effects in Learning Networks with simulations Hendrik Dr...
 
OpenNeuro: a free online platform for sharing and analysis of neuroimaging data
OpenNeuro: a free online platform for sharing and analysis of neuroimaging dataOpenNeuro: a free online platform for sharing and analysis of neuroimaging data
OpenNeuro: a free online platform for sharing and analysis of neuroimaging data
 
On the value of sampling and pruning for search-based software engineering
On the value of sampling and pruning for search-based software engineeringOn the value of sampling and pruning for search-based software engineering
On the value of sampling and pruning for search-based software engineering
 
Comparing IPv6 and IPv4 Performance, by John Berg [APNIC 38 / IPv6 Plenary]
Comparing IPv6 and IPv4 Performance, by John Berg [APNIC 38 / IPv6 Plenary]Comparing IPv6 and IPv4 Performance, by John Berg [APNIC 38 / IPv6 Plenary]
Comparing IPv6 and IPv4 Performance, by John Berg [APNIC 38 / IPv6 Plenary]
 
From Zero to Nextflow 2017
From Zero to Nextflow 2017From Zero to Nextflow 2017
From Zero to Nextflow 2017
 

Plus de Jennifer Romano Bergstrom

Processing Speed and Vocabulary are Related to Older Adults' Internet Experie...
Processing Speed and Vocabulary are Related to Older Adults' Internet Experie...Processing Speed and Vocabulary are Related to Older Adults' Internet Experie...
Processing Speed and Vocabulary are Related to Older Adults' Internet Experie...Jennifer Romano Bergstrom
 
Eye Tracking the UX of Mobile: What You Need to Know
Eye Tracking the UX of Mobile: What You Need to KnowEye Tracking the UX of Mobile: What You Need to Know
Eye Tracking the UX of Mobile: What You Need to KnowJennifer Romano Bergstrom
 
Unbiased Methods to Understand the User Experience
Unbiased Methods to Understand the User ExperienceUnbiased Methods to Understand the User Experience
Unbiased Methods to Understand the User ExperienceJennifer Romano Bergstrom
 
User-Centered Research on the Paying for College Website and Tools - EDUI 2014
User-Centered Research on the Paying for College Website and Tools - EDUI 2014User-Centered Research on the Paying for College Website and Tools - EDUI 2014
User-Centered Research on the Paying for College Website and Tools - EDUI 2014Jennifer Romano Bergstrom
 
Web Survey and Forms Usability Design & Testing
Web Survey and Forms Usability Design & TestingWeb Survey and Forms Usability Design & Testing
Web Survey and Forms Usability Design & TestingJennifer Romano Bergstrom
 
Improving Forms with User Experience Testing and Eye Tracking
Improving Forms with User Experience Testing and Eye TrackingImproving Forms with User Experience Testing and Eye Tracking
Improving Forms with User Experience Testing and Eye TrackingJennifer Romano Bergstrom
 
Eye Tracking the User Experience of Mobile: What You Need to Know
Eye Tracking the User Experience of Mobile: What You Need to KnowEye Tracking the User Experience of Mobile: What You Need to Know
Eye Tracking the User Experience of Mobile: What You Need to KnowJennifer Romano Bergstrom
 
Launch With Confidence! Integrate UX Research Throughout Development
Launch With Confidence! Integrate UX Research Throughout DevelopmentLaunch With Confidence! Integrate UX Research Throughout Development
Launch With Confidence! Integrate UX Research Throughout DevelopmentJennifer Romano Bergstrom
 
Usable Government Forms and Surveys: Best Practices for Design (from MoDevGov)
Usable Government Forms and Surveys: Best Practices for Design (from MoDevGov)Usable Government Forms and Surveys: Best Practices for Design (from MoDevGov)
Usable Government Forms and Surveys: Best Practices for Design (from MoDevGov)Jennifer Romano Bergstrom
 
Unifying the UX of a Survey Across Multiple Devices (MoDevEast 2013)
Unifying the UX of a Survey Across Multiple Devices (MoDevEast 2013)Unifying the UX of a Survey Across Multiple Devices (MoDevEast 2013)
Unifying the UX of a Survey Across Multiple Devices (MoDevEast 2013)Jennifer Romano Bergstrom
 
Effects of Age and Think-Aloud Protocol on Eye-Tracking Data and Usability Me...
Effects of Age and Think-Aloud Protocol on Eye-Tracking Data and Usability Me...Effects of Age and Think-Aloud Protocol on Eye-Tracking Data and Usability Me...
Effects of Age and Think-Aloud Protocol on Eye-Tracking Data and Usability Me...Jennifer Romano Bergstrom
 

Plus de Jennifer Romano Bergstrom (17)

Processing Speed and Vocabulary are Related to Older Adults' Internet Experie...
Processing Speed and Vocabulary are Related to Older Adults' Internet Experie...Processing Speed and Vocabulary are Related to Older Adults' Internet Experie...
Processing Speed and Vocabulary are Related to Older Adults' Internet Experie...
 
User-Centered Design of Forms and Surveys
User-Centered Design of Forms and SurveysUser-Centered Design of Forms and Surveys
User-Centered Design of Forms and Surveys
 
Eye Tracking the UX of Mobile: What You Need to Know
Eye Tracking the UX of Mobile: What You Need to KnowEye Tracking the UX of Mobile: What You Need to Know
Eye Tracking the UX of Mobile: What You Need to Know
 
UXPA2015 sponsorship prospectus
UXPA2015 sponsorship prospectusUXPA2015 sponsorship prospectus
UXPA2015 sponsorship prospectus
 
Unbiased Methods to Understand the User Experience
Unbiased Methods to Understand the User ExperienceUnbiased Methods to Understand the User Experience
Unbiased Methods to Understand the User Experience
 
Benchmarking Usability Performance
Benchmarking Usability PerformanceBenchmarking Usability Performance
Benchmarking Usability Performance
 
User-Centered Research on the Paying for College Website and Tools - EDUI 2014
User-Centered Research on the Paying for College Website and Tools - EDUI 2014User-Centered Research on the Paying for College Website and Tools - EDUI 2014
User-Centered Research on the Paying for College Website and Tools - EDUI 2014
 
Web Survey and Forms Usability Design & Testing
Web Survey and Forms Usability Design & TestingWeb Survey and Forms Usability Design & Testing
Web Survey and Forms Usability Design & Testing
 
Improving Forms with User Experience Testing and Eye Tracking
Improving Forms with User Experience Testing and Eye TrackingImproving Forms with User Experience Testing and Eye Tracking
Improving Forms with User Experience Testing and Eye Tracking
 
Eye Tracking the User Experience of Mobile: What You Need to Know
Eye Tracking the User Experience of Mobile: What You Need to KnowEye Tracking the User Experience of Mobile: What You Need to Know
Eye Tracking the User Experience of Mobile: What You Need to Know
 
Launch With Confidence! Integrate UX Research Throughout Development
Launch With Confidence! Integrate UX Research Throughout DevelopmentLaunch With Confidence! Integrate UX Research Throughout Development
Launch With Confidence! Integrate UX Research Throughout Development
 
So much UX data! Now what?
So much UX data! Now what?So much UX data! Now what?
So much UX data! Now what?
 
Usable Government Forms and Surveys: Best Practices for Design (from MoDevGov)
Usable Government Forms and Surveys: Best Practices for Design (from MoDevGov)Usable Government Forms and Surveys: Best Practices for Design (from MoDevGov)
Usable Government Forms and Surveys: Best Practices for Design (from MoDevGov)
 
The UX of Social Media
The UX of Social MediaThe UX of Social Media
The UX of Social Media
 
Unifying the UX of a Survey Across Multiple Devices (MoDevEast 2013)
Unifying the UX of a Survey Across Multiple Devices (MoDevEast 2013)Unifying the UX of a Survey Across Multiple Devices (MoDevEast 2013)
Unifying the UX of a Survey Across Multiple Devices (MoDevEast 2013)
 
UX Fundamentals
UX FundamentalsUX Fundamentals
UX Fundamentals
 
Effects of Age and Think-Aloud Protocol on Eye-Tracking Data and Usability Me...
Effects of Age and Think-Aloud Protocol on Eye-Tracking Data and Usability Me...Effects of Age and Think-Aloud Protocol on Eye-Tracking Data and Usability Me...
Effects of Age and Think-Aloud Protocol on Eye-Tracking Data and Usability Me...
 

Dernier

办理学位证(TheAuckland证书)新西兰奥克兰大学毕业证成绩单原版一比一
办理学位证(TheAuckland证书)新西兰奥克兰大学毕业证成绩单原版一比一办理学位证(TheAuckland证书)新西兰奥克兰大学毕业证成绩单原版一比一
办理学位证(TheAuckland证书)新西兰奥克兰大学毕业证成绩单原版一比一Fi L
 
2024新版美国旧金山州立大学毕业证成绩单pdf电子版制作修改#毕业文凭制作#回国入职#diploma#degree
2024新版美国旧金山州立大学毕业证成绩单pdf电子版制作修改#毕业文凭制作#回国入职#diploma#degree2024新版美国旧金山州立大学毕业证成绩单pdf电子版制作修改#毕业文凭制作#回国入职#diploma#degree
2024新版美国旧金山州立大学毕业证成绩单pdf电子版制作修改#毕业文凭制作#回国入职#diploma#degreeyuu sss
 
Call Girls Aslali 7397865700 Ridhima Hire Me Full Night
Call Girls Aslali 7397865700 Ridhima Hire Me Full NightCall Girls Aslali 7397865700 Ridhima Hire Me Full Night
Call Girls Aslali 7397865700 Ridhima Hire Me Full Nightssuser7cb4ff
 
Unveiling the Future: Columbus, Ohio Condominiums Through the Lens of 3D Arch...
Unveiling the Future: Columbus, Ohio Condominiums Through the Lens of 3D Arch...Unveiling the Future: Columbus, Ohio Condominiums Through the Lens of 3D Arch...
Unveiling the Future: Columbus, Ohio Condominiums Through the Lens of 3D Arch...Yantram Animation Studio Corporation
 
shot list for my tv series two steps back
shot list for my tv series two steps backshot list for my tv series two steps back
shot list for my tv series two steps back17lcow074
 
DAKSHIN BIHAR GRAMIN BANK: REDEFINING THE DIGITAL BANKING EXPERIENCE WITH A U...
DAKSHIN BIHAR GRAMIN BANK: REDEFINING THE DIGITAL BANKING EXPERIENCE WITH A U...DAKSHIN BIHAR GRAMIN BANK: REDEFINING THE DIGITAL BANKING EXPERIENCE WITH A U...
DAKSHIN BIHAR GRAMIN BANK: REDEFINING THE DIGITAL BANKING EXPERIENCE WITH A U...Rishabh Aryan
 
MT. Marseille an Archipelago. Strategies for Integrating Residential Communit...
MT. Marseille an Archipelago. Strategies for Integrating Residential Communit...MT. Marseille an Archipelago. Strategies for Integrating Residential Communit...
MT. Marseille an Archipelago. Strategies for Integrating Residential Communit...katerynaivanenko1
 
(办理学位证)埃迪斯科文大学毕业证成绩单原版一比一
(办理学位证)埃迪斯科文大学毕业证成绩单原版一比一(办理学位证)埃迪斯科文大学毕业证成绩单原版一比一
(办理学位证)埃迪斯科文大学毕业证成绩单原版一比一Fi sss
 
西北大学毕业证学位证成绩单-怎么样办伪造
西北大学毕业证学位证成绩单-怎么样办伪造西北大学毕业证学位证成绩单-怎么样办伪造
西北大学毕业证学位证成绩单-怎么样办伪造kbdhl05e
 
毕业文凭制作#回国入职#diploma#degree澳洲弗林德斯大学毕业证成绩单pdf电子版制作修改#毕业文凭制作#回国入职#diploma#degree
毕业文凭制作#回国入职#diploma#degree澳洲弗林德斯大学毕业证成绩单pdf电子版制作修改#毕业文凭制作#回国入职#diploma#degree 毕业文凭制作#回国入职#diploma#degree澳洲弗林德斯大学毕业证成绩单pdf电子版制作修改#毕业文凭制作#回国入职#diploma#degree
毕业文凭制作#回国入职#diploma#degree澳洲弗林德斯大学毕业证成绩单pdf电子版制作修改#毕业文凭制作#回国入职#diploma#degree ttt fff
 
办理(USYD毕业证书)澳洲悉尼大学毕业证成绩单原版一比一
办理(USYD毕业证书)澳洲悉尼大学毕业证成绩单原版一比一办理(USYD毕业证书)澳洲悉尼大学毕业证成绩单原版一比一
办理(USYD毕业证书)澳洲悉尼大学毕业证成绩单原版一比一diploma 1
 
办理(UC毕业证书)查尔斯顿大学毕业证成绩单原版一比一
办理(UC毕业证书)查尔斯顿大学毕业证成绩单原版一比一办理(UC毕业证书)查尔斯顿大学毕业证成绩单原版一比一
办理(UC毕业证书)查尔斯顿大学毕业证成绩单原版一比一z xss
 
How to Empower the future of UX Design with Gen AI
How to Empower the future of UX Design with Gen AIHow to Empower the future of UX Design with Gen AI
How to Empower the future of UX Design with Gen AIyuj
 
在线办理ohio毕业证俄亥俄大学毕业证成绩单留信学历认证
在线办理ohio毕业证俄亥俄大学毕业证成绩单留信学历认证在线办理ohio毕业证俄亥俄大学毕业证成绩单留信学历认证
在线办理ohio毕业证俄亥俄大学毕业证成绩单留信学历认证nhjeo1gg
 
办理(宾州州立毕业证书)美国宾夕法尼亚州立大学毕业证成绩单原版一比一
办理(宾州州立毕业证书)美国宾夕法尼亚州立大学毕业证成绩单原版一比一办理(宾州州立毕业证书)美国宾夕法尼亚州立大学毕业证成绩单原版一比一
办理(宾州州立毕业证书)美国宾夕法尼亚州立大学毕业证成绩单原版一比一F La
 
Design principles on typography in design
Design principles on typography in designDesign principles on typography in design
Design principles on typography in designnooreen17
 
group_15_empirya_p1projectIndustrial.pdf
group_15_empirya_p1projectIndustrial.pdfgroup_15_empirya_p1projectIndustrial.pdf
group_15_empirya_p1projectIndustrial.pdfneelspinoy
 
办理学位证加州州立大学洛杉矶分校毕业证成绩单原版一比一
办理学位证加州州立大学洛杉矶分校毕业证成绩单原版一比一办理学位证加州州立大学洛杉矶分校毕业证成绩单原版一比一
办理学位证加州州立大学洛杉矶分校毕业证成绩单原版一比一Fi L
 
Call Girls Meghani Nagar 7397865700 Independent Call Girls
Call Girls Meghani Nagar 7397865700  Independent Call GirlsCall Girls Meghani Nagar 7397865700  Independent Call Girls
Call Girls Meghani Nagar 7397865700 Independent Call Girlsssuser7cb4ff
 
'CASE STUDY OF INDIRA PARYAVARAN BHAVAN DELHI ,
'CASE STUDY OF INDIRA PARYAVARAN BHAVAN DELHI ,'CASE STUDY OF INDIRA PARYAVARAN BHAVAN DELHI ,
'CASE STUDY OF INDIRA PARYAVARAN BHAVAN DELHI ,Aginakm1
 

Dernier (20)

办理学位证(TheAuckland证书)新西兰奥克兰大学毕业证成绩单原版一比一
办理学位证(TheAuckland证书)新西兰奥克兰大学毕业证成绩单原版一比一办理学位证(TheAuckland证书)新西兰奥克兰大学毕业证成绩单原版一比一
办理学位证(TheAuckland证书)新西兰奥克兰大学毕业证成绩单原版一比一
 
2024新版美国旧金山州立大学毕业证成绩单pdf电子版制作修改#毕业文凭制作#回国入职#diploma#degree
2024新版美国旧金山州立大学毕业证成绩单pdf电子版制作修改#毕业文凭制作#回国入职#diploma#degree2024新版美国旧金山州立大学毕业证成绩单pdf电子版制作修改#毕业文凭制作#回国入职#diploma#degree
2024新版美国旧金山州立大学毕业证成绩单pdf电子版制作修改#毕业文凭制作#回国入职#diploma#degree
 
Call Girls Aslali 7397865700 Ridhima Hire Me Full Night
Call Girls Aslali 7397865700 Ridhima Hire Me Full NightCall Girls Aslali 7397865700 Ridhima Hire Me Full Night
Call Girls Aslali 7397865700 Ridhima Hire Me Full Night
 
Unveiling the Future: Columbus, Ohio Condominiums Through the Lens of 3D Arch...
Unveiling the Future: Columbus, Ohio Condominiums Through the Lens of 3D Arch...Unveiling the Future: Columbus, Ohio Condominiums Through the Lens of 3D Arch...
Unveiling the Future: Columbus, Ohio Condominiums Through the Lens of 3D Arch...
 
shot list for my tv series two steps back
shot list for my tv series two steps backshot list for my tv series two steps back
shot list for my tv series two steps back
 
DAKSHIN BIHAR GRAMIN BANK: REDEFINING THE DIGITAL BANKING EXPERIENCE WITH A U...
DAKSHIN BIHAR GRAMIN BANK: REDEFINING THE DIGITAL BANKING EXPERIENCE WITH A U...DAKSHIN BIHAR GRAMIN BANK: REDEFINING THE DIGITAL BANKING EXPERIENCE WITH A U...
DAKSHIN BIHAR GRAMIN BANK: REDEFINING THE DIGITAL BANKING EXPERIENCE WITH A U...
 
MT. Marseille an Archipelago. Strategies for Integrating Residential Communit...
MT. Marseille an Archipelago. Strategies for Integrating Residential Communit...MT. Marseille an Archipelago. Strategies for Integrating Residential Communit...
MT. Marseille an Archipelago. Strategies for Integrating Residential Communit...
 
(办理学位证)埃迪斯科文大学毕业证成绩单原版一比一
(办理学位证)埃迪斯科文大学毕业证成绩单原版一比一(办理学位证)埃迪斯科文大学毕业证成绩单原版一比一
(办理学位证)埃迪斯科文大学毕业证成绩单原版一比一
 
西北大学毕业证学位证成绩单-怎么样办伪造
西北大学毕业证学位证成绩单-怎么样办伪造西北大学毕业证学位证成绩单-怎么样办伪造
西北大学毕业证学位证成绩单-怎么样办伪造
 
毕业文凭制作#回国入职#diploma#degree澳洲弗林德斯大学毕业证成绩单pdf电子版制作修改#毕业文凭制作#回国入职#diploma#degree
毕业文凭制作#回国入职#diploma#degree澳洲弗林德斯大学毕业证成绩单pdf电子版制作修改#毕业文凭制作#回国入职#diploma#degree 毕业文凭制作#回国入职#diploma#degree澳洲弗林德斯大学毕业证成绩单pdf电子版制作修改#毕业文凭制作#回国入职#diploma#degree
毕业文凭制作#回国入职#diploma#degree澳洲弗林德斯大学毕业证成绩单pdf电子版制作修改#毕业文凭制作#回国入职#diploma#degree
 
办理(USYD毕业证书)澳洲悉尼大学毕业证成绩单原版一比一
办理(USYD毕业证书)澳洲悉尼大学毕业证成绩单原版一比一办理(USYD毕业证书)澳洲悉尼大学毕业证成绩单原版一比一
办理(USYD毕业证书)澳洲悉尼大学毕业证成绩单原版一比一
 
办理(UC毕业证书)查尔斯顿大学毕业证成绩单原版一比一
办理(UC毕业证书)查尔斯顿大学毕业证成绩单原版一比一办理(UC毕业证书)查尔斯顿大学毕业证成绩单原版一比一
办理(UC毕业证书)查尔斯顿大学毕业证成绩单原版一比一
 
How to Empower the future of UX Design with Gen AI
How to Empower the future of UX Design with Gen AIHow to Empower the future of UX Design with Gen AI
How to Empower the future of UX Design with Gen AI
 
在线办理ohio毕业证俄亥俄大学毕业证成绩单留信学历认证
在线办理ohio毕业证俄亥俄大学毕业证成绩单留信学历认证在线办理ohio毕业证俄亥俄大学毕业证成绩单留信学历认证
在线办理ohio毕业证俄亥俄大学毕业证成绩单留信学历认证
 
办理(宾州州立毕业证书)美国宾夕法尼亚州立大学毕业证成绩单原版一比一
办理(宾州州立毕业证书)美国宾夕法尼亚州立大学毕业证成绩单原版一比一办理(宾州州立毕业证书)美国宾夕法尼亚州立大学毕业证成绩单原版一比一
办理(宾州州立毕业证书)美国宾夕法尼亚州立大学毕业证成绩单原版一比一
 
Design principles on typography in design
Design principles on typography in designDesign principles on typography in design
Design principles on typography in design
 
group_15_empirya_p1projectIndustrial.pdf
group_15_empirya_p1projectIndustrial.pdfgroup_15_empirya_p1projectIndustrial.pdf
group_15_empirya_p1projectIndustrial.pdf
 
办理学位证加州州立大学洛杉矶分校毕业证成绩单原版一比一
办理学位证加州州立大学洛杉矶分校毕业证成绩单原版一比一办理学位证加州州立大学洛杉矶分校毕业证成绩单原版一比一
办理学位证加州州立大学洛杉矶分校毕业证成绩单原版一比一
 
Call Girls Meghani Nagar 7397865700 Independent Call Girls
Call Girls Meghani Nagar 7397865700  Independent Call GirlsCall Girls Meghani Nagar 7397865700  Independent Call Girls
Call Girls Meghani Nagar 7397865700 Independent Call Girls
 
'CASE STUDY OF INDIRA PARYAVARAN BHAVAN DELHI ,
'CASE STUDY OF INDIRA PARYAVARAN BHAVAN DELHI ,'CASE STUDY OF INDIRA PARYAVARAN BHAVAN DELHI ,
'CASE STUDY OF INDIRA PARYAVARAN BHAVAN DELHI ,
 

Display Matters: A Test of Visual Display Options in a Web-Based Survey

  • 1. Display  Ma*ers:     A  Test  of  Visual  Display  Op6ons  in  a   Web-­‐Based  Survey   Jennifer  C.  Romano  Bergstrom1,  Jennifer  M.  Chen1,     Timothy  R.  Gilbert2  &  Ma*  Jans1   1  Center  for  Survey  Measurement   2  Demographic  Surveys  Division   U.S.  Census  Bureau   AAPOR  66th  Annual  Conference     May  13,  2011  
  • 2. Current  Survey  Environment   •  Increasing  number  of  surveys  online   •  Design  considera6ons   –  Naviga6on  methods   –  Presenta6on  of  response  op6ons   2  
  • 3. Current  Survey  Environment   •  Increasing  number  of  surveys  online   •  Design  considera6ons   –  Naviga6on  methods   –  Presenta6on  of  response  op6ons   3  
  • 4. Background  on  Next  and  Previous   •  Next  should  be  on  the  leU   –  Reduces  the  amount  of  6me  to  move  cursor  to   primary  naviga6on  bu*on  (Couper,  2008)   –  Frequency  of  use  (Dillman  et  al.,  2009;  Faulkner,   1998;  Koyani  et  al.,  2004;  Wroblewski,  2008)   4  
  • 5. Background  on  Next  and  Previous   •  Previous  should  be  on  the  leU   –  Web  applica6on  order   –  Everyday  devices   –  Logical  reading  order   5  
  • 6. Background  on  Next  and  Previous   •  Previous  should  be  on  the  leU   –  Web  applica6on  order   –  Everyday  devices   –  Logical  reading  order   6  
  • 7. Background  on  Next  and  Previous   •  Previous  should  be  below  Next   –  Bu*ons  can  be  closer  (Couper  et  al.,  2011;   Wroblewski,  2008)   7  
  • 8. Background  on  Long  Lists   •  One  column   –  Visually  appear  to  belong  to  one  group   –  When  there  are  two  columns,  2nd  one  may  not  be   seen  (Smyth  et  al.,  1997)   •  Two  columns:  Double  banked   –  No  scrolling   –  See  all  op6ons  at  once   –  Appears  shorter   8  
  • 9. Measuring  “Best”  Design   •  Typical:  In  the  Field   –  Drop-­‐off  rates   –  Keystrokes   –  Survey  comple6on  6mes   •  Our  Study:  In  the  Lab     –  User  sa6sfac6on   –  Eye-­‐tracking  data   –  Usability  metrics   9  
  • 10. Usability   •  The  extent  to  which  a  product  can  be  used  by   specified  users  to  achieve  specified  goals  with   effec6veness,  efficiency,  and  sa6sfac6on.  ISO/ TR  16982:2002   •  For  web-­‐based  surveys,  the  design  must   –  Meet  respondents’  needs   –  Facilitate  easy  comple6on   –  Provide  a  sa6sfying  experience   –  Reduce  respondent  burden   –  Produce  high-­‐quality  data   10  
  • 11. Na6onal  Survey  of  College  Graduates   (NSCG)   •  Collects  educa6on  and  job  informa6on   •  Respondents  have  Bachelor’s  degree   •  Was  available  in  PAPI  and  CATI   •  Usability  study  for  a  web-­‐based  self-­‐ administered  instrument   11  
  • 12. Method     •  Lab-­‐based  usability  study   •  TA  read  introduc6on  and  leU  le*er  on  desk   •  Separate  rooms   •  R  read  le*er  and  logged  in  to  survey   •  Think  Aloud  (Olmsted-­‐Hawala  et  al.,  2010)   •  Eye  Tracking   •  Sa6sfac6on  Ques6onnaire   •  Debriefing   12  
  • 13. Par6cipants   Gender   N   Age   N   Educa.on   N   Male   14   <  30   8   Bachelor’s   21   Female   16   31-­‐45   7   Master’s   6   46-­‐60   10   Ph.D.   3   >  60     5   Mean:  46   13  
  • 15. Ques6ons  Eye  Tracking  Can  Answer   •  Do  respondents  look  at  Next  and  Previous?   •  What  do  they  look  at  first?   •  Is  it  distrac6ng  when  Previous  is  located  in  a   par6cular  place  on  the  screen?   •  How  long  does  it  take  respondents  to  see  the   Next  bu*on?   •  Does  presenta6on  of  long  lists  affect  what   users  look  at  on  the  list?   15  
  • 16. Previous  and  Next  Bu*ons   16  
  • 17. One  Column  vs.  Two  Columns   17  
  • 18. 4  Versions   N_P1   N_P2   Next  bu*on  on  leU,     Next  bu*on  on  leU,     1-­‐column  job  code   2-­‐column  job  code   PN1   PN2   Previous  bu*on  on  leU,     Previous  bu*on  on  leU,     1-­‐column  job  code   2-­‐column  job  code   18  
  • 19. Results:  Sa6sfac6on  I   *  p  <  0.0001   19  
  • 20. 8.5   Results:  Sa6sfac6on  II   8.5   Mean  Sa.sfac.on   Mean  Sa.sfac.on   8   8   Ra.ng   7.5   Ra.ng   7.5   7   7   6.5   6.5   6   6   Mean   N_P   PN   Mean   N_P   PN   Overall  reac6on  to  the  survey:     Informa6on  displayed  on  the  screens:     terrible  –  wonderful.  p  <  0.05.   inadequate  –  adequate.  p  =  0.07.     8.5   8.5   Mean  Sa.sfac.on   Mean  Sa.sfac.on   8   8   Ra.ng   7.5   Ra.ng   7.5   7   7   6.5   6.5   6   6   Mean   N_P   PN   Mean   N_P   PN   Arrangement  of  informa6on  on  the  screens:   Forward  naviga6on:     illogical  –  logical.  p  =  0.19.   impossible  –  easy.  p  =  0.13.     20  
  • 21. Eye  Tracking:  Next  /  Previous   21  
  • 22. Eye  Tracking:  Previous  /  Next   22  
  • 23.  Eye  Tracking:  N_P  vs.  PN   •  Par6cipants  looked  at  Previous  and  Next  in  PN   condi6ons   •  Many  par6cipants  looked  at  Previous  in  the   N_P  condi6ons   –  Consistent  with  Couper  et  al.  (2011):  Previous  gets   used  more  when  it  is  on  the  right   23  
  • 24.  Eye  Tracking:  Time  to  First  Fixa6on   8   7.5   7   6.5   Seconds   6      PN   5.5      N_P   5   4.5   4   Next   Previous   Mean  6me  to  first  look  at  the  naviga6on  bu*on   24  
  • 25.  N_P  vs.  PN:  Respondent  Debriefing   •  N_P  version   –  Counterintui6ve   –  Don’t  like  the  “bu*ons  being  flipped.”   –  Next  on  the  leU  is  “really  irrita6ng.”   –  Order  is  “opposite  of  what  most  people  would   design.”   •  PN  version   –  “Pre*y  standard,  like  what  you  typically  see.”   –  The  loca6on  is  “logical.”   25  
  • 26.  1  Column  vs.  2  Column   26  
  • 27. Time  to  First  Fixa6on   25   20   15   Seconds   1  col   *  p  <  0.01   10   2  col   5   0   First  half  of  list   Second  half  of  list   27  
  • 28. Total  Number  of  Fixa6ons   40   35   30   Number  of  Fixa.ons   25   20   1  col   15   2  col   10   5   0   First  half  of  list   Second  half  of  list   28  
  • 29. Time  to  Complete  Item   120   100   80   Seconds   60   1  col   2  col   40   20   0   Mean   Min   Max   29  
  • 30.  1  Col.  vs.  2  Col.:  Debriefing   •  25  had  a  preference   –  6  preferred  one  column   •  They  had  received  the  one-­‐column  version   –  19  preferred  2  columns   •  7  had  received  the  one-­‐column  version   •  Prefer  not  to  scroll   •  Want  to  see  and  compare  everything  at  once   •  It  is  easier  to  “look  through,”  to  scan,  to  read   •  Re  one  column,  “How  long  is  this  list  going  to  be?”   30  
  • 31. Conclusions     •  Par6cipants  were  more  sa6sfied  when   Previous  was  on  the  leU.   •  Par6cipants  preferred  the  long  lists  in  two   columns.   •  Par6cipants  looked  at  the  first  half  of  the  list   sooner  than  the  second  half  when  in  one   column.   •  Par6cipants  looked  at  the  second  half  of  the   list  more  when  it  was  in  two  columns.   31  
  • 32. Bigger  Picture:  Recap  on  Next  and  Previous   •  Next  should  be  on  the  leU   –  Reduces  the  amount  of  6me  to  move  cursor  to  primary   naviga6on  bu*on   –  Tab  order   –  Frequency  of  use   •  Previous  should  be  on  the  leU   –  Web  applica6on  order   –  Everyday  devices   –  Logical  reading  order   –  People  are  more  sa6sfied   –  It  takes  longer  to  first  look  at  Previous  when  on  the  right   32  
  • 33. Bigger  Picture:  Recap  on  Long  Lists   •  One  column   –  Visually  appear  to  belong  to  one  group   •  Two  columns:  Double  banked   –  No  scrolling   –  See  all  op6ons  at  once   –  Appears  shorter   –  Second  column  may  not  be  seen   –  People  look  at  the  second  half  more   –  People  look  at  the  first  half  sooner  when  it  is  in  one   column   –  People  prefer  two  columns   33  
  • 34. Future  Direc6ons     •  This  is  just  a  small  nugget.   •  N_P  vs.  P_N  study  in  progress   –  Same  layout   –  No  skip  pa*erns   –  Efficiency  measure   •  Long  list  of  items  condi6on   –  Which  items  do  people  pick?   –  Alphabe6zed  vs.  random  order   34  
  • 35. Thank  you!   For  more  informa6on,  please  contact   Jennifer  Romano  Bergstrom   Jennifer.C.Romano@gmail.com   Jennifer.Romano@census.gov   Twi*er:  @romanocog   35