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DfR Final Presentation

DfR Final Presentation






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    DfR Final Presentation DfR Final Presentation Presentation Transcript

    • Team JSTOR/Group 1:
      Morgan Burton Isabela Carvalho Stan (Tze-Hsiang) Lin Leo (Lei) Shi
      Data for Research (DfR) for JSTOR
    • Introduction to DfR
      System that includes metadata, information visualization, and article retrieval for JSTOR articles
      JSTOR is a major database of scholarly articles
      Provides “facets” or “selectors” that allow the user to filter their search based on specific elements such as journal, author, and discipline
      Provides graphs that update dynamically based on search query
      User base:
      User might be a researcher such as a doctoral student in linguistics, or a more casual researcher interested in comparing trends across disciplines (not exhaustive)
    • Methods
      Interaction map
      Provides a map of the sections of the site
      Personas and Scenarios
      A glimpse at what the typical user and situation might be for the system
      5 Interviews conducted on potential users
      Comparative Analysis
      We assessed several competitive systems including Google Scholar and NINES
      We surveyed over 20 target users
      Heuristic Evaluation
      An evaluation of general usability principles
      Usability Testing of 5 target users
    • Chart for interaction map
      Diff. Views:
      Charts, Graph
      Results List
      Keyterm Cloud
      Data Set
      Of DfR
      Data Set
      Down by USER
    • Finding: The overall purpose of DfR is clear to users at first glance – prior to interacting with the system
      Usability testing result: we tested prior finding from heuristic analysis that purpose of site might be unclear at first glance
      We asked users to fill out pre-task assessments where we asked them to answer questions about their expectation of the system
      Form asked users about what their general idea of the site was
      Result: User expectation matched what site was about and accurately inferred relationship to JSTOR
    • Evidence and recommendation
      Some answers provided by users:
      “The statistics about the publications, categorized by publication year, discipline.”
      “I think it's a site that gives information about articles published on certain topics.”
      “Searching for scholarly articles by date and discipline/area.”
      “This is a websites showing some statistics about paper publications and properties in JSTOR.”
      Recommendation: (contrary to prior finding) do not include an explanatory sentence on the main page about DfR
      Users have a good sense of what DfR is and what its relationship to JSTOR is
    • Finding: lack of visual indication of interrelationship between search and select features
         ’Results list’, ‘key term’, and ‘references profile’ features are tightly linked to the main search
      Current layout does not give an indication that ‘results list’, ‘key term’, and ‘reference profile’ are not separate content, but are about the search query done on the main page
      There is a hierarchy
      Evidence: usability test
      Some users did not understand that under the article list they would see the results of the search done on the main page
    • Comparison of versions
      Location indicates incorrect hierarchy
      Current Version
      Appearance of being in the same frame indicates closer relationship
      Previous Version
    • Older version took advantage of proximity
    • Recommendation
      Move search bar to a higher level in order to indicate the hierarch between search and given search elements: the given elements are under the search level
      Have the links placed under the search bar, inside the grey box.
    • Cognitive model & usability
      • Designer v. User
      “It’s like Google Scholar”
      Instances of expectations v. reality using Data for Research
      • Search
      • Key Terms
      Finding: The cognitive model of users and design of DfR are divergent.
    • The way people think for the purposes of comprehension and prediction
      Significance: for people to understand how to use the Data for Research tool, designers must understand the way they already think
      Usability: After purpose, there must be positive interaction in function for repeat use
      Cognitive Model: Defined
    • “It’s like Google Scholar” (but it isn’t!)
    • Refined
      Data Set
      Data Set
      Data Set
      Data Set
      Data Set
      Of DfR
      Data Set
      Search #1
      Search #2
      Search #2 IF NOT “Clear All”
      Search #1
      Other Database Search
      Search in DfR
    • Instance: Search aggregation
      - search terms accumulate, rather than reset on new search
      (EXCEPT WHEN going directly to index)
    • Instance: Keyword searching + blank spaces
      - all produce DIFFERENT search results
      - punctuations have different treatment in the DfR interface
    • Recommendations
      Search aggregation:
      Clearer path for new search vs. adjusting current search (“New Search” button)
      Keyword punctuation:
      Choose & specify one punctuation as AND operator
      Clarify how search results are accumulated (using all terms? listing by articles and journals with higher frequency?)
    • Search record is crucial to researchers - must keep track of information they gather
      Duplication of search in results view indicates system action to users
      After-search feedback
      Finding: A lack of DfR system feedback left searches with unclear meanings.
    • Lack of system feedback before and after making a search
      - No tracking or matching of search terms
      No indication that anything has happened!
      - Selection criteria box is not prominent enough to notice
    • Facets/Selectors
      New version:
      Not intuitive that the NAMES are links
      Further, cannot determine what they are doing to the results
      (start with selection ALL included?)
      Older version:
      Check and “X” boxes
      Much clearer
      • intuitive as to what is happening when “checking” (adding) or “X”-ing (subtracting) aspect of information
    • Recommendations
      Search Feedback:
      Additional feedback after search that indicates search has been performed
      Google Scholar model: redundancy WORKS!
      Header renaming to “Search Results”
      Facet/Selector Appearance:
      Reinstate the "X" function for all selectors (option to eliminate from results or from search entirely)
      Reinstate "checkmark" function for facets that have been eliminated or are not included in the results.  
    • Summary
      For (finding 1)...for marketing purposes, a description of DfR is NOT needed on the main page - it’s intuitive to users!
      For (finding 2)...take advantage of X to Y. <-- not sure what to put here.
      For (finding 3)...similar cognitive models will lead to positive interactions between the system and new users.
      For (finding 4)...clear feedback leads to discernible meaning of search results.