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Human Computer Interaction Introduction

Human Computer Interaction Introduction. Dr Pradipta Biswas, PhD ( Cantab ) Assistant Professor Indian Institute of Science https://cambum.net/. Content. What is HCI User Modelling Usability Evaluation Virtual Reality, Augmented Reality and Multimodal interaction.

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Human Computer Interaction Introduction

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  1. Human Computer InteractionIntroduction Dr Pradipta Biswas, PhD (Cantab) Assistant Professor Indian Institute of Science https://cambum.net/

  2. Content What is HCI User Modelling Usability Evaluation Virtual Reality, Augmented Reality and Multimodal interaction Pradipta Biswas, I3D Lab, pradipta@iisc.ac.in

  3. Human Computer Interaction H C I Pradipta Biswas, I3D Lab, pradipta@iisc.ac.in

  4. Different disciplines • Human • Psychology • Cognitive • Social • Ergonomics • Ethnography and so on • Computer • Graphics • Artificial Intelligence • Software Engineering and so on • Others • Design • Mathematics • Statistics…………. Pradipta Biswas, I3D Lab, pradipta@iisc.ac.in

  5. Early computer - ENIAC Pradipta Biswas, I3D Lab, pradipta@iisc.ac.in

  6. IBM PC – 1980s Pradipta Biswas, I3D Lab, pradipta@iisc.ac.in

  7. Approx. time line (from Prof. B. Myers) Pradipta Biswas, I3D Lab, pradipta@iisc.ac.in

  8. Present status Integration of TV and mobile devices Gesture control and speech recognition (e.g. Microsoft‘s KINECT) Second screen: Tablet PCs Smart Remote Controls 8

  9. HCI Conferences Pradipta Biswas, I3D Lab, pradipta@iisc.ac.in

  10. HCI Journals Pradipta Biswas, I3D Lab, pradipta@iisc.ac.in

  11. User Modeling in HCI Pradipta Biswas, I3D Lab, pradipta@iisc.ac.in

  12. Model MODEL Theory Observations Pradipta Biswas, I3D Lab, pradipta@iisc.ac.in

  13. Outline • Types of Models • HCI Models • Introduction • Variations • Characteristics • Open Questions Pradipta Biswas, I3D Lab, pradipta@iisc.ac.in

  14. Types of Models • Exploratory • Observation -> Model • Predictive • Model->Prediction Pradipta Biswas, I3D Lab, pradipta@iisc.ac.in

  15. Pradipta Biswas, I3D Lab, pradipta@iisc.ac.in User Model

  16. Modelling Human Fitts’ Law, Hick’s Law, Marr’s model of Vision Command Language Grammar @ Xerox Parc Model Human Processor Pradipta Biswas, I3D Lab, pradipta@iisc.ac.in

  17. HCI Models GOMS Formal Grammar Cognitive Architectures Mixed approaches Application specific models Pradipta Biswas, I3D Lab, pradipta@iisc.ac.in

  18. GOMS • Goal • Open a folder • Operator • Move mouse • Click mouse • Press <enter> • Method • Double click on the icon • Select the icon and press <enter> • Right click on the icon, select <open> from the pop-up menu • Selection Pradipta Biswas, I3D Lab, pradipta@iisc.ac.in

  19. Variations • CMN-GOMS • The original GOMS • KLM: the simplest one, no method, only 6 operators • Pressing a key • Moving the pointing device to a specific location • Making pointer drag movements • Performing mental preparation • Moving hands to appropriate locations, and • Waiting for the computer to execute a command. • CPM-GOMS • Exploit parallelism in working • NGOMSL, GLEAN… Pradipta Biswas, I3D Lab, pradipta@iisc.ac.in

  20. Characteristics • Serial processing (initially) • Extensively used in HCI • Expert performance • Errorless performance Pradipta Biswas, I3D Lab, pradipta@iisc.ac.in

  21. Formal Grammars Modelling language Operations -> Terminal symbols Interaction -> Set of rules Knowledge -> Sentence Pradipta Biswas, I3D Lab, pradipta@iisc.ac.in

  22. Variations • Task Action Language (TAL) • Minimizing size of grammar • Task Action Grammar (TAG) • Consistency • Simple tasks Pradipta Biswas, I3D Lab, pradipta@iisc.ac.in

  23. Characteristics • Model competence, not performance • Can model knowledge and learning • Difficult to define a unique set of simple tasks Pradipta Biswas, I3D Lab, pradipta@iisc.ac.in

  24. Cognitive Architectures Introduced in 1972 Carnegie Symposium Unified theories of Cognition Virtual human Pradipta Biswas, I3D Lab, pradipta@iisc.ac.in

  25. Variations • SOAR • Rule based system • Impasse and Chunking • ACT-R • Hybrid architecture • Spreading activation • EPIC • Perceptual and Motor processing • CORE • Constraint satisfaction problem Pradipta Biswas, I3D Lab, pradipta@iisc.ac.in

  26. Characteristics (Theoretically) • Can model any performance • Extensively used to model psychological experiments • Need detailed knowledge of psychology • Yet to be used to model complex interactions • Parameter tuning Pradipta Biswas, I3D Lab, pradipta@iisc.ac.in

  27. Mixed Approaches Simplicity of GOMS + Details of Cognitive Architectures Pradipta Biswas, I3D Lab, pradipta@iisc.ac.in

  28. Variations Programmable User Model (PUM) ACT-R Simple…… Pradipta Biswas, I3D Lab, pradipta@iisc.ac.in

  29. Characteristics Lost Lost Simplicity of GOMS + Details of Cognitive Architectures Pradipta Biswas, I3D Lab, pradipta@iisc.ac.in

  30. Application specific models User Profile Inference Machine Output • Online recommender system • eLearning system • Web link prediction Pradipta Biswas, I3D Lab, pradipta@iisc.ac.in

  31. Open questions • Optimum fidelity • Level of details • What to model • Performance, Knowledge, Competence.. • When to model • User trial • More experiments… Pradipta Biswas, I3D Lab, pradipta@iisc.ac.in

  32. Usability Evaluation Pradipta Biswas, I3D Lab, pradipta@iisc.ac.in

  33. Why we need it Pradipta Biswas, I3D Lab, pradipta@iisc.ac.in

  34. Why we need it Pradipta Biswas, I3D Lab, pradipta@iisc.ac.in

  35. Why we need it Pradipta Biswas, I3D Lab, pradipta@iisc.ac.in

  36. Strategies • Heuristic evaluation • Guidelines • Cognitive walkthrough • Think aloud protocol • Cognitive dimensions of notation • Simulation • Survey • Controlled experiment Pradipta Biswas, I3D Lab, pradipta@iisc.ac.in

  37. Heuristic evaluation • Nielsen's Usability Heuristics • Visibility of system status • Match between system and the real world • User control and freedom • Consistency and standards • Error prevention • Recognition rather than recall • Flexibility and efficiency of use • Aesthetic and minimalist design • Help users recognize, diagnose, and recover from errors • Help and documentation Pradipta Biswas, I3D Lab, pradipta@iisc.ac.in

  38. Guidelines Pradipta Biswas, I3D Lab, pradipta@iisc.ac.in

  39. Issues • Easy to use • Needs multiple evaluators • Tools available for automatic checking (http://www.w3.org/WAI/RC/tools/complete) , but not works for all • E.g.: Checking usability / accessibility of dynamic web content Pradipta Biswas, I3D Lab, pradipta@iisc.ac.in

  40. Cognitive walkthrough Experts simulate users’ interaction Walkthrough high frequency to low frequency tasks Good for exploratory interfaces Can quickly identify errors/ wrong assumptions in structure /sequence of interfaces Pradipta Biswas, I3D Lab, pradipta@iisc.ac.in

  41. Think aloud protocol • Users undertake task while ‘thinking aloud’ • Provides rapid, high-quality, qualitative user feedback • Allows meaningful, direct dialogue • Designer understands users’ way of thinking and can clarify • Can be video recorded for later analysis Pradipta Biswas, I3D Lab, pradipta@iisc.ac.in

  42. Prototype Systems Best Alternative Simulation User Testing New Systems Interaction Patterns Existing Systems Evaluation through simulation Pradipta Biswas, I3D Lab, pradipta@iisc.ac.in

  43. Surveys • IBM User Satisfaction Questionnaire • Usefulness • Information quality • Interface quality • Shneiderman’s Questionnaire for User Interaction Satisfaction • System Experience • User reaction • Screen design • Learning • On line tutorial and so on Pradipta Biswas, I3D Lab, pradipta@iisc.ac.in

  44. Issues • Easy to collect a lot of data • Needs careful consideration in • Questionnaire design • Avoid negative or double question • Experimenter’s bias • Easy to crowd-source • People tend to pretend ‘good’, which may not be true in reality Pradipta Biswas, I3D Lab, pradipta@iisc.ac.in

  45. SUS Pradipta Biswas, I3D Lab, pradipta@iisc.ac.in

  46. Cognitive Load Measurement • NASA TLX • Average performance • Peak Performance • System Usability Scale • Bedford Workload Scale (BWS) Pradipta Biswas, I3D Lab, pradipta@iisc.ac.in

  47. NASA TLX Pradipta Biswas, I3D Lab, pradipta@iisc.ac.in

  48. BWS Pradipta Biswas, I3D Lab, pradipta@iisc.ac.in

  49. Controlled experiments Psychological experiment in controlled laboratory setting Results suitable for formal statistical analysis Good to measure effect of an interface or interaction on users’ performance Not suitable for exploratory analysis or at design phase, should be used as a confirmatory test Pradipta Biswas, I3D Lab, pradipta@iisc.ac.in

  50. Other techniques • Pluralistic walkthrough • uses group meetings where users, developers, and human factors people step through a scenario, discussing each dialogue element. • Feature inspection • lists sequences of features used to accomplish typical tasks, checks for long sequences, cumbersome steps, steps that would not be natural for users to try, and steps that require extensive knowledge/experience in order to assess a proposed feature set. • Consistency inspection • designers who represent multiple other projects inspect an interface to see whether it does things in the same way as their own designs. • Standards inspection • an expert on an interface standard inspect the interface for compliance. • Formal Inspection • Experts hold courtroom style meeting with designers Pradipta Biswas, I3D Lab, pradipta@iisc.ac.in

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