Information vs Interaction          examining different interaction models over                     consistent metadata   ...
Motivation                            Related Work   Information vs Interaction                   Design            Result...
Motivation 1                   Understanding Search User Interface DesignDr Max L. Wilson                                 ...
Dr Max L. Wilson   http://cs.nott.ac.uk/~mlw/
4                                                                  14                13                                   ...
4                                                1                            14                      10                  ...
Dr Max L. Wilson   http://cs.nott.ac.uk/~mlw/
Faceted FiltersDr Max L. Wilson                     http://cs.nott.ac.uk/~mlw/
Dr Max L. Wilson   http://cs.nott.ac.uk/~mlw/
Dr Max L. Wilson   http://cs.nott.ac.uk/~mlw/
Wilson, M. L., Andre, P. and schraefel, m. c. (2008) Backward Highlighting: Enhancing Faceted Search. In:Proceedings of th...
So much literatureDr Max L. Wilson                        http://cs.nott.ac.uk/~mlw/
Better interaction or Better information   Query Suggestions   Clustered Categories   Faceted FiltersDr Max L. Wilson     ...
Our questions              What matters most? Interaction or Information?                                    !            ...
Motivation 2Dr Max L. Wilson                  http://cs.nott.ac.uk/~mlw/
Designs and BudgetsDr Max L. Wilson                         http://cs.nott.ac.uk/~mlw/
Designs and BudgetsDr Max L. Wilson                         http://cs.nott.ac.uk/~mlw/
Designs and BudgetsDr Max L. Wilson                         http://cs.nott.ac.uk/~mlw/
Our questions              What matters most? Interaction or Information?                                    !            ...
Motivation                           Related Work   Information vs Interaction                      Design       Results  ...
Related Work   Query Suggestions   Clustered Categories   Faceted FiltersDr Max L. Wilson                                 ...
Related Work   Query Suggestions                       • Kelly                             et al (2009) - query suggestion...
Related Work   Query Suggestions   Clustered Categories   Faceted FiltersDr Max L. Wilson                                 ...
Related Work       Clustered Categories                               • Hearst  & Pederson (1996)                         ...
Related Work   Query Suggestions   Clustered Categories   Faceted FiltersDr Max L. Wilson                                 ...
Related Work                                          Faceted Filters   • Hearst   (2006) - careful metadata      is alway...
Related Work              (Different Interaction and Different Information)                                             • ...
Different Interaction Same Information   Query Suggestions   Clustered Categories   Faceted FiltersDr Max L. Wilson       ...
Different Interaction Same Information                         Clustered    Faceted            Query data                 ...
Different Interaction Same Information            Query dataDr Max L. Wilson                   http://cs.nott.ac.uk/~mlw/
Motivation                                Related Work   Information vs Interaction                     Design            ...
Our Hypotheses                   H1:"Searchers"will"be"more"efficient"with"more"powerful"                    interaction,"us...
The 3 Interaction Models                         Query         Clustered            Faceted                       Suggesti...
3 Conditions        UIQ                UIC                UIF       Figure 1: The three interaction conditions in the stud...
Two standard types of user study task were used in the   study: 1) a simple lookup task and 2) an exploratory task.   All ...
18 people          16-55 (avg 28)                                          Mix of students,           All daily web users ...
18 People                   Intro +    UI1       UI2       UI3      QA +                   Consent   2 tasks   2 tasks   2...
18 People                   Intro +       UI1       UI2       UI3      QA +                   Consent      2 tasks   2 tas...
18 People                   Intro +       UI1       UI2       UI3      QA +                   Consent      2 tasks   2 tas...
18 People                   Intro +       UI1       UI2       UI3      QA +                   Consent      2 tasks   2 tas...
Motivation                                Related Work   Information vs Interaction                      Design           ...
Simple vs Exploratory        Measure            S       E          Diff              Time        176s    179s          no ...
between the three interface conditions. These results      indicate that for simple tasks, or tasks with a fixed answer,  ...
between the three interface conditions. These results      indicate that for simple tasks, or tasks with a fixed answer,  ...
between the three interface conditions. These results      indicate that for simple tasks, or tasks with a fixed answer,  ...
between the three interface conditions. These results      indicate that for simple tasks, or tasks with a fixed answer,  ...
between the three interface conditions. These results      indicate that for simple tasks, or tasks with a fixed answer,  ...
refinements in the faceted UIF condition (F(51,2)=6.245,           The choices high        p<0.005). Again, a post-hoc Tuk...
refinements in the faceted UIF condition (F(51,2)=6.245,           The choices high        p<0.005). Again, a post-hoc Tuk...
refinements in the faceted UIF condition (F(51,2)=6.245,           The choices high        p<0.005). Again, a post-hoc Tuk...
refinements in the faceted UIF condition (F(51,2)=6.245,           The choices high        p<0.005). Again, a post-hoc Tuk...
refinements in the faceted UIF condition (F(51,2)=6.245,           The choices high        p<0.005). Again, a post-hoc Tuk...
refinements in the faceted UIF condition (F(51,2)=6.245,              The choices high     p<0.005). Again, a post-hoc Tuk...
Subjective Responses                   Measure                        Simple                   Easy of Use                ...
Motivation                                Related Work   Information vs Interaction                      Design           ...
Hypotheses Revisted       H1:"Searchers"will"be"more"efficient"with"more"        powerful"interaction,"using"the"same"      ...
Hypotheses Revisted              H2:"Searchers"will"enjoy"more"powerful"               interaction,"despite"using"the"same...
Hypotheses Revisted       H3:"Searchers"will"use"query"recommendations"more"        when"they"are"presented"differently."  ...
Limitations   • UIF      - was not perfect   • Auto-suggest          - was not considered   • Measurements        - were l...
Conclusions                               What did we actually learn?   • We            did see different behaviour in all...
Future Work            Query dataDr Max L. Wilson                       http://cs.nott.ac.uk/~mlw/
Future Work                            Clustered    Faceted            Query data                            algorithms   ...
Future Work                                                 Facets                                                 Cluster...
Dr Max L. Wilson   http://cs.nott.ac.uk/~mlw/
Upcoming SlideShare
Loading in …5
×

IIiX2012 - Information vs Interaction - Examining different interaction models over consistent metadata

559 views
505 views

Published on

A talk given at the 2012 Information Interaction in Context conference (IIiX2012) where we developed 3 alternative versions of Google with 3 different refinement interactions on the left. Each used the same metadata, and the study was designed to show that users can get achieve better performance with different interaction over the same metadata.

You can provide benefits for searchers just be adjusting the interaction to your metadata. You do not _require_ better metadata to get better interaction.

Published in: Technology, Education
0 Comments
4 Likes
Statistics
Notes
  • Be the first to comment

No Downloads
Views
Total views
559
On SlideShare
0
From Embeds
0
Number of Embeds
0
Actions
Shares
0
Downloads
5
Comments
0
Likes
4
Embeds 0
No embeds

No notes for slide

IIiX2012 - Information vs Interaction - Examining different interaction models over consistent metadata

  1. 1. Information vs Interaction examining different interaction models over consistent metadata (for now) Kingsley Hughes-Morgan Dr Max L. Wilson Future Interaction Technology Lab Mixed Reality Lab Swansea University, UK University of Nottingham, UK kingsleyhm@googlemail.com max.wilson@nottingham.ac.uk @kingsleyhm @gingdottwitDr Max L. Wilson http://cs.nott.ac.uk/~mlw/
  2. 2. Motivation Related Work Information vs Interaction Design Results DiscussionDr Max L. Wilson http://cs.nott.ac.uk/~mlw/
  3. 3. Motivation 1 Understanding Search User Interface DesignDr Max L. Wilson http://cs.nott.ac.uk/~mlw/
  4. 4. Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
  5. 5. 4 14 13 1 5 10 8 11 2 9 12 7 6 9 11 3Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
  6. 6. 4 1 14 10 8 12 13 15 11 5 2 6 7 9 16 3Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
  7. 7. Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
  8. 8. Faceted FiltersDr Max L. Wilson http://cs.nott.ac.uk/~mlw/
  9. 9. Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
  10. 10. Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
  11. 11. Wilson, M. L., Andre, P. and schraefel, m. c. (2008) Backward Highlighting: Enhancing Faceted Search. In:Proceedings of the 21st Symposium on User Interface Software and Technology (UIST2008), October 19-22, 2008, Monterey, CA, USA. pp. 235-238.Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
  12. 12. So much literatureDr Max L. Wilson http://cs.nott.ac.uk/~mlw/
  13. 13. Better interaction or Better information Query Suggestions Clustered Categories Faceted FiltersDr Max L. Wilson http://cs.nott.ac.uk/~mlw/
  14. 14. Our questions What matters most? Interaction or Information? ! Given!a!specific!form!of! metadata,!can!we!recreate!more! advanced!IIR!interface!features! such!that!searchers!can!still! experience!their!benefits?!!Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
  15. 15. Motivation 2Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
  16. 16. Designs and BudgetsDr Max L. Wilson http://cs.nott.ac.uk/~mlw/
  17. 17. Designs and BudgetsDr Max L. Wilson http://cs.nott.ac.uk/~mlw/
  18. 18. Designs and BudgetsDr Max L. Wilson http://cs.nott.ac.uk/~mlw/
  19. 19. Our questions What matters most? Interaction or Information? ! Given!a!specific!form!of! metadata,!can!we!recreate!more! advanced!IIR!interface!features! such!that!searchers!can!still! experience!their!benefits?!! How should companies prioritise investment?Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
  20. 20. Motivation Related Work Information vs Interaction Design Results DiscussionDr Max L. Wilson http://cs.nott.ac.uk/~mlw/
  21. 21. Related Work Query Suggestions Clustered Categories Faceted FiltersDr Max L. Wilson http://cs.nott.ac.uk/~mlw/
  22. 22. Related Work Query Suggestions • Kelly et al (2009) - query suggestions are better than term suggestions • Ruthven (2003) - humans not good at choosing useful queries - algorithms should pick them well. • Diriye (2009) - slow people down during simple tasksDr Max L. Wilson http://cs.nott.ac.uk/~mlw/
  23. 23. Related Work Query Suggestions Clustered Categories Faceted FiltersDr Max L. Wilson http://cs.nott.ac.uk/~mlw/
  24. 24. Related Work Clustered Categories • Hearst & Pederson (1996) - better task performance • Pirolli et al (1996) - helped to understand corpusDr Max L. Wilson http://cs.nott.ac.uk/~mlw/
  25. 25. Related Work Query Suggestions Clustered Categories Faceted FiltersDr Max L. Wilson http://cs.nott.ac.uk/~mlw/
  26. 26. Related Work Faceted Filters • Hearst (2006) - careful metadata is always better than clusters • Wilson & schraefel (2009) - good for understanding corpusDr Max L. Wilson http://cs.nott.ac.uk/~mlw/
  27. 27. Related Work (Different Interaction and Different Information) • Joho et al (2006) - hierarchy better than linear list • butused different data structuresDr Max L. Wilson http://cs.nott.ac.uk/~mlw/
  28. 28. Different Interaction Same Information Query Suggestions Clustered Categories Faceted FiltersDr Max L. Wilson http://cs.nott.ac.uk/~mlw/
  29. 29. Different Interaction Same Information Clustered Faceted Query data algorithms metadataDr Max L. Wilson http://cs.nott.ac.uk/~mlw/
  30. 30. Different Interaction Same Information Query dataDr Max L. Wilson http://cs.nott.ac.uk/~mlw/
  31. 31. Motivation Related Work Information vs Interaction Design Results DiscussionDr Max L. Wilson http://cs.nott.ac.uk/~mlw/
  32. 32. Our Hypotheses H1:"Searchers"will"be"more"efficient"with"more"powerful" interaction,"using"the"same"metadata,"when"completing" search"tasks." H2:"Searchers"will"enjoy"more"powerful"interaction,"despite" using"the"same"metadata. " H3:"Searchers"will"use"query"recommendations"more"when" they"are"presented"differently."Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
  33. 33. The 3 Interaction Models Query Clustered Faceted Suggestions Categories Filters Changes every No change on No change on Query search refinement refinement Stay the same Stay the same Filters New filters for the query for the query One at a time Applying filters Experience Searching again in Hierarchy in combination Subset of the Subset of the Results New results original results original resultsDr Max L. Wilson http://cs.nott.ac.uk/~mlw/
  34. 34. 3 Conditions UIQ UIC UIF Figure 1: The three interaction conditions in the study. UIQ on the left presents query suggestions in theirDr Max L. Wilson http://cs.nott.ac.uk/~mlw/
  35. 35. Two standard types of user study task were used in the study: 1) a simple lookup task and 2) an exploratory task. All six tasks are shown in Table 1. The simple lookup tasks had a fixed answer, but the chosen 2 Types of Task task description was presented in such a way that the most likely query would not find the answer without subsequent queries or refinements. This approach was chosen to intrinsically encourage participants to use the IIR features on the left of each user interface condition. Table 1: Tasks set to participants in the study. S = Simple, E = Exploratory ID S/E Task Description 1 S What is the population of Ohio? A&simple&lookup&task"="had"a"fixed" 2 E Find an appropriate review of “Harry Potter and answer,"subsequent"queries"or" the Deathly Hallows”. refinements"were"needed. - Compare the rating with the previous film. 3 S Find the first state of America. An&exploratory&task"="multiple" 4 E Deduce the main problems that Steve Jobs subBproblems,"required"a"series" incurred with regards to his health. of"searches/refinements"to" 5 S What is the iPad 3’s proposed processor name? combine"answers"from"several" 6 E Explore information related to Apple’s next websites."No"fixed"answer." iPhone, the iPhone 5. (Collection8style) - Note the expected release date. There could well be multiple rumours. The exploratory search tasks were chosen to be tasks with multiple sub-problems, such that searchers would have to perform a series of searches or refinements to combineDr Max L. Wilson http://cs.nott.ac.uk/~mlw/
  36. 36. 18 people 16-55 (avg 28) Mix of students, All daily web users academic and non-academic staff in different schoolsDr Max L. Wilson http://cs.nott.ac.uk/~mlw/
  37. 37. 18 People Intro + UI1 UI2 UI3 QA + Consent 2 tasks 2 tasks 2 tasks DebriefDr Max L. Wilson http://cs.nott.ac.uk/~mlw/
  38. 38. 18 People Intro + UI1 UI2 UI3 QA + Consent 2 tasks 2 tasks 2 tasks Debrief Queries Refinements Pageviews Time MeasuresDr Max L. Wilson http://cs.nott.ac.uk/~mlw/
  39. 39. 18 People Intro + UI1 UI2 UI3 QA + Consent 2 tasks 2 tasks 2 tasks Debrief Queries Refinements Ease of use Pageviews Task Satisfaction Time MeasuresDr Max L. Wilson http://cs.nott.ac.uk/~mlw/
  40. 40. 18 People Intro + UI1 UI2 UI3 QA + Consent 2 tasks 2 tasks 2 tasks Debrief Queries Quickest Refinements Ease of use Most Enjoyable Pageviews Task Satisfaction Best Design Time MeasuresDr Max L. Wilson http://cs.nott.ac.uk/~mlw/
  41. 41. Motivation Related Work Information vs Interaction Design Results DiscussionDr Max L. Wilson http://cs.nott.ac.uk/~mlw/
  42. 42. Simple vs Exploratory Measure S E Diff Time 176s 179s no Queries 1.75 2.33 p<0.05 Pageviews 1.65 2.09 p<0.005 Refinements 2.42 2.45 noDr Max L. Wilson http://cs.nott.ac.uk/~mlw/
  43. 43. between the three interface conditions. These results indicate that for simple tasks, or tasks with a fixed answer, the different interaction models did not create a significant Simple tasks effect on refinement behaviour. Participants did, however, perform significantly faster in the hierarchical clustering UIC condition (p<0.005, F(51,2)=6.53), where a post-hoc TukeyHSD showed that UIF and UIQ were not significantly different from each other. Table 2: log data for simple tasks (*=significant) Mean (std) UIQ UIC UIF Queries (#) * 1.22 (0.55) 2.11 (1.13) 1.94 (0.93) p<0.05 Refinements (#) 2.44 (0.70) 2.5 (1.95) 2.33 (1.19) Page visits (#) 1.94 (1.11) 1.61 (0.69) 1.39 (0.61) Time (s) * 189 (3.15) 154 (2.57) 184 (3.07) p<0.05 It is not clear exactly why participants submitted significantly more queries in the UIC and UIF conditions, but the results indicate that participants were fastest when interacting with a hierarchy. Although we didn’t reach statistical significance, there was a downward trend toDr Max L. Wilson http://cs.nott.ac.uk/~mlw/
  44. 44. between the three interface conditions. These results indicate that for simple tasks, or tasks with a fixed answer, the different interaction models did not create a significant Simple tasks effect on refinement behaviour. Participants did, however, perform significantly faster in the hierarchical clustering UIC condition (p<0.005, F(51,2)=6.53), where a post-hoc TukeyHSD showed that UIF and UIQ were not significantly different from each other. Table 2: log data for simple tasks (*=significant) Mean (std) UIQ UIC UIF Queries (#) * 1.22 (0.55) 2.11 (1.13) 1.94 (0.93) p<0.05 Refinements (#) 2.44 (0.70) p<0.05 2.5 (1.95) 2.33 (1.19) Page visits (#) 1.94 (1.11) p=0.051.39 (0.61) 1.61 (0.69) (!) Time (s) * 189 (3.15) 154 (2.57) 184 (3.07) p<0.05 It is not clear exactly why participants submitted significantly more queries in the UIC and UIF conditions, but the results indicate that participants were fastest when interacting with a hierarchy. Although we didn’t reach statistical significance, there was a downward trend toDr Max L. Wilson http://cs.nott.ac.uk/~mlw/
  45. 45. between the three interface conditions. These results indicate that for simple tasks, or tasks with a fixed answer, the different interaction models did not create a significant Simple tasks effect on refinement behaviour. Participants did, however, perform significantly faster in the hierarchical clustering UIC condition (p<0.005, F(51,2)=6.53), where a post-hoc TukeyHSD showed that UIF and UIQ were not significantly different from each other. Table 2: log data for simple tasks (*=significant) Mean (std) UIQ UIC UIF Queries (#) * 1.22 (0.55) 2.11 (1.13) 1.94 (0.93) p<0.05 Refinements (#) 2.44 (0.70) 2.5 (1.95) 2.33 (1.19) Page visits (#) 1.94 (1.11) p<0.05(0.69) 1.61 p<0.05 1.39 (0.61) Time (s) * 189 (3.15) 154 (2.57) 184 (3.07) p<0.05 It is not clear exactly why participants submitted significantly more queries in the UIC and UIF conditions, but the results indicate that participants were fastest when interacting with a hierarchy. Although we didn’t reach statistical significance, there was a downward trend toDr Max L. Wilson http://cs.nott.ac.uk/~mlw/
  46. 46. between the three interface conditions. These results indicate that for simple tasks, or tasks with a fixed answer, the different interaction models did not create a significant Simple tasks effect on refinement behaviour. Participants did, however, perform significantly faster in the hierarchical clustering UIC condition (p<0.005, F(51,2)=6.53), where a post-hoc TukeyHSD showed that UIF and UIQ were not significantly different from each other. Table 2: log data for simple tasks (*=significant) Mean (std) UIQ UIC UIF Queries (#) * 1.22 (0.55) 2.11 (1.13) 1.94 (0.93) p<0.05 Refinements (#) 2.44 (0.70) 2.5 (1.95) 2.33 (1.19) Page visits (#) 1.94 (1.11) 1.61 (0.69) 1.39 (0.61) Time (s) * 189 (3.15) 154 (2.57) 184 (3.07) p<0.05 It is not clear exactly why participants submitted significantly more queries in the UIC - p=~0.1 “Downward Trend” and UIF conditions, but the results indicate that participants were fastest when interacting with a hierarchy. Although we didn’t reach statistical significance, there was a downward trend toDr Max L. Wilson http://cs.nott.ac.uk/~mlw/
  47. 47. between the three interface conditions. These results indicate that for simple tasks, or tasks with a fixed answer, the different interaction models did not create a significant Simple tasks effect on refinement behaviour. Participants did, however, perform significantly faster in the hierarchical clustering UIC condition (p<0.005, F(51,2)=6.53), where a post-hoc TukeyHSD showed that UIF and UIQ were not significantly different from each other. Table 2: log data for simple tasks (*=significant) Mean (std) UIQ UIC UIF Queries (#) * 1.22 (0.55) 2.11 (1.13) 1.94 (0.93) p<0.05 Refinements (#) 2.44 (0.70) 2.5 (1.95) 2.33 (1.19) Page visits (#) 1.94 (1.11) 1.61 (0.69) 1.39 (0.61) Time (s) * 189 (3.15) 154 (2.57) 184 (3.07) p<0.05 It - Not much difference in #refinements and #pagevisits is not clear exactly why participants submitted significantly more queries ininteractive conditions - More queries (!) in the UIC and UIF conditions, but the results indicate that participants were fastest when - Faster in UIC interacting with a hierarchy. Although we didn’t reach statistical significance, there was a downward trend toDr Max L. Wilson http://cs.nott.ac.uk/~mlw/
  48. 48. refinements in the faceted UIF condition (F(51,2)=6.245, The choices high p<0.005). Again, a post-hoc TukeyHSD revealed enjoyed and pref significant differences between UIF and the two despite believing Exploratory tasks alternatives (both p<0.05), but no difference between UIC and UIQ. Together, these two sets of results indicate that baseline conditio timing data, indi participants behaved very differently in the three baseline felt fast conditions, for exploratory tasks, using significantly fewer favourably in any queries (with UIC) and significantly more refinements. Table 5: Freq Table 3: log data for exploratory tasks (*=significant) three co Mean (std) UIQ UIC UIF Frequency of ch Queries (#) * 3.11 (1.49) 1.44 (0.51) 2.44 (1.29) p<0.0005 to correct Quickest Refinements (#) * 2.17 (0.86) 1.78 (0.65) 3.39 (2.23) p<0.005enjoyment du Most Page visits (#) * 2.55 (1.04) 1.61 (0.69) 2.11 (0.75) p<0.01 appealing des Most Time on task (s) * 190 (3.17) 169 (2.82) 177 (2.95) p<0.01 In exploratory tasks, participants visited significantly more 5. DISCUSSI Our study has p pages in the original condition (F(51,2)=5.615, p<0.01), research question where a post-hoc TukeyHSD saw only one key difference support searcher between UIQ and UIC. This finding may indicate that have a fixed form participants were able to find more relevant pages earlier inDr Max L. Wilson but hard to find a http://cs.nott.ac.uk/~mlw/
  49. 49. refinements in the faceted UIF condition (F(51,2)=6.245, The choices high p<0.005). Again, a post-hoc TukeyHSD revealed enjoyed and pref significant differences between UIF and the two despite believing Exploratory tasks alternatives (both p<0.05), but no difference between UIC and UIQ. Together, these two sets of results indicate that baseline conditio timing data, indi participants behaved very differently in the three baseline felt fast conditions, for exploratory tasks, using significantly fewer favourably in any queries (with UIC) and significantly more refinements. Table 5: Freq Table 3: log data for exploratory tasks (*=significant) three co Mean (std) UIQ UIC UIF Frequency of ch Queries (#) * 3.11 (1.49) 1.44 (0.51) 2.44 (1.29) p<0.0005 to correct Quickest Refinements (#) * 2.17 (0.86) 1.78 (0.65) 3.39 (2.23) p<0.005enjoyment du Most Page visits (#) * p<0.0005 (0.69)p<0.05 (0.75) 2.55 (1.04) 1.61 2.11 p<0.01 appealing des Most Time on task (s) * 190 (3.17) 169 (2.82) 177 (2.95) p<0.01 In exploratory tasks, participants visited significantly more 5. DISCUSSI Our study has p pages in the original condition (F(51,2)=5.615, p<0.01), research question where a post-hoc TukeyHSD saw only one key difference support searcher between UIQ and UIC. This finding may indicate that have a fixed form participants were able to find more relevant pages earlier inDr Max L. Wilson but hard to find a http://cs.nott.ac.uk/~mlw/
  50. 50. refinements in the faceted UIF condition (F(51,2)=6.245, The choices high p<0.005). Again, a post-hoc TukeyHSD revealed enjoyed and pref significant differences between UIF and the two despite believing Exploratory tasks alternatives (both p<0.05), but no difference between UIC and UIQ. Together, these two sets of results indicate that baseline conditio timing data, indi participants behaved very differently in the three baseline felt fast conditions, for exploratory tasks, using significantly fewer favourably in any queries (with UIC) and significantly more refinements. Table 5: Freq Table 3: log data for exploratory tasks (*=significant) three co Mean (std) UIQ UIC UIF Frequency of ch Queries (#) * 3.11 (1.49) 1.44 (0.51) 2.44 (1.29) p<0.05 p<0.0005 to correct Quickest Refinements (#) * 2.17 (0.86) 1.78 (0.65) 3.39 (2.23) p<0.005enjoyment du Most Page visits (#) * 2.55 (1.04) 1.61 (0.69) 2.11 (0.75) p<0.01 appealing des Most Time on task (s) * 190 (3.17)p<0.05 (2.82) 169 177 (2.95) p<0.01 In exploratory tasks, participants visited significantly more 5. DISCUSSI Our study has p pages in the original condition (F(51,2)=5.615, p<0.01), research question where a post-hoc TukeyHSD saw only one key difference support searcher between UIQ and UIC. This finding may indicate that have a fixed form participants were able to find more relevant pages earlier inDr Max L. Wilson but hard to find a http://cs.nott.ac.uk/~mlw/
  51. 51. refinements in the faceted UIF condition (F(51,2)=6.245, The choices high p<0.005). Again, a post-hoc TukeyHSD revealed enjoyed and pref significant differences between UIF and the two despite believing Exploratory tasks alternatives (both p<0.05), but no difference between UIC and UIQ. Together, these two sets of results indicate that baseline conditio timing data, indi participants behaved very differently in the three baseline felt fast conditions, for exploratory tasks, using significantly fewer favourably in any queries (with UIC) and significantly more refinements. Table 5: Freq Table 3: log data for exploratory tasks (*=significant) three co Mean (std) UIQ UIC UIF Frequency of ch Queries (#) * 3.11 (1.49) 1.44 (0.51) 2.44 (1.29) p<0.0005 to correct Quickest Refinements (#) * 2.17 (0.86) 1.78 (0.65) 3.39 (2.23) p<0.005enjoyment du Most Page visits (#) * 2.55 (1.04) 1.61 (0.69) 2.11 (0.75) p<0.01 appealing des Most Time on task (s) * 190 (3.17) 169 (2.82) p<0.05 177 (2.95) p<0.01 In exploratory tasks, participants visited significantly more 5. DISCUSSI Our study has p pages in the original condition (F(51,2)=5.615, p<0.01), research question where a post-hoc TukeyHSD saw only one key difference support searcher between UIQ and UIC. This finding may indicate that have a fixed form participants were able to find more relevant pages earlier inDr Max L. Wilson but hard to find a http://cs.nott.ac.uk/~mlw/
  52. 52. refinements in the faceted UIF condition (F(51,2)=6.245, The choices high p<0.005). Again, a post-hoc TukeyHSD revealed enjoyed and pref significant differences between UIF and the two despite believing Exploratory tasks alternatives (both p<0.05), but no difference between UIC and UIQ. Together, these two sets of results indicate that baseline conditio timing data, indi participants behaved very differently in the three baseline felt fast conditions, for exploratory tasks, using significantly fewer favourably in any queries (with UIC) and significantly more refinements. Table 5: Freq Table 3: log data for exploratory tasks (*=significant) three co Mean (std) UIQ UIC UIF Frequency of ch Queries (#) * 3.11 (1.49) 1.44 (0.51) 2.44 (1.29) p<0.0005 to correct Quickest Refinements (#) * 2.17 (0.86) 1.78 (0.65) 3.39 (2.23) p<0.005enjoyment du Most Page visits (#) * 2.55 (1.04) p<0.005(0.69) 1.61 p<0.05 (0.75) 2.11 p<0.01 appealing des Most Time on task (s) * 190 (3.17) 169 (2.82) 177 (2.95) p<0.01 p<0.05 In exploratory tasks, participants visited significantly more 5. DISCUSSI Our study has p pages in the original condition (F(51,2)=5.615, p<0.01), research question where a post-hoc TukeyHSD saw only one key difference support searcher between UIQ and UIC. This finding may indicate that have a fixed form participants were able to find more relevant pages earlier inDr Max L. Wilson but hard to find a http://cs.nott.ac.uk/~mlw/
  53. 53. refinements in the faceted UIF condition (F(51,2)=6.245, The choices high p<0.005). Again, a post-hoc TukeyHSD revealed enjoyed and pref significant differences between UIF and the two despite believing Exploratory tasks alternatives (both p<0.05), but no difference between UIC and UIQ. Together, these two sets of results indicate that baseline conditio timing data, indi participants behaved very differently in the three baseline felt fast conditions, for exploratory tasks, using significantly fewer favourably in any queries (with UIC) and significantly more refinements. Table 5: Freq Table 3: log data for exploratory tasks (*=significant) three co Mean (std) UIQ UIC UIF Frequency of ch Queries (#) * 3.11 (1.49) 1.44 (0.51) 2.44 (1.29) p<0.0005 to correct Quickest Refinements (#) * 2.17 (0.86) 1.78 (0.65) 3.39 (2.23) p<0.005enjoyment du Most Page visits (#) * 2.55 (1.04) 1.61 (0.69) 2.11 (0.75) p<0.01 appealing des Most Time on task (s) * 190 (3.17) 169 (2.82) 177 (2.95) p<0.01 5. DISCUSSI In UIC - fewer queries, fewer refinements, less page visits, and faster - exploratory tasks, participants visited significantly more Our study has p pages in the original condition (F(51,2)=5.615, p<0.01), research question where a more use of refinements (overall) and faster than UIQ - UIF - post-hoc TukeyHSD saw only one key difference support searcher between UIQ and UIC. This finding may indicate that have a fixed form participants were able to find more relevant pages earlier inDr Max L. Wilson but hard to find a http://cs.nott.ac.uk/~mlw/
  54. 54. Subjective Responses Measure Simple Easy of Use UIQ & UIC > UIF Satisfaction UIQ & UIC > UIF Question UIQ UIC UIF Quickest to correct answer 11 5 2 Most enjoyed during task 4 11 3 Most appealing design 5 11 2Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
  55. 55. Motivation Related Work Information vs Interaction Design Results DiscussionDr Max L. Wilson http://cs.nott.ac.uk/~mlw/
  56. 56. Hypotheses Revisted H1:"Searchers"will"be"more"efficient"with"more" powerful"interaction,"using"the"same" metadata,"when"completing"search"tasks. • In Simple tasks - participants were faster with UIC • In Exp tasks - participants were better in all 4 measures with either UIC. - UIF was faster than UIQ, making more use of refinementsDr Max L. Wilson http://cs.nott.ac.uk/~mlw/
  57. 57. Hypotheses Revisted H2:"Searchers"will"enjoy"more"powerful" interaction,"despite"using"the"same" metadata. • UIC was preferred and given high satisfaction/ease of use ratings • UIF - however - was not. - Participants were split in opinionDr Max L. Wilson http://cs.nott.ac.uk/~mlw/
  58. 58. Hypotheses Revisted H3:"Searchers"will"use"query"recommendations"more" when"they"are"presented"differently." • Yes - For Exploratory tasks onlyDr Max L. Wilson http://cs.nott.ac.uk/~mlw/
  59. 59. Limitations • UIF - was not perfect • Auto-suggest - was not considered • Measurements - were limited - not easy to say if differences meant ‘better’ - we had no sense of relevance - could benefit from TREC style measurements • Num Participants - was not bigDr Max L. Wilson http://cs.nott.ac.uk/~mlw/
  60. 60. Conclusions What did we actually learn? • We did see different behaviour in all 3 conditions • People were good at simple tasks with original UIQ • People were faster and more effective with UIC and preferred it • People used more filters and viewed fewer pages with UIF but did not like it so much • But is it better or worse behaviour?Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
  61. 61. Future Work Query dataDr Max L. Wilson http://cs.nott.ac.uk/~mlw/
  62. 62. Future Work Clustered Faceted Query data algorithms metadataDr Max L. Wilson http://cs.nott.ac.uk/~mlw/
  63. 63. Future Work Facets Clusters Performance Suggestions (hypothetically)Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/
  64. 64. Dr Max L. Wilson http://cs.nott.ac.uk/~mlw/

×