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Adaptive Hypertext

Adaptive Hypertext. Outline. What is adaptive hypertext? Why is it necessary? The Adaptation Cycle in Hypertext systems How is Adaptation achieved? Navigation adaptation Presentation adaptation Examples. What is hypertext?.

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Adaptive Hypertext

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  1. Adaptive Hypertext

  2. Outline • What is adaptive hypertext? • Why is it necessary? • The Adaptation Cycle in Hypertext systems • How is Adaptation achieved? • Navigation adaptation • Presentation adaptation • Examples

  3. What is hypertext? • Representation that provides a non-sequential method of representing and accessing information (Nelson, 1987) • hypertext document information is stored as a network of nodes connected by hypertext links which allow: • Jump to another part of the document • Jump to another document • Hypermedia – integrates elements of multimedia (animation, images, video, & sound)

  4. Problems with Hypertext • Non-sequential & User-driven access provides powerful flexibility • Easy to get off course and end up with irrelevant information. Leads to: • User Disorientation (Lost in Hyperspace) • Information Overload

  5. User Disorientation (Elm & Woods, 1997) • User not knowing where to go next • Users knowing where to go but not knowing how to go there • Users not knowing where they are within the overall structure

  6. Information Overload • Occurs when user is swamped with details that may not be relevant to current needs • Information is provided in a unstructured manner • Navigational support tools • Punctual Tools – labelled buttons (previous, next, home, last), curser hover descriptions, etc. • Structural Navigation Tools – guided tours, overview maps & fisheye views. • Historical Tools – access hypertext nodes that have already been visited (bookmarks & history lists)

  7. What is adaptive hypertext? • Aims to provide support to users by tailoring the system and augmenting the delivery of information • Can filter out undesirable details outside a users current field of interest or beyond their level of comprehension • Controls the size of the hyperspace

  8. Adaptive Hypertext • Basic premise • Not all users have the same goals or abilities • User may • Be experts looking for specific information • Have more general requirements • Be novices trying to find basic information • User characteristics • User requirement • Interaction style • Background knowledge • Cognitive characteristics

  9. Adaptive Hypertext Solutions • Novice Users • Specialized or simplified presentation of information • Expert Users • Enhancing navigation

  10. How? • ITSs (Intelligent Tutoring Systems) • Goal is to tailor hypertext systems to the needs of a student. • To do this, we require understanding of the student's specific information requirements. • An ideal tutoring system would present learning material to a student at a level that matches their abilities and will adapt as the student’s knowledge develops.

  11. Adaptation Cycle • Data Elicitation • Initial interviews • Questions and Answer Analysis • User Relevance feedback • Storing user browser patterns • Data Analysis • Build/Maintain User Model i.e. Personis • Adaptation

  12. How is Adaptation achieved? • Two components of hypertext can be adapted • Hyperlinks • Information contained in nodes • Navigation • Presentation

  13. Presentation Adaptation • Adapt information presented to the user by hiding details not of current interest • Techniques • Conditional text • Stretch text • Page variants • Fragment variants • Frame-based

  14. Conditional Text • A concept is divided into chunks of text • Each chunk is associated with a user type

  15. Stretch Text • To give additional explanation to the current topic without need to retrieve a new page

  16. Page Variants • Two or more variants of the same page on a concept

  17. Fragment Variants • More fine grain then page variants • Page segmented with variants of different fragments Muha haha haha haha

  18. Frame-based • Similar to fragment variant, with the addition of the ability to be able to link to other frames from a slot Muha Haha haha haha Muha Haha haha

  19. Navigation Adaptation • Assist user by manipulating the navigational aids (links, labels, hot words) within the system suggesting appropriate directions to take • Can overcome user disorientation • Techniques • Annotation • Ordering / Link Sorting • Direct Guidance • Hiding • Mapping

  20. 1. Annotation • Links are enriched with extra comments or visual cues • History-based annotation • what has been seen or what remains to be explored • Knowledge-based annotation • Take into account the users progress • Prerequisite-based annotation • Educational prerequisites

  21. 1. Annotation : Knowledge-based Annotation • MANUEL EXCEL – learning of databases in Excel spreadsheet • users left to explore goals, sub goals, and procedures through explanations, examples, exercises and tests • Denotes links as not-known, in-work, and well-learned • In-work reduces ambiguity by signify that the user is simply just browsing the page Brigitte de La Passardiere, Aude Dufresne: Adaptive Navigational Tools for Educational Hypermedia. ICCAL 1992: 555-567

  22. 1. Annotation : Prerequisite-based Annotation • Determines the educational pre-requisites of each hypertext page, based on the knowledge level of the user • Example: ELM-ART

  23. Prerequisite-based annotation: ELM-ART • is a WWW-based ITS to support learning programming in Lisp. • an on-line intelligent textbook with an integrated problem solving environment • It provides all the course materials (presentations of new concepts, test, examples, and problems) in hypermedia form. • ELM-ART "knows" the material it presents to the students and supports them in learning and navigating the course material.

  24. The metaphor is traffic lights Red (italic typeface) means not ready to be learned Green (bold) means ready and recommended Yellow means ready but not recommended. Prerequisite-based annotation: ELM-ART

  25. 2. Ordering / Link Sorting • Sorts and re-orders the links on a specific page according to a user model • MLTutor – uses machine learning techniques in order to model user’s interests from their browsing behavior • No prior knowledge regarding the user’s background or interest

  26. MLTUTOR 1 . Clustering phase 2 . Learning Phase

  27. MLTUTOR

  28. 3. Direct Guidance • The system indicates to the user the best node to visit next • WebWatcher - WebWatcher is a "tour guide" agent for the world wide web. Once you tell it what kind of information you seek, it accompanies you from page to page as you browse the web, highlighting hyperlinks that it believes will be of interest. Its strategy for giving advice is learned from feedback from earlier tours.

  29. WebWatcher Clicks WebWatcher Types in a interest

  30. WebWatcher

  31. WebWatcher

  32. WebWatcher

  33. 4. Hiding • Controls access to information by hiding or disabling links to pages, which are irrelevant to the user’s requirements • Reduces possibility of cognitive overload by controlling the navigable hyperspace • Allows for gradual exposure of hyperspace hence effective for educational hypermedia systems • Example: PUSH & Sassy (Unix Security)

  34. PUSH • The PUSH project investigates ways of utilizing adaptive hypermedia to aid users of an on-line manual. The system hides parts of a page from the user's immediate view in order to reduce the information overflow problem. The adaptation is based on inferring the users information seeking task from their interactions with the system.

  35. supports the collection, filtering and browsing of calls for papers and calls for attendance for conferences and workshops. To avoid uninteresting calls, the user sets up a user profile to retrieve a personal selection of calls and organize them in a personal manner PUSH - ConCall

  36. Persona - Soundscapes • Still under research • Sound has so far not been considered as a very important issue in the design of interfaces. All the focus has been on the visual channel, emphasizing foremost written text • Sound is a information carrier itself • 3D sound allows for better discrimination between sound sources and may allow us to design richer information spaces. • In the real world, we have layers of sounds, coming from different locations in the room. Some of them we attend to, others are just background noise that we cannot hear unless something unexpected happens. How can we imitate "natural" sounds in an efficient way?

  37. 5. Mapping • A map allows a user to understand the overall structure of the hyperspace and also to locate themselves within it • Example: HYPERCASE

  38. Comparison

  39. Concluding thoughts • Obvious applications • Online help systems • Document Repositories • Tutoring systems

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