faculty of mathematics and informatics TU/e eindhoven university of technology 1 Towards Generic Adaptive Systems: Analysis of a Case Study Licia Calvi

/faculty of mathematics and informatics

TU/e eindhoven university of technology

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Towards Generic Adaptive Systems:Towards Generic Adaptive Systems:Analysis of a Case StudyAnalysis of a Case Study

Licia Calvi & Alexandra Cristea

Databases & Hypermedia Group, Department of Informatics

AH’02: AH’02: May 29-31, 2002May 29-31, 2002, Malaga, Malaga



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Keywords

• Generic AS

• XML

• AHA!



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Index• Motivation & background• AHA! & beyond• Concept-mapping paradigm • New Adaptation Rules: How to Augment the

Adaptation Engine • Implementing New Rules in the current AHA! • Problems & need of checking mechanisms • Future directions • Conclusion



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Ideas & Motivation

• AH author can separate w. difficulty:– links vs. concepts; – adaptive navigation vs. a. presentation & – carefully design a synchronous system

• a better way to look at AH authoring pb: – combination of CM paradigm for course narrative &– several new adaptation rules



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Method

• analyze AHA! – for general observations on AHS &

– improvement suggestions for AHA!

• suggest a concept-based AHS structure

• extend rule-based overlay method for user-adaptation

another step towards flexible generic-purpose AH



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A few words on AHA!

• well-known system

• AH pioneer (1st version: 1996/97) &

• domain benchmark

• power & popularity due to simplicity



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AHA! adaptation methods1. page = concept, showed/not acc. to conds

(on vars) in XML file (“requirement list”)2. vars changing rules simple (“generate list”)3. cond. fragm. in pgs: AHA tag language (XML

based)

1-2: adaptive navigation supportadaptive navigation support (pg level) 3: adaptive presentationadaptive presentation



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Problems

• Lack of:– Reusability– Expressivity



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Concept mapping• intuitive classif.: divide source material into

concepts: piece has independent semanticsindependent semantics (~ semantic Web)

– low level: atomic concepts – concepts collections: composite concepts– together: concept hierarchy

• = primitive building blocks of hypermedia



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Linking• building blocks w. diff. sequences diff. presentations

(high granularity level: concept level) adaptive navigation support adaptive presentation: at lower, concepts fractions level

– E.g. text intro. can be used w. other introductory fragments in introductory chapter, (to drop at later browsing) etc.

– Pb.: no independent meaning.

• common solution: – divide concepts into sub-concepts; but:– pb: semantics loss; collaborative authoring; cannot be

semantically annotated & not significant for search mechanisms.



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Attributes• more appropriate :

– concept name, alternative contents, fragments, etc.

• course content mapped on concept hierarchy & describing concepts w. attributes set, adaptation = concept-level & attribute adaptation.

• Advantage: can be performed & viewed from high level– no need of separate consideration of cond. fragments in texts

(difficult to re-use by other authors) content - & adaptative engine rules authoring is separated

easier automatic checks adaptation = combining concept attributes into pages

• (info pieces that can be show at a time)



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Navigation

• dependent on presentation format – e.g.: a handheld device w. short pg displays “next”

button more often within same lesson

• model: compatible w. RDF standard:– resources concepts, – properties attributes & – literals attribute values



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Adaptive navigation & presentation



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What is already in AHA?• main difference:

– Concepts: at pg granulation– pgs constructs (conditional fragments) concept attrs

& cannot be independently used w. other concepts or c. attributes.

• under development version consider multiple attributes & a DB structure, that allows flexibility



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Typical adaptivity

• Most AS = rule-based, i.e.:

• Adaptation : conditional rules:

IF <PREREQUISITE> THEN <ACTION>



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New adaptation rules proposed



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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);



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A temporal rule:

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

WHILE <CONDITION> DO <ACTION>

– E.g: warning - user search direction is wrong service denial over a threshold / drill ex.



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A repetition rule:

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

FOR <i=1..n> DO <ACTION>• E.g.: time action has to last before reader can

move on.



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An interruption command:

• forced user to do smthg. else:

BREAK <ACTION> • = exacerbation of traditional AHS behavior: user

“punished” for not sticking to learning pathways



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A generalization command:

• new concept 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)



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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.



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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



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<if expr=”enough”><enough> Here definition of enough</enough><block> Here a conditional fragment</block><block> Here optional alternative fragment</block>

<while expr=“wrong_search>50”>

<block> Here a conditional fragment</block></while>

Another example is:<WHILE expr=“art>70 and not

culture>80”> <BLOCK> Here predefined events sequence </BLOCK> <BLOCK> Here an alternative event (action) </BLOCK></WHILE>

1. the level rule: 2. the temporal rule:



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3. the repetition rule: 4. interruption command:

<for expr=”question&sm;5”> <block> Here a conditional fragment </block></for>E.g, explan. is given if question no 5.

Next follows diff.strategy – e.g., suggestion to consult diff. material, etc.

<break><block>

Here a conditional fragment</block></break>

5.generalization command:

6. specialization command:

<generalize concept=”myconcept”> Here details of generalization (levels, etc.)</generalize>Example:<generalize concept= “double_code_theory”> Here details of generalization (levels, etc.)</generalize>E.g. jump 1-* levels in concept hierarchy.

Extra processing can be done in body part, e.g. commenting on next level & reason why.

<specialize concept=”myconcept”> Here details of specialization (levels, etc.)</specialize>Example:<specialize concept=“Model Reader”> Here details of specialization (levels, etc.)</specialize>Similar to 5, but direction of processing in

concept hierarchy is top-down instead of bottom-up.



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Pros & cons

• Balance: system complexity vs. authoring efficiency – Extending AS w. extra adaptation rules is beneficial

if rules can express situations that were not possible (difficult) to express w. given set of tools/ rules.

– Makes sense if it doesn’t increase dramatically the types of tests an AH author has to do to verify his/her output.



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Future directions

• automatic check tools

• visual checking mechanisms, dynamical representation of processes involved; – E.g., effect of new rule on rest can be shown on

static (smaller) link graph, as a propagation of a colored fluid through graph, etc.



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Conclusion• suggested a better approach for AH authoring:

– combination of CM paradigm to construct course narrative & several new adaptation rules.

– highlighted new rules to integrate into AH authoring shell / toolkit.

• showed integration of 2 formalisms in AHA! ex. version (for more adaptivity)

We claim that this approach is another step towards flexible generic-purpose adaptive hypermedia.



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• Thank you for listening!



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Recent AHA! extensions

1. editor to connect requirements to pages;

2. editor for generate rules;

3. forms to make changes to UM: • most important: form allowing AH user to modify

knowledge attributes assoc. to page-concepts.



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System complexity vs. authoring efficiency



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Problems & need of check mechanisms

• by increasing system complexity, authoring efficiency grows for a while, and then drops. – AHA! is somewhere at beginning of slope – Adding more features & flexibilities can increase

authoring efficiency for a while, but how to stop before down-curve?

• E.g., when authors deal w. complex graphs w. many concepts & attr.s, it’s easy to leave something out by mistake.



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AHAM• tries to deal w. such pb. as:

– termination ( avoiding of loops) &

– confluence (equivalence of rule execution order)

• T: activation graphs (active DBs static analysis):– possible states graph: det. by concepts, links, attr.s, values (init.

val.s & ranges – search tree constrains optimization) & rule sets

– If graph has no loops, system will always terminate.

• C: commutation check (rule pairs order equivalence)• AHA! : only monotonic attributes (per concept) increase

termination; but: difficult in next version w. multiple attr.s • AHA! doesn’t deal w. confluence.



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Other problems

• concepts (or concept fragments) never reached;

• rules (or other adaptation mechanisms) w. attributes w. out of range (or domain) values.



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New rules

• good news: don’t require extra checking mechanisms loops in regular rules will also in level -, temporal -,

repetition rules. – Non-equivalent non-commutable rules to be executed at a

given time pose same problems on extended set. – Extended commands of generalization & specialization

can be treated the same as regular links.

– Interruption command can help in breaking infinite loops, ~ Java catch-throw mechanism of exception handling.



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New rules

• bad news: time - & space -consuming.

• better way: simplifications & complexity decreasing assumptions. – E.g., belief revision technique to check

inconsistencies in knowledge attr.s to concepts & consequent knowledge acquisition pb.



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Belief revision

• introduction of a case-based heuristics that: 1. recalls previous concept w. same features

& assoc. attributes;2. adapts course struct., via rule-based

formalism, to current learning scenario;3. resolves inconsistencies so that changes of

state are epistemologically conservative (resulting narrative is not subverted).



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Future directions

• W. standardiz. of AS building bricks (LOM, Learner model– IEEE, LTSC for education, RDF, etc.) it’s feasible to collaborate & share adaptive techniques, technologies & also system parts, AH presentations, etc.

• Adaptive & adaptable systems – are necessary in education, where learners come w. different

cultural & knowledge backgrounds, learning styles, genders, ages, (context: life-long learning).

– are definitely necessary in commerce (Amazon.com).

– can have surprising applications: adaptive literature & art.



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Conclusion: distructive• criticized widespread practice to distinguish

adaptation in hypermedia between adaptive navigation support & adaptive presentation because:

• AH authors have to artificially separate links from concepts but still coordinate them to provide a conceptually valid adaptation that contributes to a significant knowledge acquisition.

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faculty of mathematics and informatics TU/e eindhoven university of technology 1 Towards Generic Adaptive Systems: Analysis of a Case Study Licia Calvi