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Authoring of Adaptive Hypermedia UPB Romania Course 2

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Title: Authoring of Adaptive Hypermedia UPB Romania Course 2


1
Authoring of Adaptive Hypermedia UPB
RomaniaCourse 2
  • Dr. Alexandra Cristea
  • a.i.cristea_at_tue.nl
  • http//wwwis.win.tue.nl/alex/


2
Learning styles AH
  • ARTHUR, iWeaver, MANIC, CS388 sensory
    preferences
  • AEC-ES field-dependent (FD) independent (FI)
  • LSAS, CS388 global-sequential (Felder-Silverman)
  • Tangow sensing-intuitive dimension
    (Felder-Silverman)
  • INSPIRE Honey and Mumford model
  • etc..

3
Learning styles AH
  • ARTHUR, iWeaver, MANIC, CS388 sensory
    preferences
  • AEC-ES field-dependent (FD) independent (FI)
  • LSAS, CS388 global-sequential (Felder-Silverman)
  • Tangow sensing-intuitive dimension
    (Felder-Silverman)
  • INSPIRE Honey and Mumford model
  • etc..

4
Sensory preferences treatment
  • Adaptive presentations can switch between the
    following styles
  • textual (hyper-text)
  • visual (image, diagrams, graphs, video,
    slideshows)
  • auditory (sounds, streaming audio)
  • kinaesthetic views (animations, simulations,
    puzzles)

5
Dunn Dunn model
6
Sensory preferences in AH
  • CS388 (1996)
  • Felder-Silverman learning styles model
    global-sequential, visual-verbal,
    sensing-intuitive, inductive-deductive styles
  • ARTHUR (1999)
  • visual-interactive, auditory-lecture and text
    styles
  • MANIC (2000)
  • uses a Naïve Bayes Classifier to reason about the
    learners preferences in terms of explanations,
    examples and graphics
  • iWeaver (2002)
  • Dunn Dunn model the application of a Bayesian
    network is planned to predict and recommend media
    representations to the learner.

7
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9
Auditory Interface, iWeaver
10
Visual Interface, iWeaver
11
Learning styles AH
  • ARTHUR, iWeaver, MANIC, CS388 sensory
    preferences
  • AEC-ES field-dependent (FD) independent (FI)
  • LSAS, CS388 global-sequential (Felder-Silverman)
  • Tangow sensing-intuitive dimension
    (Felder-Silverman)
  • INSPIRE Honey and Mumford model
  • etc..

12
FD vs. FI treatment
  • FD learners prefer
  • structures,
  • social content,
  • material relevant to own experience.
  • AH systems respond by
  • providing navigational support tools (CM, path
    indicator, advanced organizer) adaptive
    navigation support

13
FD vs. FI treatment
  • FI learners
  • perceive analytically,
  • make concept distinctions,
  • prefer impersonal orientation.
  • AH systems respond with
  • learner control arbitrary succession of course
    material.
  • Sometimes explicit switching between FI FD.

14
  • AES-CS (2000)
  • Adaptive Educational System base on cognitive
    styles
  • http//www.vrc.gr/browse_en/ShowProduct.aspx?id44

15
Learning styles AH
  • ARTHUR, iWeaver, MANIC, CS388 sensory
    preferences
  • AEC-ES field-dependent (FD) independent (FI)
  • LSAS, CS388 global-sequential (Felder-Silverman)
  • Tangow sensing-intuitive dimension
    (Felder-Silverman)
  • INSPIRE Honey and Mumford model
  • etc..

16
  • CS388 (1996)
  • LSAS
  • Global or sequential learning style
  • http//www.archives.ecs.soton.ac.uk/users/nb99r/in
    tro_short/frame.htm

17
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18
Felder-Silverman
  • 44 questions at
  • http//www.engr.ncsu.edu/learningstyles/ilsweb.htm
    l
  • Index of Learning Styles (1991)
  • Richard M. Felder, a chemical engineering
    professor at North Carolina State University,
  • Barbara A. Soloman, then the coordinator of
    advising for the N.C. State First-Year College.
  • The four learning style dimensions of the
    instrument were adapted from a model developed in
    1987 by Dr. Felder and Linda K. Silverman, an
    educational psychologist then at the University
    of Denver.

19
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20
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21
Learning styles AH
  • ARTHUR, iWeaver, MANIC, CS388 sensory
    preferences
  • AEC-ES field-dependent (FD) independent (FI)
  • LSAS, CS388 global-sequential (Felder-Silverman)
  • Tangow sensing-intuitive dimension
    (Felder-Silverman)
  • INSPIRE Honey and Mumford model
  • etc..

22
Learning styles AH
  • ARTHUR, iWeaver, MANIC, CS388 sensory
    preferences
  • AEC-ES field-dependent (FD) independent (FI)
  • LSAS, CS388 global-sequential (Felder-Silverman)
  • Tangow sensing-intuitive dimension
    (Felder-Silverman)
  • INSPIRE Honey and Mumford model
  • etc..

23
Learning styles AH
  • ARTHUR, iWeaver, MANIC, CS388 sensory
    preferences
  • AEC-ES field-dependent (FD) independent (FI)
  • LSAS, CS388 global-sequential (Felder-Silverman)
  • Tangow sensing-intuitive dimension
    (Felder-Silverman)
  • INSPIRE Honey and Mumford model
  • etc..

24
Selected ModelHoney and Mumford model
Activist I like to have a go and see what happens
Pragmatists I like tried and tested techniques
that are relevant to my problems
Theorist I like to tidy up and reach some
conclusions
Reflector I like to gather information and mull
things over
25
Presentation of MOT user guide to verbalizer
26
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27
Presentation of MOT user guide to imager
28
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29
MOT
  • pronounced moh like the French word for word
  • My Online Teacher
  • Site http//wwwis.win.tue.nl/acristea/mot.html

30
Papers on MOT
  • implementation papers
  • first (educational) MOT paper (ITCC'03)
  • http//wwwis.win.tue.nl/acristea/HTML/Minerva/pap
    ers/ITCC03-cristea-mooij.doc
  • MOT automatic linking paper (ITC'03)
  • http//wwwis.win.tue.nl/acristea/HTML/Minerva/pap
    ers/ITC03-cristea-mooij.doc
  • MOT evaluation papers
  • URD evaluation (CATE'03)
  • http//wwwis.win.tue.nl/acristea/HTML/Minerva/pap
    ers/CATE-cristea-mooij.doc
  • Student evaluations (SAC04, ATL journal 04)
  • http//wwwis.win.tue.nl/acristea/HTML/Minerva/pap
    ers/CristeaSAC04CameraReadyLast2give.doc
  • http//www.actapress.com/onlinejournals/208vol1,2
    02004/issue_2/208-0805.pdf

31
MOT Download site
  • http//wwwis.win.tue.nl/acristea/HTML/USI/MOT/

32
LAOS
  • based on AHAM
  • supporting adaptive hypermedia authoring
  • five layers
  • Domain Model (DM)
  • Goal and constraints Model (GM)
  • User Model (UM)
  • Adaptation Model (AM)
  • Presentation Model (PM)

33
Creation of the LAOS Domain Model
  • Domain Model in MOT is represented by a list of
    Domain Maps, called Concept maps

34
Conceptmaps in MOT
  • each concept map corresponds roughly to a book
    as is required by the LAOS model
  • these books should describe different topics
  • however, just as in reality, different books may
    treat a similar topic

Please note that the current conversion system
does not deal with this
35
Steps to MOT system usage
  • Try-out steps
  • http//wwwis.win.tue.nl/acristea/HTML/USI/MOT/hel
    p/steps2MOTsystemUsage.txt
  • http//e-learning.dsp.pub.ro/mot/
  • MOT user guide
  • MOT generalities installation

36
author username
Domain maps
the authors own maps
other authors maps
37
MOT Conceptmap
  • Consists of a hierarchy of concepts and their
    attributes

38
Conceptmap name
Concept hierarchy
Current concept
attributes of the current concept
39
Concept attributes in the Conceptmap
  • Should contain ONLY domain-related content
  • So no prerequisites, no pedagogic information

40
Concept attribute creation
concept attribute
Current concept
41
Editing an attribute
  • text input window in the left hand panel
  • cut paste any type of text you wish,
  • including HTML/ XML !!
  • Condition you are the author of this conceptmap.

42
Adding children concepts
Adding more attributes
Adding Relatedness relations
43
LAOS
  • based on AHAM
  • supporting adaptive hypermedia authoring
  • five layers
  • Domain Model (DM)
  • Goal and constraints Model (GM)
  • User Model (UM)
  • Adaptation Model (AM)
  • Presentation Model (PM)

44
Creation of the LAOS Goal and Constraints Model
  • Goal and Constraints Model in MOT is represented
    by a list of Lesson Maps, called Lessons

45
Lessons in MOT
  • Lessons are filtered versions of the (domain)
    Conceptmaps
  • they actually represent an overlay model with
    pedagogic information
  • Lessons contain prerequisites
  • Lesson contain ordering
  • Lessons contain labels their respective weights

46
Lessons by the current author
Lessons by other authors
47
Weights of sublesson
Labels of sublesson
Ordering of lessons
48
Group alternatives
Group of Sub- lessons
49
Changing sub-lesson order
50
Changing weights labels for sublessons
51
Note
  • The meaning of the weights labels is fixed in
    the application you will use, and is as follows
  • 0 everybody will see contents marked with it
  • 35 visual learners
  • 50 mixed learners
  • 75 verbal learners

52
MOT terms glossary
  • http//wwwis.win.tue.nl/acristea/HTML/USI/MOT/hel
    p/MOTterms-glossary.txt

53
MOT Glossary extract
  • adaptation assembly language this language is
    the basis of adaptive hypermedia adaptation. It
    consists of IT-THEN constructs.
  • adaptation strategy adaptation strategies are
    equivalent to small programs telling the
    inference engine how to adapt to the student's
    needs. These strategies are written in MOT-ADAPT,
    in a special language developed, called
    adaptation language, or in adaptation assembly
    language. See adaptation language and adaptation
    assembly language.
  • adaptation language the adaptation language is a
    language for creating adaptation strategies. It
    borrows some language constructs from other
    programming languages, but also offers some
    structure dependent constructs, that use the MOT
    concept domain hierarchy. See also, for the
    actual programming constructs and grammar, the
    document LAGgrammar.doc

54
MOT Glossary extract
  • adaptation map all the information about the
    actual dynamics of the system is contained in the
    adaptation map. In MOT, the adaptation map is
    represented by an instantiated adaptation
    strategy.
  • adaptation model the adaptation model in MOT is
    based on the LAOS model. This model is also
    called the LAG model. The adaptation model is
    instantiated in the adaptation map. The
    instantiation takes place by creating adaptation
    strategies with the help of adaptation language.
  • AM same as adaptation map.

55
MOT Glossary extract
  • concept a concept in MOT is built of a
    collection of attributes. A concept can have
    sub-concepts, if it is part of a hierarchy
    (hierarchical relation). A concept can belong to
    a domain model, a lesson model, a user model and
    a presentation model. A concept is instantiated
    in a concept instance.
  • Conceptmap This is a historical name for the
    domain map. See domain map.
  • concept map All the information in MOT is
    structured in concept maps. These are graph
    instances with nodes and links between them. Most
    links in MOT are directional. The most frequently
    used link type in concept maps in MOT is the
    hierarchical link type. See also Concept,
    Conceptmap.

56
MOT Glossary extract
  • domain concept map same as domain map.
  • domain map The domain map is a concept map
    containing all the nodes, links and structures
    that correspond to the domain model. It is an
    instantiation of the domain model. Moreover, the
    domain map in MOT also links to the actual
    resources of the course.
  • domain model the domain model in MOT is based on
    the LAOS model. The domain model in MOT is
    instantiated in the domain map. See also
    DefinitionsLAOS.doc for the same item.

57
MOT Glossary extract
  • GM same as goal and constraints map.
  • goal and constraints model the LAOS goal and
    constraints model is represented in MOT by the
    lesson model, and instantiated in the lesson
    maps. See also DefinitionsLAOS.doc for the same
    item.

58
MOT Glossary extract
  • LAG model this is the 3-layered model of
    adaptation in LAOS. It is built of adaptation
    strategies, adaptation language and adaptation
    assembly language.
  • LAOS model the LAOS model is the theoretical
    framework of the MOT system. MOT doesn't
    implement at present the whole LAOS model. See
    also DefinitionsLAOS.doc for the same item.

59
MOT Glossary extract
  • lesson same as lesson map.
  • lesson map the lesson map is an instantiation of
    the lesson model. The lesson map in MOT is a
    concept map containing all the nodes, attributes,
    links and structures that correspond to the
    pedagogical model. If the aim is not at
    education, than it contains goal related
    information and linking. Relations such as
    prerequisites appear in the lesson map. The
    lesson map will in future contain also attributes
    allowing narrative smoothing.
  • lesson model the lesson model is a goal and
    constraints model for educational purposes. It
    can, however, be streched for extended usage. LM
    same as lesson map.

60
MOT Glossary extract
  • MOTadapt same as MOT-ADAPT.
  • MOT-ADAPT This is actually a part of MOT, but it
    was developed later, and therefore has a
    different name for distinction. It refers only to
    the authoring of the adaptive strategies, based
    on adaptation language and adaptation assembly
    language.
  • MOT My Online Teacher, pronounced "moh" like the
    French word for "word". It is an Authoring System
    for (Educational) Adaptive Hypermedia. It is
    built in Perl and works with MySQL databases.
    pedagogic strategy this is an adaptation
    strategy with pedagogical purpose. See also
    adaptation strategy.

61
MOT Glossary extract
  • presentation map the presentation map is an
    instantiation of the presentation model. The
    presentation map contains all the nodes,
    attributes, links and structures populated with
    the information that corresponds to the
    presentation on the screen. Attributes about the
    color of the background or forground, booleans
    about if something is presented or not, display
    dependent attributes are all in this map. MOT's
    presentation map will soon be available. At the
    moment, MOT features only two types of
    presentations teacher view and student view.
  • presentation model this model is based on the
    LAOS model. See also DefinitionsLAOS.doc for the
    same item.

62
MOT Glossary extract
  • UM same as user map.
  • user map the user map is an instantiation of the
    user model. The presentation map contains all the
    nodes, attributes, links and structures populated
    with the information that corresponds to the
    user. Such information can be user knowledge,
    preferences, learning style, but also access of
    different concepts in the domain maps or lesson
    maps, etc. This feature is not present in the
    current version of MOT.
  • user model this model is based on the LAOS
    model. See also DefinitionsLAOS.doc for the same
    item.
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