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ICS3211 lecture 02

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Lecture 2 - Intelligent Interfaces II, Faculty of ICT, University of Malta

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ICS3211 lecture 02

  1. 1. ICS3211 - Intelligent Interfaces II Combining design with technology for effective human- computer interaction Week 2 Department of Intelligent Computer Systems, University of Malta, 2016
  2. 2. Theoretical Frameworks in HCI Week 2 overview: • Intelligent Interfaces - a recap • Need for Intelligent interfaces • Difference between Intelligent Interfaces vs Interfaces for an intelligent system; • Components of Intelligent Interfaces • Human Information Processing - methods & models;
  3. 3. Learning Outcomes At the end of this session you should be able to: • Describe and recognise intelligent interfaces; • Explain the difference between an intelligent interface and an interface for an intelligent system; • List the components for Intelligent Interfaces • Compare different theories and their applications to the field of HCI; • Compare different information processing methods and models;
  4. 4. Recap • What have we discussed during the past week? • What important points have you acquired through the online discussions? • Describe your online post input in more detail. • Think of an intelligent interface; discuss with 2 other class members why it falls under the category of intelligent interfaces
  5. 5. Intelligent Interfaces • What are they? • Intelligent interfaces have two components: ✴ArtificiaI Intelligence (AI) ✴Computer Human Interaction (CHI) • Not every intelligent program/system has an intelligent interface. Why?
  6. 6. IUI Research Fields
  7. 7. A normal user interface is defined as a method of communication between a human user and a machine. If we extend this definition, we can say that an intelligent user interface uses some kind of intelligent technology to achieve this human-machine communication. In other words, IUIs are interfaces with the ability to adapt to the user, communicate with the user, and solve problems for the user.
  8. 8. “Intelligent user interfaces specifically aim to enhance the flexibility, usability, and power of human-computer interaction for all users. In doing so, they exploit knowledge of users, tasks, tools, and content, as well as devices for supporting interaction within differing contexts of use.” [Maybury 2001]
  9. 9. • Why do we need an intelligent interface? • Interfaces can get too complex • Interfaces can get too inflexible • Interfaces don’t change when our needs change • Interfaces don’t work with each other
  10. 10. • What makes an interface intelligent? • Adapts to different user needs • Learns new concepts and techniques • Anticipates users’ needs • Takes initiative and makes suggestions to user • Justifies actions taken
  11. 11. Difference between an Intelligent System and an Intelligent Interface
  12. 12. • How can user interfaces engage users to act more intelligently? • What empirical knowledge regarding the presentation of information can be applied in the design of user interfaces and dialog models? • How will users perceive and accept the evolving ability of computers to perform surrogate tasks correctly? • What are current and future potential models of interactive computing? • How useful are sophisticated reasoning and knowledge- base technologies in UI design?
  13. 13. Components of Intelligent Interfaces • The User Model • Multimodal Communication • Plan recognition • Dynamic Presentation • Natural Language • Intelligent Help • Interface Adaptability
  14. 14. User Model • Information which best describes the user, and which is used to determine how the data is presented; • Best used when: • system seeks to adapt behaviour to users; • class of users is diverse
  15. 15. • Uses of user models: • getting input from user; • providing help & advice; • understanding user’s information seeking behaviour; • providing output to user; • deciding what to say & how to say it;
  16. 16. Multimodal Communication • Uses of various methods of communication with an interface • Two purposes: • enables users to use system more intuitively; • gives users more freedom;
  17. 17. Plan Recognition • Deduces what user plans to do; • Takes into consideration: • system knowledge • user model; • user’s actions;
  18. 18. Dynamic Presentation • Different people view data in different ways; • System decides to display data based on user models; • Intelligent data displays from data entered in system
  19. 19. Natural Language • High degree of freedom on the user’s part; • Adds more intuitiveness to a system; • Makes system less cumbersome;
  20. 20. Intelligent Help • Help that is presented to the user, just in time; • System recognises that the user is facing a problem and suggests ways in which s/he can solve the problem
  21. 21. Interface Adaptability • System may adapt to user preferences without the user having to specify; • Interface may adapt depending on user models • Step towards response planning
  22. 22. HCI Theories Early theories & Models • GOMS Model • Goals • Operations • Methods • Selection Rules
  23. 23. Theories that span 3 major eras • Theories that view human-computer interaction as information processing; • Theories that view interaction as the initiative of agents pursuing projects; • Theories that view interaction as socially and materially embedded in rich contexts;
  24. 24. Information Processing: methods & models • HIP approach tied to cognitive psychology, human factors, and human engineering; • Empirical studies evaluate the information processing requirements of various tasks in which humans use computers; • Computation models are developed with the intent to characterize human information processing when interacting with computers and to predict human performance with alternative interfaces;
  25. 25. Information Processing Methods • Signal detection methods and theory • Chronometric methods • Speed-accuracy methods • Psychophysiological methods
  26. 26. Information Processing Models • Discrete vs. continuous: • representation; • transformation; • transmission;
  27. 27. Information Processing Stages for choice reaction tasks where each stimulus is assigned to a unique response
  28. 28. Information Processing in Choice-Reaction Tasks • Stimulus Identification: • preprocessing; • feature extraction; • identification; • Response Selection; • Response Execution: • motor programming; • motor adjustment;
  29. 29. Attention Models • The Filter Theory; • The Filter Attenuation Theory; • Load Theory; • Unitary Resource Model; • Multiple Resource Model; • Feature Integration Theory; • Response Selection Bottleneck Theory;
  30. 30. –Jef Raskin “As far as the customer is concerned, the interface is the product.”

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