1. APCS Nguyen Ngoc Dan Vy – 0612755 Tran Thi Hong Diem – 0612701 Instructor: Do Lenh Hung Son

2. Contents Introduction 1 Understanding User’s Behavior 3 Automatic Tab Ordering 4 Evaluation 5 Contribution & Conclusion 6 Related Works 2

3. Contents Introduction 1 Understanding User’s Behavior 3 3 Automatic Tab Ordering 4 4 Evaluation 5 5 Contribution & Conclusion 6 6 Related Works 2 2

4. Internet Usage Statistics 93% 74%

5. Popular web browsers Web Browsers

6. Introduction Problems Find tabs Access tabs Manage opened tabs

7. Clarification Human Computer Interaction Problem does not exist advanced Research Oriented Introduce new concept

8. Clarification  Ways to approach: HCI User - Based

9. Approach User Centered design Evaluation Controlled experiment: 10 participants Effectiveness: 10-14% User behavior analysis Field study Online survey Prototyping Most Used Tabs Instant Access Fast Tab Switching Introducing concept Automatic Tab Ordering

10. Contents Introduction 1 1 Understanding User’s Behavior 3 3 Automatic Tab Ordering 4 4 Evaluation 5 5 Contribution & Conclusion 6 6 Related Works 2

11. Related Work Tabs Multitasking D.Am, A.Spink and M.Park, “Information and non-information multitasking interplay”.

12. Related Work Tabs Multitasking Web Browsing Activity Web Browsing Activity M.Kellar, C.Watters, K.M.Inkpen “An exploration of web-based monitoring:Implications for design” (CHI 2007)

13. Related Work Tabs Multitasking Web Browsing Activity Web Browsing Activity Webpage Revisitation: 30% L.Tauscher and S.Greenberg “Revisitation patterns in world wide web navigation” in CHI 97

14. Related Work Tabs Tab Grouping Multitasking Web Browsing Activity Web Browsing Activity Webpage Revisitation: 30% Webpage Revisitation: 30%

15. Related Work Tabs Tab Grouping Multitasking Web Browsing Activity Web Browsing Activity Webpage Revisitation: 30% Webpage Revisitation: 30% Visual Aid Foxtab: tab preview panel

16. Related Work Tabs Tab Grouping Multitasking Visual Aid Web Browsing Activity Web Browsing Activity Webpage Revisitation: 30% Webpage Revisitation: 30% Tab Representation

17. Contents Introduction 1 Understanding User’s Behavior 3 Automatic Tab Ordering 4 Evaluation 5 Contribution & Conclusion 6 Related Works 2

18. Field Study 7 users: 3F 4M. Age:22-25 Position: developer, designer, officer, researcher. 7 users: 3F 4M. Age:22-25 Position: developer, designer, officer, researcher. Explore how users work with browser. Interview: usage trend& difficulties. Explore how users work with browser. Interview: usage trend& difficulties. PurposeParticipants LocationSet Up PersonalVibe. 2 week duration. Run in background. Collect data: Software Interview PersonalVibe. 2 week duration. Run in background. Collect data: Software Interview Selab- Software Engineering Lab in University of Science.

19. Field Study Figure 2: One participant in this study.Figure 1: Selab- Software Engineering Lab in University of Science.

20. The amount of time using Firefox browser Data collected by Personal Vibe)

21. Semi-structured Interview “I need a tool to support me in managing tabs automatically.” “I think if I can arrange tabs in many rows, it would be better” “I want to put related tabs in same groups.” “It takes me a lot of time to find and switch when opened many tabs. I am really uncomfortable!” Number of opened tabs? Number of worked tabs? When open many tabs? 8 questions Problems with tabs? Order of tabs?

22. Semi-structured Interview A Most users opened many tabs( over 15 tabs). B Searching requires open a lot of tabs C Lost tabs' trace when opening too many tabs. D Remark the order of tabs.

23. Online Survey OnlineSurvey 1 Large population. (30 participants). General tendency of participants 2 Participants: knowledgeable workers 3 4 Created by Google Spreadsheet Form (Include 17 questions)

24. Online Survey  Analysis

25. Findings APCS 1 User spend a lot of time for web browsers. 2 Searchingrequires a lot of tabs. 3 Finding & switching tabs waste time. 4 Difficulties in managing opened tabs 25% users open >= 15 tabs

26. Contents Introduction 1 Understanding User’s Behavior 3 Automatic Tab Ordering 4 Evaluation 5 Contribution & Conclusion 6 Related Works 2

27. Concept Most Used Tabs Instant Access Free Tab Switching Tab Dummy Permanent Ranked Tabs Automatic Tab Ordering Implement on Firefox Fast Tab Switching Manualmarking Tabs Automarking Tabs

28. Finding a common equation Rank = α*No.Access + β*ActiveTime + γ*ElapsedTime Domain (α,β,γ ) = R Number of Access: number of clicks to access the tab ActiveTime: time when the tab is active (miliseconds) ElapsedTime: time when the tab is opened (miliseconds).

29. Final Equation Rank = 1*No.Access + 0.00005*ActiveTime + 0*ElapsedTime In this particular case: web browsing: Favor Number of Access. ElapsedTime does not contribute weight. Many zeros: time is calculated in miliseconds

30. Prototypes Develop 5 in total, evaluate 2. No concerning about optimization, memory management, etc. Implement in Firefox (result from online survey). Use JavaScript & XUL. A tool for demonstration.

31. Most Used Tabs Instant Access  Prototype 1.1: Free Tab Switching.

32. Most Used Tabs Instant Access  Prototype 1.2: Tab Dummy.

33. Most Used Tabs Instant Access  Prototype 1.3: Permanent Ranked Tabs.

34. Most Used Tabs Instant Access  “List all tabs” button.

35. Fast Tab Switching  Prototype 2.1: Manualmarking Tabs.

36. Fast Tab Switching  Prototype 2.2: Automarking Tabs.

37. Contents Introduction 1 Understanding User’s Behavior 3 Automatic Tab Ordering 4 Evaluation 5 Contribution & Conclusion 6 Related Works 2

38. Evaluation Pilot test Evaluation Result

39. Independent Variables Firefox with installed Tab Dummy Prototype. Default Firefox. Firefox with installed Permanent Ranked Tabs Prototype. Condition 1Condition 2Condition 3

40. Dependent Variables Performance Measures Number of scroll buttons clicked Time spent switching tabs Attitudinal Measures Self-reported workload (NASA TLX) Subjective feedbacks

41. Hypotheses 1 Number of scroll buttons clicked decreases in condition 2-3. 2 Time spent switching tabs decreases in condition 2-3. 3 User workload & stress decreases in condition 2-3.

42. Pilot Test PurposePurposeQuestionnairesQuestionnaires Task Description -2 specific keywords : one text, one image. -Keywords must be unpopular. -One question/ page.  Require to open many tabs and multitasking. - Perform searching tasks. - 45 minutes. - 14 participants. - 3 conditions. Get first impression of users in real context.

43. Feedback & Improvement Change questionnaires to open more tabs Synchronize interaction Divide participants to smaller group. Improvement for control experiment

44. Controlled Experiment 1 10 participants. Same configurations 2 3 conditions. 45 minutes each. 3 4Searching task and answer questionnaires proposed by us.

45. Evaluation – Result  Overall result: Mental’s stress and workload decreases:  Tab Dummy: 10%.  Permanent Ranked Tabs: 14%.

46. Contents Introduction 1 Understanding User’s Behavior 3 Automatic Tab Ordering 4 Evaluation 5 Contribution & Conclusion 6 Related Works 2

47. Contribution - Impact Web Browsers Text Editors IDEs Any Serial lists OS: Taskbar

48. Future Works 2 nd Category Platforms Experiment. Controlled Experiment. Fast Tab Switching: Continue development Controlled Experiment Implement in various platforms: Text editors, IDE. Oss Experiment. Platform differences

49. Conclusion Benefits large population No existing Efficient technique Challenge Traditional Tab order Automatic Tab Ordering Automatic Tab Ordering Reduce stress Users’ workload Reduce stress Users’ workload Problems With Tabbed Browsing

50. APCS