LAG

Alexandra I. CristeaUPB intensive course “Adaptive Hypermedia” January 2004

Overview: LAG

1. What is LAG

2. LAG components

3. Why LAG?

4. New adaptation rules

5. Adaptation strategies

What is LAG?

What is LAG ?

• a generalized adaptation model for generic adaptive hypermedia authoring

• First paper: http://wwwis.win.tue.nl/~alex/Conferences/02/AH02/calvi-cristea-final-w-header-ah2002.pdf

• Second (referring) paper: http://wwwis.win.tue.nl/~alex/Conferences/02/ELEARN02/Cristea-Adaptation-Adaptability.pdf

• Third paper: http://wwwis.win.tue.nl/~alex/HTML/Minerva/papers/UM03-cristea-calvi-accepted.doc

LAG components

LAG components

• Direct adaptation Techniques

• Adaptation Language

• Adaptation Strategies

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: more 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

Why LAG?

Motivation LAG

• Authoring with different complexity degrees (beginner authors vs. advanced)

• Re-usage at each level

• Better semantics

• standardization

New adaptation rules proposed(Adaptation Language)

Adaptation ‘Programming’ language

level rule: IF ENOUGH(<PREREQUISITES>) THEN<ACTION>temporal rule: WHILE <CONDITION> DO <ACTION>repetition rule:FOR <i=1..n> DO <ACTION>interruption command:BREAK <ACTION>generalization command:

GENERALIZE (COND, COND1, …, CONDn)specialization command:

SPECIALIZE (COND, COND1, …, CONDn)

A level rule

IF ENOUGH(<PREREQUISITES>) THEN<ACTION>• ENOUGH = fct. of no. & quality of prerequisites; true if, e.g.,

a given no. of prerequisites from a set is fulfilled – Ex: PREREQUISITES = time_spent; ACTION = “go to next level”– Rule becomes:

• IF ENOUGH (time_spent on crt. level) THEN “go to next level”– Where ENOUGH is defined, e.g., as follows:

• ENOUGH (time) = 30 time units;

• time (advanced topic) = 10 (time units per topic);

• ENOUGH (medium topic) = 5 (time units per topic);

• ENOUGH (beginner topic) = 2 (time units per topic);

A temporal rule:

• action repeated as long as 1-more cond.s hold:

WHILE <CONDITION> DO <ACTION>• According to CM paradigm, concepts canned but

assembled depending on UM & their attr.s ( more than mere addition/deletion of links)– E.g, a warning is repeated that user search direction is wrong.

Another cond. can trigger a service denial response if a threshold is passed.

A repetition rule:

• a certain (simple / composed) action repeated for a no. of times predefined by author:

FOR <i=1..n> DO <ACTION>• describes the time this action has to last before

reader can move on.

An interruption command:

• user action is interrupted & s/he is forced to undertake a different one:

BREAK <ACTION> • represents an exacerbation of traditional behavior

of AHS: user is “punished” if she doesn’t stick to learning pathways provided by system.

A generalization command:

• new concept reader has reached is compared w. more general ones it refers to. As a result, the reader is pointed to related concept(s):

GENERALIZE (COND, COND1, …, CONDn)

A specialization command:

• if concept is general, system deductively points reader to more specific instantiations:

SPECIALIZE (COND, COND1, …, CONDn)

– E.g, if student reads about “Model Reader” in a course on postmodern literature, she can be pointed to an extract from Calvino’s novel ‘Se una notte’, where this notion is exemplified.

Other commands

• comparison (concept analogy search) &

• difference

• both instances of generalization;

• duration – a rule related to repetition– lyrical use of repetitions in hyperfiction has

given rise to a particular design pattern

Adaptation Strategies

Adaptive strategies for cognitive styles

converger (abstract, active) medium_increase() : generate adaptive presentation with (obviously) increasing difficulty

1. Explanation: Convergers are abstract and active; they like to feel in control; start with course for intermediates at medium adaptivity level, repeat for a number of times:-          evaluate state of learner and start increasing difficulty & decreasing adaptivity level if result=good -          evaluate state of learner and start decreasing level if result=bad

2. Translation at medium level: (ENOUGH shows here that the result is above an average result)AdaptLevel= 5; N=AskUser(); # this is to let user feel and be in control; levels: (1=min to

10=max)FOR <I=1..N> DO{ SPECIALIZE (ENOUGH(Result)); IF (AdaptLevel>1) AdaptLevel--; GENERALIZE (NOT(ENOUGH(Result))); IF (AdaptLevel<5) AdaptLevel++;} # Note that adaptation level is not allowed to increase too much3. Translation at low level: (the average can be implemented but takes more space)DiffLevel = 3; AdaptLevel= 5; # note that here there is no predefined number of repetitionsIF <ACTION> THEN # Note that above we don’t need the action of the user for triggering;{ IF (Result1 +Result2)/2>5 AND DiffLevel<10 THEN # Note that ‘enough’ and specialize { DiffLevel++; IF (AdaptLevel>1) AdaptLevel--;} # must be redefined each time IF (Result1 +Result2)/2<5 AND DiffLevel>1 THEN {DiffLevel--; IF (AdaptLevel<5)

AdaptLevel++;}}

diverger (concrete, reflective) low() : generate adaptive presentation with adaptively increasing difficulty

Explanation: start with course for beginners at high level of adaptation, from general issues + examples, down + rest as in Table 1

2. Translation at medium level: (ENOUGH same as in Table 1) AdaptLevel= 10; GENERALIZE(); WHILE (not_finished) DO{ SPECIALIZE (ENOUGH(Result)); IF (AdaptLevel>5) AdaptLevel--; # Note that we

keep adaptation GENERALIZE (NOT(ENOUGH(Result))); IF (AdaptLevel<10) AdaptLevel++; } #

level high here

3. Translation at low level: DiffLevel = 1; AdaptLevel= 10; IF <ACTION> THEN { IF (Result1 +Result2)/2>5 AND DiffLevel<10 THEN { DiffLevel++; IF

(AdaptLevel>5) AdaptLevel--;} IF (Result1 +Result2)/2<5 AND DiffLevel>1 THEN {DiffLevel--; IF

(AdaptLevel<10) AdaptLevel++;}}

assimilator (abstract, reflective)

high() : generate adaptive presentation with high difficulty and little adaptivity

1. Explanation: start with course for intermediates at high level adaptation + similar Table 1

2. Translation at medium level: (ENOUGH same as in Table 1) SPECIALIZE(); AdaptLevel= 1; WHILE (not_finished) DO { GENERALIZE(ENOUGH(Result)); SPECIALIZE (NOT(ENOUGH(Result))); }

3. Translation at low level: DiffLevel = 10; AdaptLevel= 1; IF <ACTION> THEN{ IF (Result1 +Result2)/2>5 AND DiffLevel<10 THEN DiffLevel++; IF (Result1 +Result2)/2<5 AND DiffLevel>1 THEN DiffLevel--; }

accommodator (concrete, active) medium_decrease() : generate adaptive presentation with (obviously) decreasing difficulty

-          1. Explanation: Accomodators like to feel in control; they want first examples and then theory.

2. Translation at medium level: (ENOUGH same as in Table 1)AdaptLevel= 5; N=AskUser(); # this is to let user feel and be in control; FOR <I=1..N> DO{ SPECIALIZE (ENOUGH(Result)); IF (AdaptLevel>1) AdaptLevel--; GENERALIZE (NOT(ENOUGH(Result))); IF (AdaptLevel<5) AdaptLevel++; }

3. Translation at low level: (the average can be implemented but takes more space)DiffLevel = 8; AdaptLevel= 5; IF <ACTION> THEN { IF (Result1 +Result2)/2>5 AND DiffLevel<10 THEN {DiffLevel++; IF (AdaptLevel>1)

AdaptLevel--;} IF (Result1 +Result2)/2<5 AND DiffLevel>1 THEN {DiffLevel--; IF (AdaptLevel<5)

AdaptLevel++;}}