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Title: Foundations of Adaptive Hypermedia


1
  • Foundations of Adaptive Hypermedia
  • Heiko Spallek, DMD, PhD
  • Center for Dental Informatics
  • University of Pittsburgh, School of Dental
    Medicine, Pittsburgh, PA
  • March 30, 2005
  • Dental Informatics Seminar (2202)

2
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3
  • Agenda
  • Background
  • e-learning hype
  • reality check
  • current status of dental online courses
  • Adaptive Hypermedia
  • definitions, concepts
  • usage in education, information retrieval, kiosk
    help systems
  • Conceptual architecture
  • Technical implementation
  • In-class assignment
  • Evaluation
  • Conclusions

4
  • Hype About E-learning
  • General
  • number of online courses 50,000 ? 100,000
    between 1998 and 1999
  • online learning market 2.2 billion in 2001,
    estimated 11.4 billion by 2003
  • e-learning conference in Europe attracted 10,000
    attendees last year
  • Dentistry
  • 1998 158 online continuing dental education
    (CDE) courses from 32 providers
  • 2001 just DentalxChange.com 428 courses in 27
    different categories
  • International Data Corp.

5
  • Reality check
  • E-learning is the revenge of the nerds.
  • evaluation of 158 online continuing dental
    education
  • uncovered major deficiencies in existing
    Web-based CDE courses
  • no author indicated
  • relation between course length and credit hours
    varies
  • market for course shells immature
  • no standards ? risk of losing content
  • no peer-review process for online learning
    resources ? no academic credit
  • usually no formative or summative evaluation
  • high drop-out rate (based on meta analysis of
    multiple studies)
  • in dentistry/medicine no one has reported
    profits yet (break even for online course
    300-500 participants)
  • Schleyer T, Pham T. Online continuing dental
    education. Journal of the American Dental
    Association 1999130(June)848-854,877-878

6
  • Evaluation of Web-based CDE courses
  • evaluate the outcomes of online CDE courses at
    six organizations analysis
  • focused on
  • how the participants of online CDE can be
    characterized
  • whether the participants' expectations were met
    by the courses
  • how the participants evaluate the content of the
    courses
  • why they enrolled
  • how they experienced the online environment
  • ? develop recommendations for the design of
    future courses

7
  • Results regarding online environment
  • Single most important reason that attracted them
    to an online course
  • 47 answered "convenience"
  • Biggest disadvantage to the online format?
  • "lack of human interaction" -- 13 of respondents
  • "cannot ask questions" -- 12 of respondents
  • Lack of face-to-face contact with a teacher
    stumbling block for their learning
  • 18 agreed
  • 65 disagreed
  • 17 neither agreed nor disagreed

8
  • Current state-of-the-art dental online course
  • collection of static Web pages
  • translations of existing lecture notes
  • existing course manuals
  • existing papers
  • first generation online course model
  • Course material is still implicitly oriented for
    a traditional on-campus audience!

9
  • Generations of online courses
  • 1. Generation
  • static pages
  • 2. Generation
  • adapted by the instructor to different audiences
    (static versions of the same course saved at
    different locations)
  • 3. Generation
  • adaptive to the individual learner

10
  • Adaptive Hypermedia (AH)
  • new direction of research
  • crossroads of hypermedia and user modeling
  • model of the goals, preferences, knowledge of
    each individual user
  • use of model throughout interaction with user
  • adapt to the needs of user
  • Brusilovsky 1996, Brusilovsky 2001

11
  • Definition User Model
  • - mental state of the user
  • AH system keeps a model of the user
  • to adapt teaching sequence, presentation
  • for each Knowledge Item (KI)
  • individual user model
  • stores some value
  • estimation of the users knowledge level of this
    concept
  • De Bra and Calvi 1998
  • Brusilovsky 1996

12
  • AH ? Areas of Application
  • educational hypermedia
  • online information systems
  • online help systems
  • information retrieval hypermedia
  • institutional hypermedia
  • systems for managing personalized views in
    information spaces
  • Brusilovsky, P. (2001) Adaptive hypermedia. User
    Modeling and User Adapted Interaction, Ten Year
    Anniversary Issue (Alfred Kobsa, ed.) 11 (1/2),
    87-110

13
Taxonomy of AH Technologies
Adaptive presentation
  • Adaptive
  • hypermedia
  • technologies

Adaptive navigation support
The updated taxonomy of adaptive hypermedia
technologies Brusilovsky, P. (2001) Adaptive
hypermedia. User Modeling and User Adapted
Interaction, Ten Year Anniversary Issue (Alfred
Kobsa, ed.) 11 (1/2), 87-110
14
  • Curriculum Sequencing
  • active
  • implies a learning goal
  • best individual path to achieve the goal
  • passive
  • reactive technology
  • offers the user a subset of available learning
    material ? fill the gap in student's knowledge

15
  • AH Technologies in Web-based Education
  • adaptive navigation support technology
  • - changing the appearance of visible links
  • generalization of curriculum sequencing
    technology in a hypermedia context
  • - direct guidance, adaptive link annotation,
    adaptive link hiding
  • adaptive presentation technology
  • - adapt the content of a Web page to the user's
    goals, knowledge and other information stored in
    the user model
  • - pages are adaptively generated or assembled
    from pieces for each user

16
  • Conceptual architecture
  • What features of the learner can be used as a
    source of the adaptation?
  • What can be adapted in a technical feasible
    manner?

17
  • 1. What features of the learner can be used as a
    source of the adaptation?
  • users knowledge- pre-test results- completion
    of quizzes throughout the course
  • users interests/goals- selection of a specific
    learning goal
  • users traits- learning style

18
  • 2. What can be adapted in a technical feasible
    manner?
  • users learning goal ? compilation of KIs
  • ? individual curriculum (active sequencing)
  • systems estimation of the learners knowledge
    level of each KI stored
  • modifies content (adaptive presentation)

19
  • Adaptiveness
  • adaptive text presentation
  • inserting/removing of fragments
  • altering fragments
  • stretch text
  • adaptive navigation support
  • adaptive links hiding
  • adaptive link annotation
  • sitemap adaptation
  • admission to final quiz only after mastering of
    all offered KIs
  • forced repetition of KI
  • example-based learning versus concept-based
    learning

20
Demographic Information
AccessRights
PrivacyInformation
LearningGoal
Knowledge Assessment
Learning Style
AH system stores information
User
AH system compiles KIs
AH system compiles pre-test
Estimation of users knowledge
AH system adjusts KIs
AH system compiles curriculum
AH system adjusts user model
AH system compiles final
AH system evaluates final
provides enrollment information
performes pre-test
provides traits
User Model
User Info
Course Info
Estimation of users knowledge
L
Eligibility for Final Test
Demographic
Learning style
O
J
D
A
G
B
E
Access
Test history
H
T
G
H
E
J
Privacy
A
Final test
B
O
A
G
B
D
E
H
O
J
L
T
T
Learning Goal ? Knowledge Items
Test results
used for adaptation effect
Test results are used for revising the user model.
Final test
21
  • Technical Implementation
  • Learner Environment

Authoring Tool
22
  • Authoring Tools
  • general course setting
  • views of KIs
  • abbreviated version of the core explanation
    (short)
  • for novice users (basic)
  • very detailed high-level textual explanation
    (main)
  • for graduate level knowledge (advanced)
  • multiple-choice questions
  • fill-in-the-blank questions
  • descriptive / online examples
  • prerequisites KI
  • metadata keywords, semantic
  • Teaching Tools
  • student registration, performance, question
    analysis

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26
  • Learner Environment
  • General design approach follows Mark Weisers
    idea
  • The most profound technologies are those that
    disappear. They weave themselves into the fabric
    of everyday life until they are indistinguishable
    from it.
  • Scientific American, 265(3)94--104, September
    1991

27
  • Learner Environment
  • Overview page
  • background about the subject of the course
  • explanation about the concept of AH
  • introduction to personal tutor
  • acknowledgements

28
  • Learner Environment
  • Emotional Intelligence?
  • show emotional behavior (e.g. the persona-effect,
    help relieve frustration, recover to a positive
    emotional state)
  • ? beneficial for tutoring agents and learning
    software
  • C Elliot, J.C. Lester, J. Rickel. Integrating
    affective computing into animated tutoring agents
  • In Proceedings of the IJCAI Workshop on Animated
    Interface Agents
  • Nagoya, Japan, 1997, 113121
  • ? improve user acceptance
  • J. Klein. Computer Response to User Frustration.
    TR480, MIT, 1998

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33
  • Learner Environment
  • user model is dynamic and is continuously revised
  • not based on the content reviewed
  • Beaumont 1994
  • Boyle and Encarnacion 1994
  • Vassileva 1996
  • Henze et al. 2002

34
LearningGoal
User
AH system re-compiles curriculum
User Model
User Info
Course Info
Estimation of users knowledge
L
Demographic
Learning style
D
Access
Test history
G
H
J
E
Privacy
A
B
O
A
U
F
K
R
S
T
M
Learning Goal ? Recompile Knowledge Items
New curriculum
User changes learning goal.
35
  • Annotations
  • feedback is encouraged
  • annotations informal continuous formative
    evaluation
  • ? all KIs are annotatable by learners
  • Henze et al. 2002

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37
  • Design
  • cross platform, all browsers
  • screen resolutions with a minimum of 800x600
    pixel
  • Guidelines of the Design of Educational Software
  • ANSI Standards Committee on Dental Informatics

38
  • Technology

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40
  • PHP Scripting
  • // check what is up with prerequisites
  • if(prereq!"disregard")
  • queryPrereq "select Requires from
    AH_Prerequisites where KI'KIID'"
  • dbPrereq-query(queryPrereq)
  • if(dbPrereq-num_rows())
  • querygetKI "select AH_Knowledge_Items.KI_tit
    le, AH_Knowledge_Items.KIID from
    AH_Prerequisites, AH_Knowledge_Items where
    AH_Prerequisites.KI'KIID' and
    AH_Prerequisites.RequiresAH_Knowledge_Items.KIID"
  • dbgetKI-query(querygetKI)
  • KItitlewithlink""
  • while(dbgetKI-next_record())
  • vKI_title dbgetKI-Record"KI_title"
  • vKIID dbgetKI-Record"KIID"
  • scoregetscore(vKIID, UserID)

41
  • Evaluation
  • initial review (cognitive walkthroughs )
  • alpha-test (task-oriented)
  • formative evaluation (heuristic evaluation
    end-user testing)
  • summative evaluation (end-user testing) planned

42
  • Cognitive Walkthroughs
  • Goal solve anticipated problems before bringing
    the course to users for testing
  • - performed independent and under observation of
    the developer
  • Results (encountered problems were fixed
    immediately )
  • - confusing labels of fields
  • - confusing options during enrollment
  • - missing guidance on start page
  • - repetition of test questions
  • - inadequate feedback for wrong answers

43
  • Alpha Test
  • task-oriented alpha test
  • complete the course
  • determine deficiencies (educational,
    instructional design, technical, design and
    layout)
  • send an unstructured informal feedback
  • Results (encountered problems were fixed
    immediately )
  • - general feedback was positive
  • - personal tutor concept was beneficial
  • - 12 specific usability, functionality issues
    were discovered (regarding change of setting,
    annotations, quiz, flow, sequencing)

44
  • Formative Evaluation I
  • Usability Inspection Heuristic Evaluation
  • general heuristic for UI design (Jakob Nielsen)
  • heuristic extracted from ANSI standard
    Guidelines for the Design of Education
    Software http//di.dental.pitt.edu/edswstd/

45
  • In-Class Assignment
  • Evaluate the pre- and post-questionnaires
  • Problems/Critique
  • Order of questions
  • Comparing terms
  • Formatting
  • Disclaimer

46
  • Formative Evaluation II
  • End-user testing
  • separation between delivery (media) and
    instructional method
  • use of a validated instrument
  • ? Evaluation of
  • participants reactions
  • achievement of program objectives
  • changes in student learning
  • values
  • motivations
  • ability to transfer knowledge acquired outside
    the instructional setting

47
  • Conclusions
  • applying of established principles of AH research
  • state-of-the-art programming environment
  • separation of content and design
  • Web-based delivery system
  • For the first time, a dental educational delivery
    system adapts itself dynamically using active and
    passive curriculum sequencing and adaptive
    presentation.
  • authoring process challenge
  • Brusilovsky, Eklund, and Schwartz 2002
  • De Bra and Calvi 1998
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