CS415 Human Computer Interaction

Transcription

1 CS415 Human Computer Interaction Lecture 6, Part 2 Implementation and Testing Tools for HCIs October 1, 2018 Sam Siewert

2 Minute Paper Summary - The Gurus Don Norman 1. make it fun (attributed to Fadell?) 2. fear changes mind state (attributed to Fadell?) 3. form over function (attributed to Fadell?) 4. think like a child (Norman or Fadell? Fadell - Jobs said always think like a beginner ) 5. context affects performance 6. Trying to look outside the box 7. and then theres (sic) this sticker (attributed Fadell?) Tony Fadell 1. Habituate (attributed to Norman?) 2. Think broader spectrum (attributed to Norman?) 3. But smaller details (attributed to Norman?) 4. No comment (??) 5. The battery thing is huge! 6. Creating something that is useable 7. pleasant designs always work better (attributed to Norman?) Sam Siewert 2

3 Minute Paper Summary - The Gurus I believe the Gurus provide an interesting point of view, but generally guidelines & standards I feel is (sic) more helpful overall. it would be pointless to advance products or designs that have no use scientists were so concerned if they would do they didn t stop to think if they should do [Can we, Should we? - common technology / HCI theme] They are helpful have experience in the field opportunity to experiment an idea of what does and doesn t work the ideal product to be (sic) a hybrid of experience and guidelines Gurus are helpful bring experience and explanations to the story Gurus can be helpful... They also can be harmful if they have a way of doing something and will not other ways Sam Siewert 3

4 Coming Up Quiz after fall break, 10/16-10/17 Material since first Quiz Chapters 5,6,7,8,9 On Canvas for practice Review After Break on Tuesday, 10/16 Exam on Thursday, 10/18 Chapters 1-9 Knowledge and Concepts True/False, Multiple-Choice, Short Answer Problem Solving Analysis, Design, Implementation, Test Sam Siewert 4

5 Context for all Applications Windows 7,8, 10 Linux / Unix X-Windows Ubuntu Red Hat (Centos) Fedora Mac OS-X Android OS ios Window Managers Sam Siewert 5

6 Client/Server Window Managers Window Managers like X-Windows are Client/Server Applications are Clients of the Window Manager The Server is the Window Manager Sam Siewert 6

7 C programming Low-Level to Widget Level GUI Code Generators X Series O Reilly Douglas Young Book X Protocol Xlib X toolkit X Widget Set (Motif, Athena) X-Window System Sam Siewert 7

8 Apple Macintosh Windowing System Macintosh and Mac SE ( ) Graphics Toolbox (ROM code for Drawing and Widgets) Common Look and Feel Simplified Programming for Interactive GUI/WIMP Applications Human- Computer Interaction, 3 rd Edition, by Alan Dix, Janet Finlay, Gregory Abowd, Russell Beale Sam Siewert 8

9 X-Windows Sam Siewert 9

10 Windowing System Widget Sets Windows OS-X Unix / Linux Sam Siewert 10

11 Android Studio for AOS Phone Emulators SDK - Java Apps Linux NDK (Native Development Kit) Skia Graphics Engine, SGL Mobile Development Sam Siewert 11

12 Mobile Considerations Location / time aware, Sensors (magnetometer, sound, camera) Outdoor and indoor use (sunlight), Security/Privacy, Cloud portal New Interaction Modes - Android Auto (NLP, Telematics), wearables Sam Siewert 12

13 Widget Application Updates Interactive Design Event Handlers Event Masks Register Call-back Update State Sam Siewert 13

14 WIMP Interaction Toolkit Interaction Widgets and Gadgets Simplify Development Sam Siewert 14

15 Class Hierarchy OO is Helpful, but Not Required X-Windows is Object-based C code Sam Siewert 15

16 Early Interactive Systems Development (Smalltalk - OO) Smalltalk and Model-View-Controller Interactive System Programming Xerox PARC Early 1980 s Sam Siewert 16

17 Modern OO Interactive System Development Java Swing, AWT, NetBeans Python, PyTk Qt Creator (C++) Visual Studio WinForm (C#) X-Windows (Object-based, but not OOP) Many more Java, Ruby, Objective-C, C++, C#, Python Sam Siewert 17

18 Interactive System Evaluation Testing Traditional SQA Usability However is a Specialized form of Testing and Evaluation Field Tests with Users (Human side of HCI) Sam Siewert 18

19 Cognitive Walkthrough Similar to Code Walkthrough, but with Focus on how easy a system is to use Cognitive Load Efficiency and Ability to Complete Tasks (User Community) Normally requires a Mock-up or Prototype Sam Siewert 19

20 Evaluation Method Answer 4 Questions for Each Step in Action Sequence (Task specified as a Goal) 1) Effect of Action Matches User Goal? 2) Action Visibility / Availability? 3) Recognition of Actions for Goals? 4) Visible Easy to Understand Feedback for Goal Attainment? Sam Siewert 20

21 How to Measure? - Heuristic Nielsen s Ten Heuristics 1. Visibility of Status 2. System / Real-World Match 3. User Control / Freedom 4. Consistency / Standards 5. Error Prevention 6. Recognition over Recall 7. Efficiency 8. Aesthetic Less is More 9. Design for Error 10. Built-in Help Sam Siewert 21

22 Empirical Methods of Evaluation Participants Real Users, Sample Size, Small and in Depth vs. Large and Shallow (Within or Between) Variables Those that are Changed for each evaluation (independent or IV) and those that are Measured (dependent or DV) E.g. Complete Task with WIMP GUI Widget #1 Complete Same Task with CLI Task Time, Efficiency and Correct Outcome Measured DVs CLI vs WIMP GUI Widget - IV Changed is Interaction Method Hypothesis Prediction of Outcome (to Test) If Differences in Measure can t be Explained by Chance (Null Hypothesis is Disproven) Outcomes Compared with Level of Significance (Sample Size, Mean, Standard Deviation, Reliability, Confidence, T-test) Sam Siewert 22

23 Empirical Methods of Evaluation Experimental Design Between-subjects and withinsubjects Between Subjects is Ideal, but Costly (need more subjects) Within Subjects is lower Cost, but Subjects learn, develop a bias, and results can be impacted Sam Siewert 23

24 General Usability Statistical Measures Looking to Serve the Majority of Users - Significance E.g. Can Most or Majority of Users Efficiently Complete a Test Task? Sam Siewert 24

25 Statistics Mapping to HCI Independent Variable (what is changed in each experiment) Dependent Variable (not changed e.g. goal or task) Analysis Technique (math to determine significance of results and model) Human- Computer Interaction, 3 rd Edition, by Alan Dix, Janet Finlay, Gregory Abowd, Russell Beale Sam Siewert 25

26 Icon Experiment from Book Sam Siewert 26

27 Evaluation through Participation Observer and Track User While Experiment is Run In addition to feedback from user In addition to other metrics (time, correctness) Human-Computer Interaction, 3 rd Edition, by Alan Dix, Janet Finlay, Gregory Abowd, Russell Beale An Automobile-Integrated System for Assessing and Reacting to Driver Cognitive Load, Pompei, Sharon, Buckley, Kemp, Sam Siewert 27

28 Color Coding Example from Book (p. 339) Sam Siewert 28