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AH Example Systems

AH Example Systems. Dr. Alexandra Cristea a.i.cristea@warwick.ac.uk http://www.dcs.warwick.ac.uk/~acristea/. Example Adaptive Hypermedia Systems. • We show examples that are very different: TV Scout: personalized TV guide (GMD Darmstadt)

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AH Example Systems

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  1. AH Example Systems Dr. Alexandra Cristea a.i.cristea@warwick.ac.uk http://www.dcs.warwick.ac.uk/~acristea/

  2. Example Adaptive Hypermedia Systems • We show examples that are very different: • TV Scout: personalized TV guide (GMD Darmstadt) • AIMS: Adaptive Information Management System (TU/e+UT) • SQL-Tutor: Intelligent Tutoring System for SQL (Canterbury, • New Zealand) • ISIS tutor (Moscow State University) • Interbook: Adaptive Electronic Textbooks (Univ. of Pittsburgh) • INTRIGUE: adaptable tourist guide (Univ. of Torino) • HERA • MOT (My Online Teacher) • Adaptation to learning styles in (an extension of) AHA! • The ARIA Photo Agent (MIT) with commonsense reasoning

  3. TV Scout: Personalized TV Guide • A cooperation between GMD-IPSI and • Goal: Help users in creating their personal TV schedule • Short-lived data (not a static database) • Low user effort required to “tune” the system • Filtering based on time and genre, information provided by the stations • Users plan only for one day • TV Scout has a simple and an advanced interface, with possibilities for collaborative filtering.

  4. TV Scout: What’s on Tonight?

  5. TV Scout: Setting Preferences • Preferred genres can be indicated • Deeper genres are more specific • Less general than Boolean combinations

  6. TV Scout: Forms and Graphical Interface

  7. QSA profile editor (experts) viewing time profile editor channelprofile editor QSAprofile editor suggest queries QSAmenu query menus TV Scout user interface with starting page textsearch retentionmenus programdescription table laundry list video labels programdescriptionlist

  8. TV Scout: Evaluation / Feedback • Orientation is easy, but undo is missing • For some users the system is still too complex (opening folders, buttons to small for visually impaired users) • People liked the „grocery list“ (forms interface) • Overall it is useful and easy to use • High fun-factor! • Biggest success indicator is repeat visits by users

  9. AIMS: Task-Based Information Retrieval • Agent-based Information Management System: • concept visualization (using “aquabrowser”) • task-based search (keyword search extended with task information) • user model: keeps track of user’s knowledge and performed tasks • graphical user-interfaces for creating concepts, tasks, courses, etc. • initiated at and evaluated with students from the Universiteit Twente • Note: adaptation to a “moving target”, because the knowledge changes

  10. AIMS Global Information Model • Domain model: defines subject domain by means of a concept map • concepts are linked to each other (“ontology”) • Library model: defines relationship between documents and concepts • how relevant is a document for a given concept • Course model: course topics and tasks • tasks are described using concepts, task description, prerequisites, task status • Learner model: what the user has learned: • course tasks, domain concepts, library documents • overlay model • built jointly by the user and the system

  11. AIMS Student Interface

  12. AIMS Instructor Domain Environment

  13. AIMS Instructor Library Environment

  14. AIMS Instructor Course Environment

  15. AIMS Admin Environment

  16. SQL Tutor • Knowledge-based tutor for the SQL language • based on constraint-based modeling • currently deals only with the SELECT statement • users register with an initial knowledge level • system suggests problems based on the knowledge level (based on which clause select, from, where, group by, having or order by the user needs to practice • system was evaluated to find out whether it was useful and pleasant to use • SQL-Tutor is described (and sometimes accessible) at: • http://www.cosc.canterbury.ac.nz/tanja.mitrovic/sql-tutor.html • Try out:http://ictg.cosc.canterbury.ac.nz:8000/sql-tutor/login

  17. SQL Tutor, Main Window

  18. ISIS-Tutor: adaptive annotation/ hiding • Tutor for CDS/ ISIS library system • CDS/ISIS is a library system for PCs sponsored by UNESCO • ISIS Tutor developed by Peter Brusilovsky and Leonid Pesin • Descendent from an older system ITEM/P (Moscow State Univ.) • Domain and student model for monitoring student knowledge • Tutor component to perform adaptive task sequencing • Hypertext component lets students navigate through course material. • Learning environment lets users interact with ISIS • Versions to determine learning effect of using adaptation • http://www.cs.joensuu.fi/~mtuki/www_clce.270296/Brusilov.html

  19. ISIS Tutor with Link Annotation The wrong example:

  20. ISIS Tutor with Link Removal + Annotation

  21. Evaluation of ISIS Tutor (number of steps)

  22. Evaluation of ISIS Tutor (repetitions)

  23. Relationship between well-known AHS

  24. Interbook • tool for adaptive electronic textbooks (developed mostly at the Carnegie Mellon University): • authoring through Microsoft Word (+conversion tools) • domain model: concepts and prerequisite relationships • user model: overlay model, updated through “outcome concepts” of read pages • adaptive link annotation • several additional tools: index, glossary, “teach me” • a good description of Interbook: • http://ausweb.scu.edu.au/aw97/papers/eklund/paper.htm

  25. Interbook: textbook window

  26. Interbook: Glossary and Concepts

  27. Authoring for Interbook

  28. Interbook: Evaluation • Goal: to find a value of adaptive annotation • Electronic textbook about ClarisWorks • 25 undergraduate teacher education students • 2 groups: with/without adaptive annotation • Format: exploring + testing knowledge • Full action protocol • Results: • Sequential navigation dominates (“continue” button) • Adaptive link annotation encourages non-sequential navigation • Most students follow the “green” links

  29. Intrigue: adaptive tourist guide • Allows for the planning of a trip • stereotype user modeling • allows to plan a trip for a diverse group, for instance parents with children • takes physical disabilities into account, age, interests, etc. • can produce output in html or wml (for mobile phone) • can sometimes be tried at: • http://silk.di.unito.it:8083/ishtar/intrigue.html

  30. Intrigue: recommendation for 2 groups

  31. Intrigue: combined recommendation

  32. MOT (My Online Teacher) • Authoring environment based on the LAOS authoring framework that specifies separation of concerns

  33. MOT (old): Domain Concept attribute creation Try at: http://e-learning.dsp.pub.ro/mot/ concept attribute Current concept

  34. MOT (old): Editing a Goal Map Weights of sublesson Labels of sublesson Ordering of lessons

  35. Evaluation of early MOT (2004) Goal point of view evaluation

  36. USI point of view evaluation

  37. Semantics in MOT • MOT is based on LAOS and on semantic web directives • necessary • more explicit ontologies, • synonyms - to identify semantic overlaps

  38. User Model in MOT • dynamic model of the user's history; • user model variables should be also user writable (flag); • retrieved by prompting the user • Specified where? AM? UM?

  39. Domain concept attribute MOT: Domain attribute creation Try at: http://prolearn.dcs.warwick.ac.uk/MOT/ Current domain concept

  40. MOT: Uploading other files/content

  41. MOT: Goal model authoring Ordering of lessons Weights of sublesson Labels of sublesson

  42. MOT: Goal model authoring Group of Sub- lessons Group alternatives

  43. Evaluation of new MOT (2007) • intensive two-week course AH & SW • 33 out of 61 students selected: 4th year Engineering & 2nd year MsC in CS • theoretical exam half way for selecting students due to space constraints in computer room • at the end: practical exam & 5 questionaires • 3 systems: OLD MOT, NEW MOT & Sesame2MOT

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