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Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

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Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea
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Page 1: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages

Alexandra Cristea

Page 2: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

LAOSModel

Page 3: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

Adaptation granularity

• lowest level: direct adaptation techniques: – adaptive navigation support & adaptive presentation (Brusilovsky

1996), implem.: AHA!; expressed in AHAM syntax– techniques usually based on threshold computations of variable-

value pairs.

• medium level: goal / domain-oriented adaptation techniques:– based on a higher level language that embraces primitive

low level adaptation techniques (wrapper)– new techniques: adaptation language (Calvi & Cristea 2002),

• high level: adaptation strategies– wrapping layers above– goal-oriented

Adaptation Assembly language

Adaptation Programming

language

Adaptation Function calls

Page 4: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

How to create an adaptation language?

• Adaptation Language as an Intermediate Platform (between authoring environment and adaptation engine)

• An interface between the adaptation engineer and the authoring system

Page 5: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

Contents• Motivation

– “Authoring problem” & solutions– Comparison of 2 adaptation languages, focus on learning styles

(LS)

• Adaptation Language as an Intermediate Platform– Elements of course dynamics– Types of adaptive strategies– Classification of actions in adaptive strategies

• AHA! & LAG-XLS (XML LS adaptation language)• LAOS & LAG (generic adaptation language)• Authoring of learning styles in LAG and AHA!• Conclusion

Page 6: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

Contents• Motivation

– “Authoring problem” & solutions– Comparison of 2 adaptation languages, focus on learning styles

(LS)

• Adaptation Language as an Intermediate Platform– Elements of course dynamics– Types of adaptive strategies– Classification of actions in adaptive strategies

• AHA! & LAG-XLS (XML LS adaptation language)• LAOS & LAG (generic adaptation language)• Authoring of learning styles in LAG and AHA!• Conclusion

Page 7: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

“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

The solutionReuse of dynamics:“Exchanging not only the ingredients, but the recipes as well”Adaptation languages:- LAG - LAG-XLS (read as “LAG-excels”)

Page 8: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

LAG language

Dr. Alexandra [email protected]

http://www.dcs.warwick.ac.uk/~acristea/

Page 9: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

What does the LAG adaptation LAG adaptation languagelanguage do?• Turing-complete ? – no!• Captures adaptation patterns, typical for AHS,

for reuse• We start with a set of desired adaptive behavior:

– Inherited from direct adaptation techniques: If, Action – ConditionsConditions, EnoughEnough conditions– We could add more: e.g., WhileWhile, ForFor + BreakBreak,

GeneralizeGeneralize, SpecializeSpecialize

Page 10: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

Classification of Actions in Adaptive Strategies (from N. Stash)

Basic actions on items Selection

Showing the content of an item

Showing a link to an item

Defaults

Hierarchical actions on items Actions on child items

Actions on parent items

Actions on groups of items (e.g. siblings)

Ordering

Performing “actions on items” on each group item

Actions on the overall environment

Changing the layout of the presentation

Page 11: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

Select

• selecting concept representation

• In MOT, given by attributes, so LAG has:– DM.Concept.attribute or– GM.Concept or GM.Concept.attribute– Or presentation only:– PM.DM.Concept.attribute.show– PM.GM.Concept.show

Page 12: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

sort

• sequencing concept representation

• Order of the current concept:– GM.Concept.order

Page 13: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

showContent

• showing content of a concept– PM.DM.Concept.attribute.show– PM.GM.Concept.show

Page 14: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

showLink

• showing link to a concept

• No difference, only in the menu links can be made available:– PM.DM.Concept.attribute.show– PM.GM.Concept.show

• For having a menu, we need:– PM.menu = true

Page 15: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

setDefault

• setting defaults

WHILE GM.Concept.label == ‘’

( PM.GM.Concept.show = true)

Page 16: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

actions

• updating the User Model

Overlay variable:

UM.GM.Concept.knowledge +=1

Free variable:

UM.knowledge += 1

Page 17: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

Concepts & their contents

Stressing the overlay structure of user model on top of

• Conceptmaps (DM) – UM.DM.stereotype1 = beg

• or Lessons (GM):– UM.GM.stereotype1 = beg

• or as independent variables:– UM. stereotype1 = beg

Page 18: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

Concepts & their contents

Stressing the overlay structure of presentation model on top of

• Conceptmaps (DM) – PM.DM.show = true

• or Lessons (GM):– PM.GM.show = true

Page 19: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

Special attributes• As few as possible!• Event attributes:

– Access: a concept has been seen by the user:

UM.GM.Concept.access = true

• Hierarchy attributes:– Parent: the parent concept of a given concept:

DM.Concept.parent– Child: the child concept of a given concept:

GM.Concept.child

Page 20: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

Presentation model versions

• the presentation model (e.g., reflected in the AHA! delivery engine)      PM.GM.next = true // or PM.next // next button appears, showing the next most appropriate concept            //according to the order in MOT and the showability       PM.GM.ToDo = true // a list of items still to open appears, that are

//showable and have not been visited yet;           // their order reflects the order in MOT ; also PM.ToDo      PM.GM.menu = true // table of contents that is already used in AHA,

// should be also able to dissapear ; also PM.menu

Page 21: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

Type & Order & Label of Attributes• Type of Attributes (in Lessons) usage

– GM.Concept.type = title – DM.Concept.attribute.type = title

• Order of Attributes (in Lessons) usage– GM.Concept.order

• Labels, weights of attributes (in Lessons) usage– GM.Concept.label = beg

Page 22: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

Overall structure of the LAG adaptation strategy// Description

// Variables

initialization (

// what the user sees first

)

implementation (

// how the user interacts with the system

)

Page 23: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

Example strategies

• http://prolearn.dcs.warwick.ac.uk/

Page 24: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

Extended LAG: Adaptation strategy example// DESCRIPTION// This strategy slowly rolls out (and hides) the attributes of concepts based// on how often a concept has been accessed. Concepts are monitored

through// the title attribute.// Concept.beenthere keeps track of visits; Concepts have the label// "showatmost" if they should disappear after a while (with weight

indicating// the number of visits required) and the label "showafter" if they should

show// up after a while (again, weight indicates the number of visits)

// VARS// UM.GM.Concept.beenthere, GM.Concept.label, GM.Concept.weight

Page 25: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

Extended LAG: Adaptation strategy example

initialization(

while true ( UM.GM.Concept.beenthere = 0 PM.GM.Concept.show = true ) while GM.Concept.label == showafter ( if GM.Concept.weight > 1 then ( PM.GM.Concept.show = false ) else ( PM.GM.Concept.show = true ) ))

Page 26: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

Extended LAG: Adaptation strategy exampleimplementation (

if UM.GM.Concept.access == true then ( UM.GM.Concept.beenthere += 1 )

if enough(UM.GM.Concept.beenthere >= GM.Concept.weight GM.Concept.label == showatmost ,2) then ( PM.GM.Concept.show = false )

if enough(UM.GM.Concept.beenthere >= GM.Concept.weight GM.Concept.label == showafter ,2) then ( PM.GM.Concept.show = true ))

Page 27: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

Extended LAG: Adaptation strategy example 2

// DESCRIPTION// strategy which shows the beginner concepts first (together with the

concepts for all learners); // after all beginner concepts are read, the intermediate concepts are

shown as well;// finally, after all the intermediate concepts are read, the advanced

concepts are shown and the course can be viewed completely// Note: this is inspired from games, where the player can only look at

the current level at the beginning, but when he manages to finish the level, he can access the next level, as well as all the levels below.

// VARS// UM.GM.beginnerno, UM.GM.intermediateno, UM.GM.advancedno,

GM.Concept.label, PM.GM.Concept.show, UM.GM.Concept.first, UM.GM.stereotype1

Page 28: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

Extended LAG: Adaptation strategy example 2

initialization(

// INITIALIZATION// initialize as beginnerUM.GM.stereotype1 = beg

// initialize sets of lesson concepts for stereotypes// AHA! 'personal' variable; name = 'GMname'+'stereotypename'UM.GM.beginnerno = 0UM.GM.intermediateno = 0UM.GM.advancedno = 0

// …)

Page 29: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

Extended LAG: initialization (ex.2)

• // as long as still general concepts available, make those readable• while GM.Concept.label == null • ( • PM.GM.Concept.show = true• UM.GM.Concept.first = true• )

• // compute number beginner texts• // as long as still beginner concepts available, make those readable• while GM.Concept.label == beg • ( • UM.GM.beginnerno += 1 • PM.GM.Concept.show = true• UM.GM.Concept.first = true• )

Page 30: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

Extended LAG: initialization (ex.2)

// compute number of intermediate textswhile GM.Concept.label == int ( UM.GM.intermediateno += 1 UM.GM.Concept.first = true )

// compute number of advanced textswhile GM.Concept.label == adv ( UM.GM.advancedno += 1 UM.GM.Concept.first = true )

Page 31: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

Extended LAG: implementation (ex.2)

implementation (

// IMPLEMENTATION// remove already access itemsif enough( UM.GM.Concept.access == true UM.GM.Concept.first == true GM.Concept.label == beg , 3 ) then ( UM.GM.beginnerno -= 1 UM.GM.Concept.first = false )

…)

Page 32: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

Extended LAG: implementation (ex.2)

// change from beginner to intermediate if it is appropriateif (UM.GM.beginnerno == 0) then UM.GM.stereotype1 = int

// show to intermediate only what is relevantif enough( GM.Concept.label == int UM.GM.stereotype1 == int , 2 ) then ( PM.GM.Concept.show = true )

Page 33: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

Extended LAG: implementation (ex.2)

// remove already access itemsif enough( UM.GM.Concept.access == true GM.Concept.label == int UM.GM.Concept.first == true , 3 ) then ( UM.GM.intermediateno -= 1 UM.GM.Concept.first = false )

// change from intermediate to advanced if it is appropriateif (UM.GM.intermediateno == 0) then UM.GM.stereotype1 = adv

Page 34: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

Extended LAG: implementation (ex.2)

// show to advanced only what is relevantif enough( GM.Concept.label == adv UM.GM.stereotype1 == adv , 2 ) then ( PM.GM.Concept.show = true ) )

Page 35: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

Another example (Ex.3)initialization ( while true ( PM.GM.Concept.show = false ) '\Neural Networks II\Neural Networks I\title'.show = true)implementation (

// if you visited the parent you should be able to visit the child

if UM.GM.Concept.parent.access then ( GM.Concept.show = true

))

Page 36: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

LAG Grammar & Semantics

• Grammar:– http://www.dcs.warwick.ac.uk/~acristea/M

OT/help/LAGgrammar%5B2%5D.doc

• Semantics: – http://www.dcs.warwick.ac.uk/~acristea/M

OT/help/LAGgrammarSemantics.doc

Page 37: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

LAG grammarPROG DESCRIPTION VARIABLES INITIALIZATION IMPLEMENTATIONDESCRIPTION // “text”VARIABLES // “text” INITIALIZATION initialization ( STATEMENT )IMPLEMENTATION implementation ( STATEMENT )STATEMENT IFSTAT | WHILESTAT | FORSTAT | BREAKSTAT | GENSTAT |

SPECSTAT | (STATEMENT)* STATEMENT |ACTION IFSTAT if CONDITION then (STATEMENT)+ | if CONDITION then

(STATEMENT) + else (STATEMENT)+WHILESTAT while CONDITION (STATEMENT)+ [TARGETLABEL]ACTION ATTRIBUTE OP VALUECONDITION enough((CONDITION)+, VALUE) | PREREQPREREQ ATTRIBUTE COMPARE VALUEATTRIBUTE GENCONCEPTATTR | SPECCONCEPTATTRSPECCONCEPTATTR ‘\SPECCONMAP\SPECCON\SPECATTR\

ATTR’.ATTRATTRLAOSCM, LAOSCONCEPTMAP DM | GM | UM | PM | CMATTR Attribute | title | keywords | text | introduction | conclusion | exercise | child | parent | Relatedness | ATTR.ATTR |

CONCEPT.ATTR |label | weight | “text”ATTRATTR type | order | next | ToDo | menu | show | access | visited | “text”

Page 38: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

Grammar + SemanticsPROG DESCRIPTION VARIABLES INITIALIZATION IMPLEMENTATION • PROG: A LAG strategy or procedure, containing a set of instructions (programming

constructs) defining the user and presentation adaptation in an adaptive hypermedia environment.

• DESCRIPTION: The description of PROG; contains a natural language description of the behavior of the adaptive strategy; it serves as the label (meta-description) for the whole strategy. It is important, as laic (non-programmer) authors should be able to extract from it the necessary elements to make a decision about using this adaptation or not.

• VARIABLES: The variables of PROG; contains the list of variables that are used in the adaptive strategy. This information can be used by a laic (non-programmer) author to decide what attributes of the GM (goal and constraints model) should be filled-in for this strategy.

• INITIALIZATION: The static initialization part of PROG; in this part, the initial experience of the user, when entering the adaptive environment, is described. This is useful so that a user doesn’t enter a void environment. Here, all the default decisions are set. Adaptive environments which are adaptable but not adaptive can only render this part.

• IMPLEMENTATION: The dynamic implementation part of PROG; in this part, the interactivity between the adaptive environment and the user is described (for instance, the effect of user clicks).

Page 39: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

Grammar + Semantics (cont)

INITIALIZATION initialization ( STATEMENT )IMPLEMENTATION implementation ( STATEMENT )STATEMENT IFSTAT | WHILESTAT |

(STATEMENT)*STATEMENT |ACTION • STATEMENT: The LAG language is a simple language built of a number

of programming constructs, or statements, as follows:– IFSTAT: condition-action rules: the basic building block of the

adaptation language. – WHILESTAT: loops– ACTION: This is part of the basic building block of condition-actions. It

can be used by itself, as if the condition attached to it would be set to TRUE. This statement is the only one that allows specification of updates and changes of visible (such as the current screen) or invisible (such as the user knowledge) variables.

Page 40: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

Grammar + Semantics (cont)

IFSTAT if CONDITION then (STATEMENT)+ | if CONDITION then (STATEMENT) +

else (STATEMENT)+WHILESTAT while CONDITION (STATEMENT)+ACTION ATTRIBUTE OP VALUE OP = | += | -= | .=VALUE true | false | “text”

Page 41: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

Grammar + Semantics (cont)

CONDITION enough((CONDITION)+, VALUE) | PREREQPREREQ ATTRIBUTE COMPARE VALUE

ATTRIBUTE GENCONCEPTATTR | SPECCONCEPTATTR

COMPARE == | < | > VALUE “number”

• CONDITION: for CA or ECA rules, specified by 1-enough prerequisites– enough: number VALUE of conditions should be fulfilled.

• ATTRIBUTE: appears in conditions or actions; can be a generic attribute of DM, GM, UM or PM (e.g., UM.DM.Concept.knowledge); or can be specific (e.g., ‘\Neural Networks Map\Learning\Introduction\Weight’.show). For reusability use generic!

Page 42: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

Grammar + Semantics (cont)GENCONCEPT ATTR LAOS.CONCEPT.ATTR |

LAOS.CONCEPT.ATTR.ATTRATTR | LAOS.ATTR | LAOS.LAOS.ATTRATTR | LAOS.LAOS.CONCEPT.ATTR.ATTRATTR

SPECCONCEPTATTR ‘\SPECCONMAP\SPECCON\SPECATTR\ATTR’.ATTRATTR

LAOS DM | GM | UM | PMCONCEPT Concept | “text”ATTR Attribute | title | keywords | text | introduction | conclusion | exercise | child | parent | Relatedness | ATTR.ATTR | CONCEPT.ATTR |

label | weight | “text”ATTRATTR type | order | next | ToDo | menu | show | access | visited | “text”SPECCONMAP “text”SPECCON “text”SPECATTR “text”

Page 43: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

Contents

• Motivation– “Authoring problem” & solutions– Comparison of 2 adaptation languages, focus on learning styles

(LS)

• Adaptation Language as an Intermediate Platform– Elements of course dynamics– Types of adaptive strategies– Classification of actions in adaptive strategies

• AHA! & LAG-XLS (XML LS adaptation language)• LAOS & LAG (generic adaptation language)• Authoring of learning styles in LAG and AHA!• Conclusion

Page 44: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

How to create an adaptation language?• Adaptation Language as an Intermediate

Platform (between authoring environment and adaptation engine)

• We need to find out which are the:

– Elements of course dynamics• For this, we need to analyse what happens in

an adaptive course, and what is done dynamically:

Page 45: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

Selection of Media Items

Visual style

• Diagrams• Illustrations• Graphs• Flowcharts• Animations+ audio

Verbal style

• More text• Possibly audio

Page 46: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

Providing navigation paths

Sequential style

Linear step-by-step learning process

Global style

Global overview first, then details

Page 47: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

Presentation for Visual+Global Learner

Page 48: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

Presentation for Verbal+Analytic Learner

Page 49: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

Ordering information

Active style

Learn by doing things actively

Reflective style

Learn by looking at examples

Page 50: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

Contents

• Motivation– “Authoring problem” & solutions– Comparison of 2 adaptation languages, focus on learning styles

(LS)

• Adaptation Language as an Intermediate Platform– Elements of course dynamics– Types of adaptive strategies– Classification of actions in adaptive strategies

• AHA! & LAG-XLS (XML LS adaptation language)• LAOS & LAG (generic adaptation language)• Authoring of learning styles in LAG and AHA!• Conclusion

Page 51: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

• Adaptation Language as an Intermediate Platform• Having found the elements of course dynamics, we

need to find out what variation we have in terms of:

–Types of adaptive strategies

Page 52: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

Types of Adaptive Strategies

• Instructional strategies- selection of media items

- ordering information or providing different navigation paths

• Instructional meta-strategies – inference or monitoring strategies. Preferences for:- certain types of information (e.g. text vs. image)

- reading order (e.g. breadth-first vs. depth-first)

Page 53: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

Contents• Motivation

– “Authoring problem” & solutions– Comparison of 2 adaptation languages, focus on learning styles

(LS)

• Adaptation Language as an Intermediate Platform– Elements of course dynamics– Types of adaptive strategies– Classification of actions in adaptive strategies

• AHA! & LAG-XLS (XML LS adaptation language)• LAOS & LAG (generic adaptation language)

Authoring of learning styles in LAG and AHA!• Conclusion

Page 54: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

• Adaptation Language as an Intermediate Platform

• Having found the elements of course dynamics, and the types of adaptation strategies, we need to find out the:–Classification of actions in adaptive

strategies

Page 55: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

Classification of Actions in Adaptive Strategies (from N. Stash)

Basic actions on items Selection

Showing the content of an item

Showing a link to an item

Hierarchical actions on items Actions on child items

Actions on parent items

Actions on groups of items (e.g. siblings)

Ordering

Performing “actions on items” on each group item

Actions on the overall environment

Changing the layout of the presentation

Page 56: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

Contents

• Motivation– “Authoring problem” & solutions– Comparison of 2 adaptation languages, focus on learning styles

(LS)

• Adaptation Language as an Intermediate Platform– Elements of course dynamics– Types of adaptive strategies– Classification of actions in adaptive strategies

• LAG-XLS (XML LS adaptation language) (& AHA!) • LAOS & LAG (generic adaptation language)• Authoring of learning styles in LAG and AHA!• Conclusion

Page 57: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

AHA! Adaptive Hypermedia Architecture

WWW server

User(student)

Author

DM/AMlocal

pages

Manager

Authoring tools

ConceptEditorGraph Author

Java Applets

AHA! engine

Java servlets

DM - Domain ModelAM - Adaptation ModelUM - User Model

Pages from externalWWW servers

UM

Page 58: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

Classification of Actions in Adaptive Strategies (from N. Stash)

Basic actions on items Selection

Showing the content of an item

Showing a link to an item

Hierarchical actions on items Actions on child items

Actions on parent items

Actions on groups of items (e.g. siblings)

Ordering

Performing “actions on items” on each group item

Actions on the overall environment

Changing the layout of the presentation

Page 59: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

LAG-XLS:an XML Learning Style Adaptation Language

Elements of the language:• select – selecting concept representation• sort – sequencing concept representation• showContent – showing content of a concept• showLink – showing link to a concept• setDefault – setting defaults • actions – updating the User Model

Page 60: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

Select

• selecting concept representation

• <select attributeName="media">

Page 61: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

sort

• sequencing concept representation

Page 62: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

showContent

• showing content of a concept

<showContent>image</showContent>

Page 63: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

showLink

• showing link to a concept

<showLink>

<linkTo>text</linkTo>

<comment>See textual information</comment>

</showLink>

Page 64: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

setDefault

• setting defaults

<showContentDefault>default</showContentDefault>

Page 65: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

actions

• updating the User Model

<action attributeName="media"> <UMvariable>personal.VERBvsIM</UMvariable>

<expression>personal.VERBvsIM-5</expression>

</action>

Page 66: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

Examples LAG-XLS

Page 67: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

Verbalizer versus Imager

<if><condition>personal.VERBvsIM &lt; 30</condition> <then> <select attributeName="media"> <showContent>image</showContent> <showContentDefault>default</showContentDefault>

<showLink> <linkTo>text</linkTo> <comment>Textual information</comment> </showLink> </select> </then> </if>

<if><condition>personal.VERBvsIM &gt; 70</condition> <then> <select attributeName="media"> <showContent>text</showContent> <showContentDefault>default</showContentDefault>

<showLink> <linkTo>image</linkTo> <comment>Pictorial information</comment> </showLink> </select> </then> </if>

Page 68: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

Monitoring Strategy:Image versus Text Preference<if><condition>personal.initial.VERBvsIM > 29 & personal.initial.VERBvsIM < 71 & personal.traceTextvsImage & concept.media==“image” & concept.visited==0 & !parent.text</condition><then> <action attributeName="media"> <UMvariable>personal.VERBvsIM</UMvariable><expression>personal.VERBvsIM-5</expression></action></then></if>

<if><condition>personal.initial.VERBvsIM > 29 & personal.initial.VERBvsIM < 71 & personal.traceTextvsImage & concept.media==“text” & concept.visited==0 & !parent.image </condition><then> <action attributeName="media"> <UMvariable>personal.VERBvsIM</UMvariable><expression>personal.VERBvsIM+5</expression></action></then></if>

Page 69: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

Inferring preferences: text vs. image

UM: personal.VERBvsIM-5

UM: personal.VERBvsIM+5

Presentation for Verbalizer

Presentation for Imager

Page 70: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.
Page 71: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

Contents

• Motivation– “Authoring problem” & solutions– Comparison of 2 adaptation languages, focus on learning styles

(LS)

• Adaptation Language as an Intermediate Platform– Elements of course dynamics– Types of adaptive strategies– Classification of actions in adaptive strategies

• AHA! & LAG-XLS (XML LS adaptation language)• LAOS & LAG (generic adaptation language)• Authoring of learning styles in LAG and LAG-XLS• Conclusion

Page 72: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE strategy SYSTEM "../strategy.dtd"> <strategy name="VerbalizerVersusImager"> <description>Strategy for "Verbal" versus "Visual“

style</description> <if> <condition>personal.VERBvsIM &lt; 30</condition> <then> <select attributeName="media"> <showContent>image</showContent>

<showContentDefault>default</showContentDefault> <showLink> <linkTo>text</linkTo> <comment>See textual information</comment> </showLink> </select> </then> </if> …</strategy>

Imager (Visualizer) strategyLAG (old) LAG-XLS

Page 73: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

<if><condition>personal.initial.VERBvsIM < 29 & personal.initial.VERBvsIM > 71 & personal.traceTextvsImage & concept.media==“image” & concept.visited==0 & !parent.text</condition><then> <action attributeName="media"> <UMvariable>personal.VERBvsIM</UMvariable><expression>personal.VERBvsIM-5</expression></action></then></if>

Monitoring Strategy: Preference for ImageLAG LAG-XLS

Page 74: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

Contents

• Motivation– “Authoring problem” & solutions– Comparison of 2 adaptation languages, focus on learning styles

(LS)

• Adaptation Language as an Intermediate Platform– Elements of course dynamics– Types of adaptive strategies– Classification of actions in adaptive strategies

• AHA! & LAG-XLS (XML LS adaptation language)• LAOS & LAG (generic adaptation language)• Authoring of learning styles in LAG and AHA!• Conclusion

Page 75: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

Conclusion

• Extracted intelligence

• Presented 2 adaptation languages:

- LAG

- LAG-XLS

Page 76: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

Contents

• Motivation– “Authoring problem” & solutions– Comparison of 2 adaptation languages, focus on learning styles

(LS)

• Adaptation Language as an Intermediate Platform– Elements of course dynamics– Types of adaptive strategies– Classification of actions in adaptive strategies

• AHA! & LAG-XLS (XML LS adaptation language)• LAOS & LAG (generic adaptation language)• Authoring of learning styles in LAG and AHA!• Conclusion

Page 77: Explicit Intelligence in Adaptive Hypermedia: Generic Adaptation Languages Alexandra Cristea.

• Questions?


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