Semiotic Integration: Information Structure Maps

1. Semiotic Integration:Information Structure Maps Lawrie Hunter Kochi University of Technology http://www.core.kochi-tech.ac.jp/hunter/ lawrie_hunter@kochi-tech.ac.jp

2. Semiotic Integration:Information Structure Maps Lawrie Hunter Kochi University of Technology http://www.core.kochi-tech.ac.jp/hunter/ lawrie_hunter@kochi-tech.ac.jp

3. Claim: Information maps, with textured links that represent information relationships, are a ‘good enough’ mapping of information structures in language and as such can enhance L2 performance and reduce cognitive load even in L1.

4. Claim: Information maps, with textured links that represent information relationships, are a ‘good enough’ mapping of information structures in language and as such can enhance L2 performance and reduce cognitive load even in L1. Next step: Incorporate links in e-document design as an alternative/adjunct to menus.

5. Principle 1: • content, and philosophy about content, must come FIRST

6. Mass amateurisation of everything: “...over the last fifteen years or so pretty much all media creation has started to be deprofessionalised.” http://www.plasticbag.org/archives/2003/09/ weblogs_and_the_mass_amateurisation_of_nearly_everything.shtml

7. Principle 1: • content, and philosophy about content, must come FIRST content task design materials design content philosophy

8. Principle 1: • content, and philosophy about content, must come FIRST AKA “Tell me later what your computer can do.” content task design materials design content philosophy

9. Institution design Societal demands Learner needs CALL scenario design flowchart Hunter (2001) http://www.core.kochi-tech.ac.jp/hunter/CALLL/ Learning theory Curriculum policy Objectives and Content domains Unsupervised (tutor) Teaching practice Learner character- ization Learner characterization Virtual lab: www (distance ed) Supervised (semi-tool) Methodologies and Content CMC-based CALL vs. Intelligent CALL (tool vs tutor) Multi-lab High software Learner character- ization content domains budgets software scenario Classroom IT LL Low software High authoring CALL lab Low software High teaching

10. Principle 2: • Learning language is learning a set of behaviors

11. Principle 2: • Learning language is learning a set of behaviors • These behaviors may be said to be rule-driven.

12. Principle 2: • Learning language is learning a set of behaviors • These behaviors may be said to be rule-driven. • But what are the rules?

13. Principle 2: • Learning language is learning a set of behaviors • These behaviors may be said to be rule-driven. • But what are the rules? • A number of grammars attempt to impose rules on the whole of language.

14. However, language came before the rules. • This is why the lexical approach is proving so interesting.

15. Similarly, information came before the idea of information system. • This is why learning objects are not well known to educators.

16. PRINCIPLE 3: Learners need to have a clear situating of what they are doing. • This calls for a simple, structured characterization of language and communication.

17. So how can we characterize what we as language teachers are doing?

18. In my work, I use GENRES, REGISTERS and MOVES. So how can we characterize what we as language teachers are doing?

19. hunter’s tools GENRES REGISTERS MOVES [a classification map]

20. hunter’s tools GENRES REGISTERS MOVES Genres allow us to talk about the type of information conveyed in any given utterance. This is the starting point for the L2 learner.

21. hunter’s tools GENRES REGISTERS MOVES Systemic Functional Linguistics SFL talks about these genres: • Narrative: construct a pattern of events • Procedure: tell how to do something • Information report: present information • Explanation: tell how and why things occur • Exposition: argue a case • Discussion: look at sides of an issue

22. hunter’s tools GENRES REGISTERS MOVES KUT’s genres At KUT, we have built our curriculum around these genres: • Description • Classification • Comparison • Sequence • Cause-effect (including inference) • Pro-con

23. KUT’s genres Critical Thinking Asahi Press 2001 2nd year textbook 6 units (6 genres) in 2 quarters Thinking in English KUT Press 2004 A mapping workbook, companion to CT 6 units (6 genres) Extends CT to 4 quarters

24. KUT’s genres Textbooks as paper prototyping

25. hunter’s tools GENRES REGISTERS MOVES KUT’s genres ... reflect information types (Mohan's (1986) knowledge structures) rather than speech act types such as SFL's text types. This allows us to use Hunter's information mapping as the graphic embodiment of what we are hearing/saying/reading/writing.

26. Hunter’s infomap links

27. Hunter’s infomap links Description

28. Hunter’s infomap links Classification Description

29. Hunter’s infomap links Classification Description Degree comparison < big

30. Hunter’s infomap links Classification Description Degree comparison Attribute comparison < big

31. Hunter’s infomap links Classification Description Degree comparison Attribute comparison < big Contrast !

32. Hunter’s infomap links Classification Description Degree comparison Attribute comparison < big Contrast ! Sequence

33. < big Hunter’s infomap links Classification Description Degree comparison Attribute comparison Contrast ! Sequence Cause-effect

34. please study here

35. hunter’s tools GENRES REGISTERS MOVES Hunter’sREGISTERS allow a separation of language domains according to intention and situation

36. hunter’s tools GENRES REGISTERS MOVES Hunter’s REGISTERS • Here are the ad hoc (but definable) registers I talk about with my students:

37. hunter’s tools GENRES REGISTERS MOVES Hunter’s REGISTERS The registers of the non-technical world • Casual • Informal • Formal The registers of the technical world. • Casual technical • used in discussion of technical matters with engineer peers • Informal academic (used in presentations) • Formal academic (used in research papers and theses)

38. hunter’s tools GENRES REGISTERS MOVES Hunter’s REGISTERS The registers of the non-technical world • Casual • Informal • Formal The registers of the technical world. • Casual technical • used in discussion of technical matters with engineer peers • Informal academic (used in presentations) • Formal academic (used in research papers and theses)

39. hunter’s tools GENRES REGISTERS MOVES MOVES MOVES are characterizations of the purpose of a given utterance.

40. hunter’s tools GENRES REGISTERS MOVES In Hunter's graduate technical writing course, MOVES include: • Attributing (a statement to a source, including other researcher, common knowledge...). • Identifying an example/archetype. • Generalizing • Summarizing • Reporting • Inferring • Claiming • Demonstrating • Establishing • Proving • Deducing • Predicting • Concluding

41. hunter’s tools GENRES REGISTERS MOVES

42. This presentation’s focus: integrating information symbolsfor iconic representation To support the second language reader, our information representation should be: -unambiguous -specific (granular enough) -non-fuzzy - iconic if possible

43. Question:Do Hunter’s infomap linkshave iconic status?

44. hunter’s tools: iconic? granular enough? sufficient coverage? Question:Do Hunter’s infomap linkshave iconic status? i.e.Are they granular enough, and is their mapping coverage sufficient to constitute a pattern language?

45. other systems: iconic? granular enough? sufficient coverage? Butaren’t there already mapping systems whose links have iconic status?

46. other systems: iconic? granular enough? sufficient coverage? Butaren’t there already mapping systems whose links have iconic status? How about Mind mapping? Wurman’s LATCH? Reason.able’s argument mapping? “International” signage? Rhetorical structure theory maps

47. Buzan: iconic? granular enough? sufficient coverage? Tony Buzan’s mind mapping? Not iconic: -the links are all associations -i.e. zero granularity

48. Wurman: iconic? granular enough? sufficient coverage? R.S. Wurman’s LATCH? Wurman says there are just five ways to organize information: by location, alphabet, time, category, or hierarchy. These methods can be remembered by the acronym LATCH. Roads, towns, and bodies of water are best organized by LOCATION. Dictionaries, encyclopedias, and many collections of data, by ALPHABET. Museum exhibits and planning documents, by TIMEline. Department stores and Yellow Pages, by CATEGORY. And physical objects, by HIERARCHY -- from the largest to the smallest, from the densest to the least dense. Arguably, LATCH is not a mapping. LATCH is also short on coverage. e.g. where is cause => effect here?

49. Reason!able: iconic? granular enough? sufficient coverage? Reason!able argument mapping? Reason!able makes software for mapping arguments. This design surpasses Horn’s Argument Mapping in granularity: the links are labeled to indicate the rhetorical device represented by the link. www.goreason.com But a text label cannot achieve iconic status.

50. RST(rhetorical structure theory) mapping? RST: iconic? granular enough? sufficient coverage? Bill Mann’s Rhetorical Structure Theory (RST) uses various sorts of "building blocks" to describe texts. The principal block type deals with "nuclearity" and "relations" (often called coherence relations in the linguistic literature.) www.sil.org/~mannb/rst/