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Authoring of Adaptive (and Adaptable) Educational Hypermedia A 3 EH Course ; day2 part2/2. Dr. Alexandra Cristea [email protected] http://wwwis.win.tue.nl/~alex/. Outline Theory. Adaptive Hypermedia of the Past, Present and Future Example systems and applications

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Authoring of adaptive and adaptable educational hypermedia a 3 eh course day2 part2 2 l.jpg

Authoring of Adaptive (and Adaptable) Educational Hypermedia A3EH Course ; day2 part2/2

Dr. Alexandra Cristea

[email protected]

http://wwwis.win.tue.nl/~alex/


Outline theory l.jpg
Outline Theory

  • Adaptive Hypermedia of the Past, Present and Future

  • Example systems and applications

  • Authoring for Adaptive Hypermedia

  • AH Authoring reference architecture: LAOS

  • A closer look on adaptation design: LAG

  • Learning Styles in Adaptive Hypermedia

  • Conclusions


Authoring ahs l.jpg
Authoring AHS

  • content alternatives,

  • model population

  • adaptation mechanism & whole

  • user-system interaction mechanism design


Content alternatives attributes ex l.jpg
Content alternatives (attributes) ex.

Title: Adaptive Hypermedia

Introduction: Adaptive Hypermedia deals with personalization and adaptation in hypertext and hypermedia.

Concept

Keywords: adaptive; hypermedia; hypertext; personalization

Introduction: Adaptive Hypermedia deals with personalization and adaptation in hypertext and hypermedia.

Text: Adaptive Hypermedia is a special type of hypermedia that customizes the information that each user receives. Based on an interpretation of the user’s current needs, interests, goals, knowledge, etc., adaptive hypermedia systems provide the users with information ...


User model population initialization ex l.jpg
User model population (initialization) ex.

overlay

free

Concept1

Knowledge: 0

Learning style: unknown

Interest: 50

Age group: 10 years

Concept2

Knowledge: 10

Concept3

Knowledge: 20


Presentation model population initialization ex l.jpg
Presentation model population (initialization) ex.

overlay

free

Concept1

Color char: Red

Screen resolution: 1024x768 pixels

Page no.: 3

Min char size: 10 points

Concept2

Color char: Blue

Connection: 56kbps modem

Concept3

Color char: Black


Adaptation techniques ex l.jpg
Adaptation techniques ex.

Concept1

prerequisite

Concept3

Concept2

prerequisite










Some authoring perspectives l.jpg
(some) Authoring perspectives

  • Conceptual view: defining concepts, interrelationships and resources.

  • Navigational (goal) view: defining navigation behavior.

  • Presentation view: defining presentation aspect like frame, frameset, and window and pages content .


Authoring ahs17 l.jpg
Authoring AHS

  • content alternatives, adaptation mechanism & whole user-interaction mechanism design

  • complicated heavy task => help, guidelines & automation facilities needed

  • for AHS to spread widely => facilitate author work

    (Open Learning Repositories)


Slide18 l.jpg

“Authoring problem” Defining:- content alternatives & multiple paths through the content - adaptation techniques - whole user-interaction mechanism design

Alleviating “Authoring problem”Improving reuse capabilities:(reuse of previously created material & other components)- reuse of static & dynamic parts of the courseware

Our solutionReuse of static materials:LAOS (learning repositories) ; implementation: MOTReuse of dynamics:“Exchanging not only the ingredients, but the recipes as well”Adaptation languages:-LAGimplementation: MOT- LAG-XLS (read as “LAG-excels”)


Authoring standardization l.jpg
Authoring & standardization

  • Formalization attempts:

    • standardizingthe whole procedure

  • Research on a systematic base

    • clear explicit models for adaptive authoring


Outline l.jpg
Outline

  • Adaptive Hypermedia of the Past, Present and Future

  • Example systems and applications

  • AH Reference architectures: AHAM

  • Authoring for Adaptive Hypermedia

  • AH Authoring reference architecture: LAOS

  • A closer look on adaptation design: LAG

  • Learning Styles in Adaptive Hypermedia

  • Authoring system: MOT

  • Delivery System: AHA!

  • Conclusions


Slide21 l.jpg
LAOS

  • What is LAOS?

  • Concept based adaptation

  • LAOS components

  • Why LAOS?

  • LAOS authoring steps

  • Future directions



What is laos23 l.jpg
What is LAOS ?

  • a generalized model for generic adaptive hypermedia authoring

  • based on the AHAM model

  • based on concept maps

  • http://wwwis.win.tue.nl/~alex/HTML/Minerva/papers/WWW03-cristea-mooij.doc

  • http://www.ifets.info/journals/7_4/7.pdf



General motivation for layer distributed information l.jpg
General motivation for layer distributed information

  • Flexibility

  • Expressivity (semantics: also meta-data)

  • Reusability

  • Non-redundancy

  • Cooperation

  • Inter-operability

  • Standardization



Laos components27 l.jpg
LAOS components

  • domain model (DM),

  • goal and constraints model (GM),

  • user model (UM),

  • adaptation model (AM) and

  • presentation model (PM)


Laos motivation in detail l.jpg
LAOS motivation in detail

  • Why domain model (DM) ?

  • Why goal and constraints model (GM)?

  • Why user model (UM)?

  • Why adaptation model (AM)? and

  • Why presentation model (PM)?


Laos motivation in detail30 l.jpg
LAOS motivation in detail

  • Why domain model (DM) ?

    • Because of historical AHS, ITS, AHAM

  • Why goal and constraints model (GM)?

  • Why user model (UM)?

  • Why adaptation model (AM)? and

  • Why presentation model (PM)?


Slide31 l.jpg
LAOS

  • supporting adaptive hypermedia authoring

  • five layers:

    • Domain Model (DM)

    • Goal and constraints Model (GM)

    • User Model (UM)

    • Adaptation Model (AM)

    • Presentation Model (PM)



Creation of the laos domain model l.jpg
Creation of the LAOS Domain Model

  • Domain Model in MOT is represented by a list of Domain Maps, called Conceptmaps


Conceptmaps in mot l.jpg
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


Laos motivation in detail35 l.jpg
LAOS motivation in detail

  • Why domain model (DM) ?

  • Why goal and constraints model (GM)?

  • Why user model (UM)?

    • Because of historical ITS, AHS, AHAM

    • Because of personalization aim

  • Why adaptation model (AM)? and

  • Why presentation model (PM)?


Laos motivation in detail36 l.jpg
LAOS motivation in detail

  • Why domain model (DM) ?

  • Why goal and constraints model (GM)?

  • Why user model (UM)?

  • Why adaptation model (AM)? and

    • Because of AHAM

    • Because of personalization aim

    • – see also LAG for more details!!

  • Why presentation model (PM)?


Laos motivation in detail37 l.jpg
LAOS motivation in detail

  • Why domain model (DM) ?

  • Why goal and constraints model (GM)?

  • Why user model (UM)?

  • Why adaptation model (AM)? and

  • Why presentation model (PM)?

    • Because of Kuypers, AHAM

    • Because of non-user dependent parameters


Laos motivation in detail38 l.jpg
LAOS motivation in detail

  • Why domain model (DM) ?

  • Why goal and constraints model (GM)?

    • Because of book metaphor

    • Also because of goal adaptation!! (see adapt to what?)

  • Why user model (UM)?

  • Why adaptation model (AM)? and

  • Why presentation model (PM)?


Slide39 l.jpg
LAOS

  • supporting adaptive hypermedia authoring

  • five layers:

    • Domain Model (DM)

    • Goal and constraints Model (GM)

    • User Model (UM)

    • Adaptation Model (AM)

    • Presentation Model (PM)


Creation of the laos goal and constraints model l.jpg
Creation of the LAOS Goal and Constraints Model

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


Lessons in mot l.jpg
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 information

  • Lessons contain labels & their respective weights


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GM book metaphor – why?

  • Domain model only:

    • equivalent to skip the presentation and just tell the user to read the book.

  • search space too big

  • Not only one purposeful orientation


Gm motivation l.jpg
GM motivation

  • intermediate authoring step,

  • goal & constraints related:

  • goals: focused presentation

    • specific end-state

  • constraints: limit search space

    • DM filter



Authoring steps in laos l.jpg
Authoring steps in LAOS

  • STEP 1: write domain concepts + concept hierarchy + attributes (contents) + other domain relations

  • STEP 2: add content related adaptive features regarding GM (design alternatives – AND, OR, weights, etc.)

  • STEP 3: add UM related features (simplest way, tables, with attribute-value pairs for user-related entities (AHAM); UM can be represented as a concept map)

  • STEP 4: decide among adaptation strategies, write in adaptation language medium-level adaptation rules or give the complete set of low level rules (such as condition-action (CA) or IF-THEN rules).

  • STEP 5: define format (presentation means-related; define chapters)

Only precondition is Step 1 before Step 2!!



Laos components definitions l.jpg
LAOS components – definitions


Domain concept model l.jpg
Domain concept model

  • Definition 1. An AHS domain mapDM is determined by the tuple <C,L, Att>, where

    • C: set of concepts,

    • L: set of links,

    • Att a set of DM attributes

  • Definition 2. A domain conceptcDMi. C is defined by <A,C>

    • where A : set of attrs and C set of sub-concepts.

  • Constraint 1.Amin is the minimal set of (standard) attributes required for each concept to have (AAmin).

    • for sufficient meta-data

    • if Amin = required standard attributes.


Domain concept model in mot l.jpg
Domain concept model inMOT

  • Definition 1. An AHS domain mapDM is determined by the tuple <C,L, Att>:

    C: set of concepts,

     L: set of links : only hierarchical and relatedness

    Att a set of DM attributes

  • Definition 2. A domain conceptcDMi. C is defined by <A,C>

    where A : set of attrs and C set of sub-concepts.

  • Constraint 1.Amin is the minimal set of (standard) attributes required for each concept to have (AAmin).

    • Amin = {title, introduction, text, figure, exercise, conclusion}

    • Amin


Domain concept model cont l.jpg
Domain concept model – cont.

  • Definition range 2.1. A domain concept cC is a composite domain concept if c.C.

  • Definition range 2.2. A concept cC is an atomic domain concept if c.C=.

  • Definition 3. A domainlinklL is a tuple <S, E, N, W> with S,E{DMi.ck}i,k (S, E) start and end sets of DM concept instances, respectively; N set of labels of the links; W set of weights of the links.


Domain concept model cont in mot l.jpg
Domain concept model – cont.; inMOT

  • Both composite & atomic concepts exist.

  • Definition 3. A domainlinklL is a tuple <S, E, N, W> with S,E{DMi.ck}i,k (S, E) start and end sets of DM concept instances, respectively; N set of labels of the links; W set of weights of the links.

    card(S)=card(E)=1 ;

    for relatedness relations, card(N)=cart(W)=1


Domain concept model cont52 l.jpg
Domain concept model – cont.

  • Definition 4. A domain attributeaDMi.C.A is a tuple <type, val>, where

    • type is the name of the DM attribute;

    • val is the value (contents) of the DM attribute.

  • Constraint 2. concept c must be involved at least in one link l. This special relation is called hierarchical link (link to ancestor concept). Exception: root concept.


Domain concept model cont in mot53 l.jpg
Domain concept model – cont. ; inMOT

  • Definition 4. A domain attributeaDMi.C.A is a tuple <type, val>, where

    • type is the name of the DM attribute;

    • val is the value (contents) of the DM attribute.

      e.g.,type=“title” ; val=“Neural Networks”

      we refer this attribute specifically with:‘\Neural Networks \Neural Networks \title’

      or, generically, with:DM.Concept.title

  • Hierarchical links exist in MOT.


Algebraic operators respective operations over the model l.jpg
algebraic operators & respective operations over the model

  • constructors

    • create, edit

  • destructors

    • delete

  • visualization or extractors

    • list, view, check

  • compositors

    • repeat

  • Effects

    • restructuring (constructors, destructors and any compositors using at least one operator belonging to the previous categories) or

    • structure neutral (visualization and any compositors applied to visualization alone)


Algebraic operators respective operations over the model in mot l.jpg
algebraic operators & respective operations over the model ; inMOT

  • constructors

    • create, edit

  • destructors

    • delete

  • visualization or extractors

    • list, view, check

  • compositors

    • repeat


Slide56 l.jpg

operation & operator

Range of operation in DM

Description

Create

&

‘C’

  • Input (atomic): optionally object name (text label) of objects such as for DMx,; father concept for c;ids (numerical) of (S, E) and labels, weights for l, ai[h] (with h>Amin)

  • ·Input (set): as above for sets of objects{cj}+,{lj}+,{ai[h]}+ (with 1hAmin)

  • ·Output space: DM, C, L, A

  • ·Output: DMx , {cj}*,{lj}*,{ai[h].type}*

·creates one object such as a concept map, concept, link, a non-standard attribute

·creates sets of objects such as set of new hierarchical child nodes and/ or links connected to the same parent or a full standard attributes set

[1] We assume here that val is defined analogously for CM, c, l.


Slide57 l.jpg

operation & operator

Range of operation in DM

Description

Create

&

‘C’

  • Input (atomic): optionally object name (text label) of objects such as for DMx,; father concept for c;ids (numerical) of (S, E) and labels, weights for l, ai[h] (with h>Amin)

  • ·Input (set): as above for sets of objects{cj}+,{lj}+,{ai[h]}+ (with 1hAmin)

  • ·Output space: DM, C, L, A

  • ·Output: DMx , {cj},{lj},{ai[h].type}

  • N

·creates one object such as a concept map, concept, link, a non-standard attribute

·creates sets of objects such as set of new hierarchical child nodes and/ or links connected to the same parent or a full standard attributes set

inMOT

only one created at a time

[1] We assume here that val is defined analogously for CM, c, l.


Slide58 l.jpg

Edit

&

‘E’

·Input: object ids or expression

·Output: { {DMx, c, l, ai[h]}.type}*

edits the object value

Delete

&

‘D’

·Input: as the two above together, condition or expression

·Outputspace: DM, C, L, A

deletes an object (set) from the corresponding structure or empties the contents


Slide59 l.jpg

Edit

&

‘E’

·Input: object ids or expression

·Output: { {DMx, c, l, ai[h]}.type}

edits the object value

Delete

&

‘D’

·Input: as the two above together, condition or expression

·Outputspace: DM, C, L, A

deletes an object (set) from the corresponding structure or empties the contents

inMOT

internally, ids yes, externally, no

only one edited at a time

only ids internally


Slide60 l.jpg

List

&

‘L’

·Input: Any sets from above, optional condition or expression

·Output: interface object

lists the objects of the set(s)

View

&

‘V’

·Input: (set of) object id-s and mode (e.g., Graph/ Text)

·Output: interface object

gives alternative views of the results to the author

Check

&

‘Ck’

·Input: (set of) object id-s from DM, C, L, A, checking goal, (and implicitly their value domains)

·Output: interface object

checks the checking goal for the selected object and informs about value domain trespasses

Repeat

&

‘R’

·Input: Any of above, number of times or other stopping condition

·Output space: same as operation performed

Repeats any of the operations above


Slide61 l.jpg

List

&

‘L’

·Input: Any sets from above, optional condition or expression

·Output: interface object

lists the objects of the set(s)

View

&

‘V’

·Input: (set of) object id-s and mode (e.g., Graph/ Text)

·Output: interface object

gives alternative views of the results to the author

Check

&

‘Ck’

·Input: (set of) object id-s from DM, C, L, A, checking goal, (and implicitly their value domains)

·Output: interface object

checks the checking goal for the selected object and informs about value domain trespasses

Repeat

&

‘R’

·Input: Any of above, number of times or other stopping condition

·Output space: same as operation performed

Repeats any of the operations above

inMOT

Concepts, attributes, keywords, relatedness links

only keywords have alternative view



Goal and constraints model l.jpg
Goal and constraints model

  • Definition 5. A constraint conceptgGMi.G in GM is defined by the tuple <GA, G, DMj.c.a> GA is a set of attributes; G a set of sub-concepts; DMj.cC is the ancestor DM concept and DMj.c.aA is an attribute of that concept;GMiisthe name of the GM map instance to whom it belongs.

  • Definition 6. A constraint linkglL is a tuple <S, E, N, W> with S,E{DMi.ck}i,k (S, E) start and end sets of GM concept instances, respectively; N set of labels of the links; W set of weights of the links.


Goal and constraints model in mot l.jpg
Goal and constraints model ; inMOT

only 2 attributes possible: weights and labels

  • Definition 5. A constraint conceptgGMi.G in GM is defined by the tuple <GA, G, DMj.c.a> GA is a set of attributes; G a set of sub-concepts; DMj.cC is the ancestor DM concept and DMj.c.aA is an attribute of that concept;GMiisthe name of the GM map instance to whom it belongs.

  • Definition 6. A constraint linkglL is a tuple <S, E, N, W> with S,E{DMi.ck}i,k (S, E) start and end sets of GM concept instances, respectively; N set of labels of the links; W set of weights of the links.

card(W)=card(N)=0

card(S)=card(E)=1


Slide65 l.jpg

Atomic operation & operators

Range of operation in GM

Description

Create

&

‘C’

·Input: original concept id in GM and attribute id; optionally object name (text label) of objects such as for GMx, father concept for c;ids (numeric) of (S, E); labels, weightsfor l

·Input: as above for sets of objects{cj}+,{lj}+,{ai[h].var}+ (1h2)

·Output space: GM, G, L, A

·Output: GMx, {cj}*,{lj}*, {ai[h].type}*

·creates object e.g. GM map, concept, link, a non-standard attribute

·creates sets of objects e.g., set of new hierarchical child nodes +/- links to the same parent or a full standard attributes set

Edit

&

‘E’

·Input: object ids or expression

·Output: { {GMx, c, l, ai[h]}.val}*

edits the object value

Delete

&

‘D’

·Input: as the two above together, condition or expression

·Outputspace: GM, G, L, A

deletes an object (set) from the corresponding structure or empties the contents


Slide66 l.jpg

Atomic operation & operators

Range of operation in GM

Description

Create

&

‘C’

·Input: original concept id in GM and attribute id; optionally object name (text label) of objects such as for GMx, father concept for c;ids (numeric) of (S, E); labels, weightsfor l

·Input: as above for sets of objects{cj}+,{lj}+,{ai[h].var}+ (1h2)

·Output space: GM, G, L, A

·Output: GMx, {cj},{lj}, {ai[h].type}

·creates object e.g. GM map, concept, link, a non-standard attribute

·creates sets of objects e.g., set of new hierarchical child nodes +/- links to the same parent or a full standard attributes set

Edit

&

‘E’

·Input: object ids or expression

·Output: { {GMx, c, l, ai[h]}.val}

edits the object value

Delete

&

‘D’

·Input: as the two above together, condition or expression

·Outputspace: GM, G, L, A

deletes an object (set) from the corresponding structure or empties the contents

inMOT

only one created at a time

only one edited at a time

only ids


Slide67 l.jpg

List

&

‘L’

·Input: Any sets from above, optional condition or expression

·Output: interface object

lists the objects of the set(s)

View

&

‘V’

·Input: (set of) object id-s and mode (e.g., Graph/ Text)

·Output: interface object

gives alternative views of the results to the author

Check

&

‘Ck’

·Input: (set of) object id-s from GM, G, L, Ac , checking goal, (and implicitly their value domains)

·Output: interface object

checks the checking goal for the selected object and informs about value domain trespasses

Repeat

&

‘R’

·Input: Any of above, number of times or other stopping condition

·Output space: same as operation performed

Repeats any of the operations above


Slide68 l.jpg

List

&

‘L’

·Input: Any sets from above, optional condition or expression

·Output: interface object

lists the objects of the set(s)

View

&

‘V’

·Input: (set of) object id-s and mode (e.g., Graph/ Text)

·Output: interface object

gives alternative views of the results to the author

Check

&

‘Ck’

·Input: (set of) object id-s from GM, G, L, Ac , checking goal, (and implicitly their value domains)

·Output: interface object

checks the checking goal for the selected object and informs about value domain trespasses

Repeat

&

‘R’

·Input: Any of above, number of times or other stopping condition

·Output space: same as operation performed

Repeats any of the operations above

inMOT

lessons, labels & weights, sublesson order

Lesson maps have alternative views



What can laos do for you laos is flexible you can reuse the same material in many ways l.jpg
What can LAOS do for you?LAOS is flexible; you can reuse the same material in many ways


Slide71 l.jpg
Example 1: flexibility indexbetween concept C1 and rest of concepts in DMfor automatic semantic linking in the DM or GM

where C = card(DM)

and Amin = card(Amin)


Slide72 l.jpg
Example 2: flexibility degree for selecting attributes from DM concept C1 for GM, considering the order



Future developments laos74 l.jpg
Future developments LAOS

  • Operators for each layer (partially done)

  • Automatic transformations between layers for authoring simplification (partially done)

  • Automatic concept linking (partially done)

  • Verification work of the different layers


Laos summary l.jpg
LAOS summary

  • a five level AHS authoring model with a clear cut separation of the processing levels:

  • 1. the domain model (DM),

  • 2. the goal and constraint model (GM),

  • 3. the user model (UM),

  • 4. the adaptation model (AM) - more LAG following

  • 5. the presentation model (PM).



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