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The New Web Browsers: They’re Cool but Are They Useful? Mary Czerwinski & Kevin Larson Microsoft Research August,1 PowerPoint Presentation
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  1. The New Web Browsers:They’re Cool but Are They Useful? Mary Czerwinski & Kevin LarsonMicrosoft ResearchAugust,1997

  2. Classic UI Problems with Searching... • The major classes of user problems (e.g., Hertzum & Frokjaer, 1996; Tonta, 1992): • Logical Queries • ~10% syntactically incorrect • ~30% using AND or OR misrepresent the users’ intent (e.g., Ss expect OR to bind the terms more strongly than AND) • Users use AND more often than OR (few NOTs) • Formal rules of logical expression are cumbersome when users are focusing on search task HCI ‘97 Bristol, U.K.

  3. Search UI Problems... • Query Simplicity • ~30% queries are kept very simple (often 1 word) with today’s UIs • Users prefer to tackle query richness through sequences of queries • 1st query is initial, incomplete attempt (“anchoring” a la Tversky & Kahneman, 1974) • Ss may not stray far from initial attempt • User’s query syntax may not match system’s indexing HCI ‘97 Bristol, U.K.

  4. Search UI Problems… • Hierarchy Search • Most discriminating headings are at the bottom of the hierarchy, not at the top • Breadth/depth tradeoff (Norman, 1991) • More depth hurts past 3 levels (users required to backtrack too far and get lost)--anchoring • More breadth at top means headers will be more discriminable • Tree hierarchy UIs can mitigate some of these problems HCI ‘97 Bristol, U.K.

  5. Search UI Problems… • User Satisfaction • Influenced by user expertise and search goals • Strongest predictors of satisfaction (e.g., Bates, 1977; Saracevic & Kantor, 1988): • precision of search--more valued than recall (a few good retrievals valued even if a couple are missed) • amount of time saved • perceived quality of the db as a reference source HCI ‘97 Bristol, U.K.

  6. UI Problems Specific to the Web • Users need global and local info when searching large spaces of WWW • Global---used to guide lower-level, detailed tracking of information during a query • Both levels of detail cropping up in new browsers • Lack of empirical evidence of benefits • Do they address classic search UI problems? HCI ‘97 Bristol, U.K.

  7. New Browsers: The Claims • Techniques attempt to exploit pattern perception to enable preattentive interaction (e.g.,Eick, 1997) • Cognitive capacity freed up so user can attend to relevant info related to the search task HCI ‘97 Bristol, U.K.

  8. More Claims • A formula for the next generation UI (Card, 1997) : • Perceptually-loaded, • Use human, time-layered interaction (use human interaction times + object constancy), • Rely on focus + periphery, animated transitions, enlarged, 3D spaces and moving points of view HCI ‘97 Bristol, U.K.

  9. Goals of Research • Initial attempt to track user performance across info vis techniques during queries • Hyperbolic browser versus hierarchical tree • Performance and preference data collected • “Lostness” measures and spatial abilities tracked HCI ‘97 Bristol, U.K.

  10. Experiment 1--Method • 17 Ss--all Internet users and pc-savvy • Within Ss design • Order of browser use counterbalanced • Eight search tasks chosen randomly from Encarta • All Ss carried out the same 8 search tasks • Subjective data collected immediately after using each browser HCI ‘97 Bristol, U.K.

  11. Materials • 512 lower-level entries from Encarta placed onto the web • Hierarchical structure built using same category headers as exist in Encarta today • 3 levels of eight items in hierarchy HCI ‘97 Bristol, U.K.

  12. HCI ‘97 Bristol, U.K.

  13. Experiment 1--Results • Lostness: • Factors optimal path, total no. nodes traversed, total no. of unique nodes • Smith defined lostness as any score greater than 0.5, and any score less than 0.4 as not-lost • Hyperbolic browser = 0.39 (S.D. = 0.28), tree browser = 0.33 (S.D. = 0.26) N.S. HCI ‘97 Bristol, U.K.

  14. Experiment 1--Results HCI ‘97 Bristol, U.K.

  15. Experiment 1--Results • Subjective Measures Hyperbolic Browser Tree I liked it. (Disagree=1, Agree =5) 2.5 3.35 I will use this software on a regular basis. 2.53 3.58 I will recommend this software to others. 2.59 3.47 It was easy to get where I wanted to go. 3.05 3.88 Each area of the software was clearly marked. 2.82 4.41 This software uses new technology. 3.47 1.82 This software provides valuable information. 4 3.82 This software provides topic breadth (or variety). 3.88 3.47 This software provides depth (or detail of information). 3.76 3.82 This software has appealing graphics. 2.35 1.7 This software is easy to use. 3.17 4.64 This software feels unique. 4.29 1.82 This software feels familiar. 2.65 4.76 Overall Average Rating 3.19 3.46 HCI ‘97 Bristol, U.K.

  16. Experiment 1--Conclusion • Usability issues with both browsers • Item difficulty drove performance and preference • Tree better for tracking where you’d been, familiarity • Hyperbolic browser better for keeping global/local focus, seeing category size and related topics HCI ‘97 Bristol, U.K.

  17. Experiment 2--Motivation • Better control for item difficulty by semi-randomly choosing query for each user, browser and trial • Visual scanning and spatial visualization pre-tests • Tutorial • More training with each browser (12 queries instead of 4) HCI ‘97 Bristol, U.K.

  18. HCI ‘97 Bristol, U.K.

  19. HCI ‘97 Bristol, U.K.

  20. Experiment 2--Method • 16 Ss, all pc and web-savvy, ages 18-60 • Tree hierarchy and hyperbolic browser • Within Ss design, all 512 end nodes were potential search targets • 12 searches per browser, browser order again counterbalanced • RTs, subjective measures, lostness and spatial ability pretest DVs HCI ‘97 Bristol, U.K.

  21. Experiment 2--Results • Lostness: • No difference in lostness • Both hyper and tree browsers scored .38 • Spatial ability • More predictive of fast hyperbolic searching (r=-.47 for hyper, -.39 for tree) HCI ‘97 Bristol, U.K.

  22. Experiment 2--Results HCI ‘97 Bristol, U.K.

  23. Experiment 2--Results Hyper Tree Which browser did you like better? 9 7 I liked the browser. (Disagree=1, Agree=5) 3.5 3.62 Right when I started, I knew what I could do with the browser. 3.38 4.44** It was easy to get where I wanted to go with the browser. 3.8 4.1 The browser uses new technology. 3.06 1.5** The browser has appealing graphics. 3.94 2** The browser is easy to use. 3.94 4.19 • Subjective Measures HCI ‘97 Bristol, U.K.

  24. Experiments 1 &2--Discussion • No significant advantage for either browser • Tree hierarchy good for tracking traversal path if used systematically; overviews • Hyperbolic browser best for keeping global/local info in focus; category relatedness and size HCI ‘97 Bristol, U.K.

  25. Experiment 3--Perspecta® • Hyperkinetic text and “fly-throughs” • Clients include CineMap, AllTheNews and others • Global and local information maintained, as well as “related topics” and cross-references • Previews of categories before committing HCI ‘97 Bristol, U.K.

  26. Experiment 3---Perspecta® HCI ‘97 Bristol, U.K.

  27. Experiment 3--Method • 9 Ss, all PC and web-savvy • 18-60 years old, mode=25-35 • Access the web 4 or more times/week, on avg. • 14 movie title searches in CineMap • 1st search unassisted, tutorial before searches 2-14 • Same DVs as Exp. 1 and 2 (no lostness) HCI ‘97 Bristol, U.K.

  28. Experiment 3--Results Subjective Questionnaire Avg. Rating • Spatial pretest mildly related to search speed: r=-.28 HCI ‘97 Bristol, U.K.

  29. Experiment 3--Usability Issues • 1 or 2 clicks? • Lack of control in time and space • Category header issues • Too many cross-refs • Related topics trap • Confusion: headers v. titles and links • Small text difficult to read • RSI HCI ‘97 Bristol, U.K.

  30. Experiment 3--Good Features • User can “sniff” around without committing • Use size of category to guide search • Use related topics • Use popup titles and info without flying in • Cool! HCI ‘97 Bristol, U.K.

  31. Conclusion--Are They Useful? • None are Boolean! Users like visual UIs • Can see local/global focus, size and relatedness (hyperbolic browser) • Can keep track of where you’ve looked (hierarchical tree) • Search hints with little user effort (PerspectaView, hyperbolic browser) HCI ‘97 Bristol, U.K.

  32. Conclusion: Are They Useful? • But problems remain: • Users not as overwhelmed with large sets but screen real estate challenges • User/system terminology mismatches & trust • Anchoring • Initial training investment is high • Issues with spatial reasoning abilities &/or age • Need multiple options for searching HCI ‘97 Bristol, U.K.