1. LAG Alexandra I. Cristea UPB intensive course “Adaptive Hypermedia” January 2004

2. Overview: LAG 1.What is LAG 2.LAG components 3.Why LAG? 4.New adaptation rules 5.Adaptation strategies

3. What is LAG?

4. 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.pdfhttp://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 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.dochttp://wwwis.win.tue.nl/~alex/HTML/Minerva/papers/UM03-cristea- calvi-accepted.doc

5. LAG components

6. Direct adaptation Techniques Adaptation Language Adaptation Strategies

7. 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

8. Why LAG?

9. Motivation LAG Authoring with different complexity degrees (beginner authors vs. advanced) Re-usage at each level Better semantics standardization

10. New adaptation rules proposed (Adaptation Language)

11. Adaptation ‘Programming’ language level rule: IF ENOUGH( ) THEN temporal rule: WHILE DO repetition rule: FOR DO interruption command: BREAK generalization command: GENERALIZE (COND, COND 1, …, COND n ) specialization command: SPECIALIZE (COND, COND 1, …, COND n )

12. A level rule IF ENOUGH( ) THEN 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);

13. A temporal rule: action repeated as long as 1-more cond.s hold: WHILE DO 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.

14. A repetition rule: a certain (simple / composed) action repeated for a no. of times predefined by author: FOR DO describes the time this action has to last before reader can move on.

15. An interruption command: user action is interrupted & s/he is forced to undertake a different one: BREAK represents an exacerbation of traditional behavior of AHS: user is “punished” if she doesn’t stick to learning pathways provided by system.

16. 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, COND 1, …, COND n )

17. A specialization command: if concept is general, system deductively points reader to more specific instantiations: SPECIALIZE (COND, COND 1, …, COND n ) –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.

18. 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

19. Adaptation Strategies

20. Adaptive strategies for cognitive styles

21. 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 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 much 3. 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 repetitions IF 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 1 THEN {DiffLevel--; IF (AdaptLevel<5) AdaptLevel++;} }

22. 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 THEN { IF (Result1 +Result2)/2>5 AND DiffLevel 5) AdaptLevel--;} IF (Result1 +Result2)/2 1 THEN {DiffLevel--; IF (AdaptLevel<10) AdaptLevel++;}}

23. 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 THEN { IF (Result1 +Result2)/2>5 AND DiffLevel<10 THEN DiffLevel++; IF (Result1 +Result2)/2 1 THEN DiffLevel--; }

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