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Media as Levers

task      alt.medium
            support
                              performance

                          Lawrie Hunter
                       Kochi University of Technology
              http://www.core.kochi-tech.ac.jp/hunter/
Media as Levers
 The obvious approach:

 Determine              Assemble a
a framework           pattern language
  for CALL                for CALL
optimization.



What if video games were like schools?
from
Disrupting Class
Media as Levers
Taking a contrarian approach:

 Search for          Assemble a
a framework          pattern language
  for CALL           for CALL
optimization.


        Explore the notion
          ‘media levers’
Ubiquitous IT now

Physical plant limitations =>
      =>non-ubiquitous access to IT classrooms.

Yet 'virtually' every learner does have some personal access to
web and media.

Though standardization remains an obstacle,
IT uniquely affords individualization of learning activities.

Then crucial question:
How to heighten
the learner's motivation/need
to autonomously access task resources/media?
Beyond absorption

Wesch http://blip.tv/file/2615703/:

-stresses ‘meaningful’:
<Today’s IT ubiquity throws us into a pit of
meaninglessness and insignificance.>
so
<education needs to move beyond
absorption learning and critical thinking
towards developing learner creativity>.
Macro creativity or micro creativity?
Then creativity at what level, macro or micro?

Wesch stresses ‘meaningful’:
nowadays, IT ubiquity throws us into a pit of meaninglessness and insignificance.“Of
course, multiple-choice questions are an easy target for criticism, but even more sophisticated measures of
                         When you watch somebody who is
cognitive development may miss the point.

truly “in it,” somebody who has totally given themselves over
to the learning process, or if you simply imagine those moments in which you were “in it”
yourself, you immediately recognize that learning expands far beyond the mere cognitive dimension. Many of
these dimensions were mentioned in the issue precis, “such as emotional and affective dimensions, capacities for
risk-taking and uncertainty, creativity and invention,” and the list goes on. How will we assess these? I do not
have the answers, but a renewed and spirited dedication to the creation of authentic learning environments that
leverage the new media environment demands that we address it.

The new media environment provides new opportunities for us to create a community of learners with our students
seeking important and meaningful questions. Questions of the very best kind abound, and we become students
again, pursuing questions we might have never imagined, joyfully learning right along with the others. In the best
case scenario the students will leave the course, not with answers, but with more questions, and even more
importantly, the capacity to ask still more questions generated from their continual pursuit and practice of the
subjectivities we hope to inspire. This is what I have called elsewhere, “anti-teaching,” in which the focus is not
on providing answers to be memorized, but on creating a learning environment more conducive to producing the
types of questions that ask students to challenge their taken-for-granted assumptions and see their own underlying
biases.’
http://www.academiccommons.org/commons/essay/knowledgable-knowledge-able
Macro creativity or micro creativity?

Hunter: in this discussion,
         go for fascination at the micro level.
In that frame, the notion of
creativity in language learning scenarios
raises critical design issues:

       curriculum control
       learner time demand
       input/output sequencing
       input/output proportion
Design for creativity in task:
partial or overall solutions?

Task design to address critical design issues:
      curriculum control
      learner time demand
      input/output sequencing
      input/output proportion

Recently available tools such as
Cmap Tools, Yahoo Pipes and debategraph
provide partial resolutions to these design issues.
Design for creativity in task:
partial or overall solutions?

<claim>
Task-intrinsic behavioral constraints
      such as media leverage,

       along with
       content-related and structure-related constraints,

       can provide overall resolutions in macro scenarios

       while at the same time
       making tasks more effective
       in terms of motivation and available agenda.
For today, let’s go non-Weschian:
Language tasks: overall solutions at the micro level
For today, let’s go non-Weschian:
Language tasks: overall solutions at the micro level




task             same medium            performance
                    support


task              alt.medium
                    support
                                        performance

Make task support medium
different from task medium
different from performance medium
Non-Weschian question:
how to quantify ‘involvement’?

We need a bottom line: what are the markers/degrees of
‘involvement’?

Possible markers:

       Task success

       Practice performance (vs. non)

       Practice persistence

       Reported experience

       Neuro-electric
Task design discourse
-articulating what is usually implicit

We need a ‘pattern language’:

A designer way for talking about processing, task shaping,
involvement, media leverage.
Task design discourse
     Tools                              www.patternlanguage.com


                      A pattern language?
Target behavior
 …The language, and the processes which stem from it,
 merely release the fundamental order which is native to us.
 They do not teach us, they only remind us of what we know
 already, and of what we shall discover time and time again,
 when we give up our ideas and opinions, and do exactly
 what emerges from ourselves.
                                 Christopher Alexander,
                           The Timeless Way of Building
Task design discourse
  Tools                 www.patternlanguage.com


            A pattern language?
Target behavior

    Pattern language emerges from practice:
                     look at some examples first =>
Media lever example 1:
Task: learners are to prepare for a challenge where they must write sentences to describe
the information embodied in any one of a set of line graphs with discrete data points.
       INPUT                       LEVER                              OUTPUT




     line graph                   audio file                         writing task

Media lever: provision of web- and mobile-accessible sound files containing 'answers’,
i.e. model language for the powerpoint set of graphs being studied.

Observations:
In class practice sessions were lackadaisical and slow/stopped.
~70% of students did report accessing the web files in their own time.
~30% of those transcribed the speech.
Frequent mention of having enjoyed the challenged of matching the unnumbered sound
files to the numbered powerpoint graphs.
Media lever example 1 – clever extensions
Task: learners are to prepare for a challenge where they must write sentences to describe
the information embodied in any one of a set of line graphs with discrete data points.

Media lever 1: make sound files available on the web, each file containing the utterance
for one graph in the flashcard set. Listening is foregrounded.
Media lever 2: put the sound files, unlabeled, in random order on the web. Learners
must match the sound files to the graph slides. Both listening and graph decoding are
foregrounded. Higher cognitive load.
Media lever 3: provide sound files for only some of the graph slides. Both listening and
graph decoding are foregrounded, and decision-making and pattern application are
forced. Even higher cognitive load.
Media lever 4: make the graphs similar in content. Listening is foregrounded. Make the
graphs dissimilar in content. Analytical process if foregrounded.
Media lever example 1 power variation 1:
Task: learners are to prepare for a challenge where they must write sentences to describe
the information embodied in any one of a set of line graphs with discrete data points.
                INPUT                       LEVER                        OUTPUT




1                               3
    2                               2                            4
        3                               5                            1
            4                               1                            2
                5                               4
                                                                     3 writing tasks
                5 line graphs
                                            5 audio files               (jumbled)

                                             (jumbled)


Media lever: provision of web- and mobile-accessible sound files containing 'answers’
but in jumbled order. Learners must match sound levers to task inputs.
Media lever example 1 power variation 2:
Task: learners are to prepare for a challenge where they must write sentences to describe
the information embodied in any one of a set of line graphs with discrete data points.
                INPUT                   LEVER                                OUTPUT




1
    2                           4                                1
        3                           1                                2
            4                           2                                3
                5                                                            4
                                                                        5
                                        3 audio files                 5 writing tasks
                5 line graphs
                                                                     (original order)
                                         (jumbled)



Media lever: provision of web- and mobile-accessible sound files containing 'answers’
to only some tasks. Learners must match sound levers to task inputs, and must transfer
the training to the remaining unleveraged tasks.
Conscious threshold
Remembering that
media levers’ power lies below the conscious threshold.

Remembering that the learner should be placed in executive role as much
as possible – or at least feel situated there.

Atmosphere change => attitude change
Conscious threshold
Example:
rikai.com's web page mouseover reading tool:
compared to a JEJ dictionary,
completely different atmosphere.




 Results: completely different
 text attack attitude.
 L2 Nihongo learners have responded
 ecstatically to discovery of this tool.

 Analysis: Asked to analyze their response,
 the learners gave signs of not having thought
 analytically about the tool.
Media lever example 2:
Task perception: at times
it is motivating to provide
a 'distractor task' so as to
background the actual task.

          Low-tech example*:




Task: in a textbook, learners are to copy the sentences from the left hand
page and adapt them to express the data given on the right hand page
(information substitution) (appealing).
Writing and calculation are foregrounded, reading backgrounded.

Covert task: read the left hand page (unappealing).


                               *don’t forget: not all media are electronic
Media lever example 3:
Task: learners are presented with a mystery,
embodied in a ‘scene of the crime’ drawing.
Learners are to do abduction:
find a believable explanation
for all the evidence in the graphic.
Media lever example 3:
Task: learners are presented with a mystery,
embodied in a ‘scene of the crime’ drawing.
Learners are to do abduction:
find a believable explanation
for all the evidence in the graphic.

Obvious procedure:
brainstorm in L1; compose in L2.

Media lever:
learners receive pages of
'fodder’ model sentences
for composition within
the problem solving task.

Outcome:
hint searching is foregrounded;
reading is backgrounded.
Media lever example 3 variation 1:
Task: learners are presented with a mystery,
embodied in a ‘scene of the crime’ drawing.
Learners are to do abduction:
find a believable explanation
for all the evidence in the graphic.

Media lever 3.1:
give the fodder in text
when the task is introduced.

Outcome: the reading of the fodder
is foregrounded,
as a source of problem solving help.
Media lever example 3 variation 2:
Task: learners are presented with a mystery,
embodied in a ‘scene of the crime’ drawing.
Learners are to do abduction:
find a believable explanation
for all the evidence in the graphic.

Media lever 3.2:
give the fodder after the students
have developed solutions.

Outcome: problem solving is foregrounded,
and the fodder becomes the matrix
for a search for L2 versions
of what they want to say.
Media lever example 3 variation 3:
Task: learners are presented with a mystery,
embodied in a ‘scene of the crime’ drawing.
Learners are to do abduction:
find a believable explanation
for all the evidence in the graphic.

Media lever 3.3:
make the fodder available as
sound files linked from objects
in the problem picture

Outcome: listening is foregrounded
and cognitive load reduced.
Media lever example 3 variation 4:
Task: learners are presented with a mystery,
embodied in a ‘scene of the crime’ drawing.
Learners are to do abduction:
find a believable explanation
for all the evidence in the graphic.

Media lever 4:
make the fodder long audio files
of whole solutions.

Outcome:
problem solving is backgrounded,
listening is foregrounded
and cognitive load reduced.
Media levers point to:

The need for a framework for cognitive task design work.

The need for a pattern language for professional deliberation.
CALL cognitive task design work
Designer NEEDS



                     A pattern language?
                             www.patternlanguage.com
Designer WANTS
…The language, and the processes which stem from it,
merely release the fundamental order which is native to us.
They do not teach us, they only remind us of what we know
already, and of what we shall discover time and time again,
when we give up our ideas and opinions, and do exactly
what emerges from ourselves.
                                Christopher Alexander,
                          The Timeless Way of Building
Tensions (to germinate pattern language)
 Typical tensions in CALL work

 Learner – PC
 Learner – software
 Learner – target content
 Learner – interface
 Instructor intervention – learner performance
 Content presentation style – learner performance
 Ubiquity – learner motivation
Tensions (to germinate pattern language)
 Hunter's tensions of interest
 Interface/task – learner perception of curriculum
 Representation – message comprehension
 Processing type – learner persistence
 Processing variation – learning effectiveness/efficiency
 Use of metalanguage – learner attack style
 Representation type – cognitive load in task scenario
 Representation type – degree of abstraction
                              – curriculum transparency
 Representation type – degree of abstraction
                                      – task success
Tensions (to germinate pattern language)
 Hunter's tensions of interest
 Interface/task – learner perception of curriculum
 Representation – message comprehension
 Processing type – learner persistence
 Processing variation – learning effectiveness/efficiency
 Use of metalanguage – learner attack style
 Representation type – cognitive load in task scenario
 Representation type – degree of abstraction
                              – curriculum transparency
 Representation type – degree of abstraction
                                      – task success
“Processing”: a pattern language element
                          L2 processing

Information processing    Language -> information
                          identify sounds/words/phrases
Recognize symbols         find L1 equivalent
Identify a pattern        find mental construct equivalent
Identify a problem        identify anaphora/exophora
Select a transformation   identify discourse pattern
Select a technique        identify discourse intent
Apply a technique
Evaluate results          Information -> language
                          mimic sounds/symbols
                          create sounds/symbols
                          encode visual impressions
                          encode discourse impressions
                          encode text impressions
                          build discourse from intention
“Processing” types

                   PROCESSING
                   TYPES

                   Remembering
                                                            OUTPUT TASKS
 INPUT TASKS       Accumulating
                   Transforming
                                                                Pointing
   Listening       Naming
                                                                Moving
    Looking        Describing
   Watching        Classifying
                                                             Making a noise
Reading a symbol   Comparing
                                                               Speaking
  Reading text     Finding an answer to a question
                   Selecting an answer to a question
                                                               Drawing
     Feeling       Applying a rule
                                                               Writing
    Smelling       Describing a rule
                                                               Making
    Tasting        Discovering a rule
                   Sequencing
                   Applying a process    By carefully monitoring the modes
                   Inferring
                   Analyzing
                                                   of task input and output,
                   Synthesizing          the designer can lead the learner to
                   Evaluating
                   Deciding            a wide variety of cognitive activities
                                                         (here "processing").
“Processing” immediacy and presence
                         Immediate processing

              Tests
                                           Dictation          Conversation
            for points
                                                       Chat



                                                        Classroom
                     Classroom                          questioning
                    paper tasks
 Minimum                                                               Maximum
 presence                 Point n’ click
                                              SMS                      presence
                                              chat
                    Drag n’ drop           email
                                            chat


                                                   Cell phone
                                                      push
            Homework




                         Delayable processing
Pro-con
Cause-effect
Classification
  Description


   Sequence
 Comparison


   Inference
                 Remembering
                 Accumulating
                 Transforming
                 Naming
                 Describing
                 Classifying
                                              to decide task type




                 Comparing
                 Finding an answer to a question
                 Selecting an answer to a question
                 Applying a rule
                 Describing a rule
                 Discovering a rule
                 Sequencing
                 Applying a process
                 Inferring
                                              Merging content and processing




                 Analyzing
                 Synthesizing
                 Evaluating
                 Deciding
Sequencing of tasks
                                            Remembering
                                            Accumulating
                                            Transforming
 Sample 1: False beginners
 (repeating same content in each task)      Naming
                                            Describing
 Aural only                                 Classifying
 A1:listen and   repeat                     Comparing
 A2-listen and   repeat cumulative          Finding an answer to a question
 A3-listen and   draw/signify graphically
                                            Selecting an answer to a question
 A4-listen and   complete pattern clozes
                                            Applying a rule
 A5-listen and   problem-solve
                                            Describing a rule

 Read/write                                 Discovering a rule

 W1-reverse of A3                           Sequencing
 W2-A4 with no listening                    Applying a process
 W3-Read cases and discover rules           Inferring
 W4-Read cases and draw scenarios           Analyzing
 W5-Read cases and solve problems           Synthesizing
                                            Evaluating
                                            Deciding
An essential pattern language element:
Baddeley and Hitch’s
1986 model of working memory,
with its 3 components.
 Three-component model of working
memory
-assumes an attentional controller, the
central executive, aided by two
subsidiary systems:

1. the phonological loop, capable of
holding speech-based information, and

2.the visuospatial sketchpad, which
performs a similar function for visual
information.

The two subsidiary systems form active
stores that are capable of combining
information from sensory input, and from
the central executive. Hence a memory
trace in the phonological store might
stem either from a direct auditory input,
or from the subvocal articulation of a
visually presented item such as a letter.
Working memory model extended (2000)

Phonological loop:                                                                  Central
                                                                                   Executive
Important for short-term storage
-ALSO for long term phonological learning
                                                      Phonological                             Visuo-spatial
                                                         Loop                                   Sketchpad

                                                         Visual                  Episodic         Language
                                                       semantics                  LTM
Associated with
-development of vocabulary in children
-speed of FLA in adults


         Baddeley, A. D. (2000) The episodic buffer: a new component of working memory?
         Trends in cognitive sciences 4(11) 417-423.
Working memory model extended (2000)

Phonological loop effects:                                                           Central
                                                                                    Executive
1.   Phonological similarity
2.   Word-length
3.   Articulatory suppression
                                                       Phonological                             Visuo-spatial
4.   Code transfer                                        Loop                                   Sketchpad
5.   Central rehearsal code,
         not operation                                    Visual                  Episodic         Language
                                                        semantics                  LTM




          Baddeley, A. D. (2000) The episodic buffer: a new component of working memory?
          Trends in cognitive sciences 4(11) 417-423.
A most promising task design tool:

Baddeley’s model of working memory,
                                                                               Central
                                                                              Executive
with its (since 2000) 4 components.

The episodic buffer:
-assumed capable of storing infor-              Phonological                   Episodic      Visuo-spatial
mation in a multi-dimensional
                                                   Loop                         Buffer        Sketchpad
code.
-thus provides a temporary
interface between the slave                            Visual                Episodic
systems and LTM.                                     semantics                LTM              Language
-assumed to be controlled by the
central executive                               Shaded areas: ‘crystallized’ cognitive systems
-serves as a modelling space that               capable of accumulating long-term knowledge
is separate from LTM, but which
forms an important stage in                     Unshaded areas: ‘fluid’ capacities (such as
longterm episodic learning.                     attention and temporary storage), themselves
                                                unchanged by learning.
            Baddeley, A. D. (2000) The episodic buffer: a new component of working memory?
            Trends in cognitive sciences 4(11) 417-423.
Shall we compose
a pattern language for CALL?
   ...a promising notion


…The language, and the processes which stem from it,
merely release the fundamental order which is native to us.
They do not teach us, they only remind us of what we know
already, and of what we shall discover time and time again,
when we give up our ideas and opinions, and do exactly
what emerges from ourselves.
                                Christopher Alexander,
                          The Timeless Way of Building
Thanks for your attention.

Downloads from
http://lawriehunter.com/presns/tw4/
http://www.core.kochi-tech.ac.jp/hunter/
http://slideshare.net/rolenzo/

Contact (please)

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Media as Levers (pdf)

  • 1. Media as Levers task alt.medium support performance Lawrie Hunter Kochi University of Technology http://www.core.kochi-tech.ac.jp/hunter/
  • 2. Media as Levers The obvious approach: Determine Assemble a a framework pattern language for CALL for CALL optimization. What if video games were like schools? from Disrupting Class
  • 3. Media as Levers Taking a contrarian approach: Search for Assemble a a framework pattern language for CALL for CALL optimization. Explore the notion ‘media levers’
  • 4. Ubiquitous IT now Physical plant limitations => =>non-ubiquitous access to IT classrooms. Yet 'virtually' every learner does have some personal access to web and media. Though standardization remains an obstacle, IT uniquely affords individualization of learning activities. Then crucial question: How to heighten the learner's motivation/need to autonomously access task resources/media?
  • 5. Beyond absorption Wesch http://blip.tv/file/2615703/: -stresses ‘meaningful’: <Today’s IT ubiquity throws us into a pit of meaninglessness and insignificance.> so <education needs to move beyond absorption learning and critical thinking towards developing learner creativity>.
  • 6. Macro creativity or micro creativity? Then creativity at what level, macro or micro? Wesch stresses ‘meaningful’: nowadays, IT ubiquity throws us into a pit of meaninglessness and insignificance.“Of course, multiple-choice questions are an easy target for criticism, but even more sophisticated measures of When you watch somebody who is cognitive development may miss the point. truly “in it,” somebody who has totally given themselves over to the learning process, or if you simply imagine those moments in which you were “in it” yourself, you immediately recognize that learning expands far beyond the mere cognitive dimension. Many of these dimensions were mentioned in the issue precis, “such as emotional and affective dimensions, capacities for risk-taking and uncertainty, creativity and invention,” and the list goes on. How will we assess these? I do not have the answers, but a renewed and spirited dedication to the creation of authentic learning environments that leverage the new media environment demands that we address it. The new media environment provides new opportunities for us to create a community of learners with our students seeking important and meaningful questions. Questions of the very best kind abound, and we become students again, pursuing questions we might have never imagined, joyfully learning right along with the others. In the best case scenario the students will leave the course, not with answers, but with more questions, and even more importantly, the capacity to ask still more questions generated from their continual pursuit and practice of the subjectivities we hope to inspire. This is what I have called elsewhere, “anti-teaching,” in which the focus is not on providing answers to be memorized, but on creating a learning environment more conducive to producing the types of questions that ask students to challenge their taken-for-granted assumptions and see their own underlying biases.’ http://www.academiccommons.org/commons/essay/knowledgable-knowledge-able
  • 7. Macro creativity or micro creativity? Hunter: in this discussion, go for fascination at the micro level. In that frame, the notion of creativity in language learning scenarios raises critical design issues: curriculum control learner time demand input/output sequencing input/output proportion
  • 8. Design for creativity in task: partial or overall solutions? Task design to address critical design issues: curriculum control learner time demand input/output sequencing input/output proportion Recently available tools such as Cmap Tools, Yahoo Pipes and debategraph provide partial resolutions to these design issues.
  • 9. Design for creativity in task: partial or overall solutions? <claim> Task-intrinsic behavioral constraints such as media leverage, along with content-related and structure-related constraints, can provide overall resolutions in macro scenarios while at the same time making tasks more effective in terms of motivation and available agenda.
  • 10. For today, let’s go non-Weschian: Language tasks: overall solutions at the micro level
  • 11. For today, let’s go non-Weschian: Language tasks: overall solutions at the micro level task same medium performance support task alt.medium support performance Make task support medium different from task medium different from performance medium
  • 12. Non-Weschian question: how to quantify ‘involvement’? We need a bottom line: what are the markers/degrees of ‘involvement’? Possible markers: Task success Practice performance (vs. non) Practice persistence Reported experience Neuro-electric
  • 13. Task design discourse -articulating what is usually implicit We need a ‘pattern language’: A designer way for talking about processing, task shaping, involvement, media leverage.
  • 14. Task design discourse Tools www.patternlanguage.com A pattern language? Target behavior …The language, and the processes which stem from it, merely release the fundamental order which is native to us. They do not teach us, they only remind us of what we know already, and of what we shall discover time and time again, when we give up our ideas and opinions, and do exactly what emerges from ourselves. Christopher Alexander, The Timeless Way of Building
  • 15. Task design discourse Tools www.patternlanguage.com A pattern language? Target behavior Pattern language emerges from practice: look at some examples first =>
  • 16. Media lever example 1: Task: learners are to prepare for a challenge where they must write sentences to describe the information embodied in any one of a set of line graphs with discrete data points. INPUT LEVER OUTPUT line graph audio file writing task Media lever: provision of web- and mobile-accessible sound files containing 'answers’, i.e. model language for the powerpoint set of graphs being studied. Observations: In class practice sessions were lackadaisical and slow/stopped. ~70% of students did report accessing the web files in their own time. ~30% of those transcribed the speech. Frequent mention of having enjoyed the challenged of matching the unnumbered sound files to the numbered powerpoint graphs.
  • 17. Media lever example 1 – clever extensions Task: learners are to prepare for a challenge where they must write sentences to describe the information embodied in any one of a set of line graphs with discrete data points. Media lever 1: make sound files available on the web, each file containing the utterance for one graph in the flashcard set. Listening is foregrounded. Media lever 2: put the sound files, unlabeled, in random order on the web. Learners must match the sound files to the graph slides. Both listening and graph decoding are foregrounded. Higher cognitive load. Media lever 3: provide sound files for only some of the graph slides. Both listening and graph decoding are foregrounded, and decision-making and pattern application are forced. Even higher cognitive load. Media lever 4: make the graphs similar in content. Listening is foregrounded. Make the graphs dissimilar in content. Analytical process if foregrounded.
  • 18. Media lever example 1 power variation 1: Task: learners are to prepare for a challenge where they must write sentences to describe the information embodied in any one of a set of line graphs with discrete data points. INPUT LEVER OUTPUT 1 3 2 2 4 3 5 1 4 1 2 5 4 3 writing tasks 5 line graphs 5 audio files (jumbled) (jumbled) Media lever: provision of web- and mobile-accessible sound files containing 'answers’ but in jumbled order. Learners must match sound levers to task inputs.
  • 19. Media lever example 1 power variation 2: Task: learners are to prepare for a challenge where they must write sentences to describe the information embodied in any one of a set of line graphs with discrete data points. INPUT LEVER OUTPUT 1 2 4 1 3 1 2 4 2 3 5 4 5 3 audio files 5 writing tasks 5 line graphs (original order) (jumbled) Media lever: provision of web- and mobile-accessible sound files containing 'answers’ to only some tasks. Learners must match sound levers to task inputs, and must transfer the training to the remaining unleveraged tasks.
  • 20. Conscious threshold Remembering that media levers’ power lies below the conscious threshold. Remembering that the learner should be placed in executive role as much as possible – or at least feel situated there. Atmosphere change => attitude change
  • 21. Conscious threshold Example: rikai.com's web page mouseover reading tool: compared to a JEJ dictionary, completely different atmosphere. Results: completely different text attack attitude. L2 Nihongo learners have responded ecstatically to discovery of this tool. Analysis: Asked to analyze their response, the learners gave signs of not having thought analytically about the tool.
  • 22. Media lever example 2: Task perception: at times it is motivating to provide a 'distractor task' so as to background the actual task. Low-tech example*: Task: in a textbook, learners are to copy the sentences from the left hand page and adapt them to express the data given on the right hand page (information substitution) (appealing). Writing and calculation are foregrounded, reading backgrounded. Covert task: read the left hand page (unappealing). *don’t forget: not all media are electronic
  • 23. Media lever example 3: Task: learners are presented with a mystery, embodied in a ‘scene of the crime’ drawing. Learners are to do abduction: find a believable explanation for all the evidence in the graphic.
  • 24. Media lever example 3: Task: learners are presented with a mystery, embodied in a ‘scene of the crime’ drawing. Learners are to do abduction: find a believable explanation for all the evidence in the graphic. Obvious procedure: brainstorm in L1; compose in L2. Media lever: learners receive pages of 'fodder’ model sentences for composition within the problem solving task. Outcome: hint searching is foregrounded; reading is backgrounded.
  • 25. Media lever example 3 variation 1: Task: learners are presented with a mystery, embodied in a ‘scene of the crime’ drawing. Learners are to do abduction: find a believable explanation for all the evidence in the graphic. Media lever 3.1: give the fodder in text when the task is introduced. Outcome: the reading of the fodder is foregrounded, as a source of problem solving help.
  • 26. Media lever example 3 variation 2: Task: learners are presented with a mystery, embodied in a ‘scene of the crime’ drawing. Learners are to do abduction: find a believable explanation for all the evidence in the graphic. Media lever 3.2: give the fodder after the students have developed solutions. Outcome: problem solving is foregrounded, and the fodder becomes the matrix for a search for L2 versions of what they want to say.
  • 27. Media lever example 3 variation 3: Task: learners are presented with a mystery, embodied in a ‘scene of the crime’ drawing. Learners are to do abduction: find a believable explanation for all the evidence in the graphic. Media lever 3.3: make the fodder available as sound files linked from objects in the problem picture Outcome: listening is foregrounded and cognitive load reduced.
  • 28. Media lever example 3 variation 4: Task: learners are presented with a mystery, embodied in a ‘scene of the crime’ drawing. Learners are to do abduction: find a believable explanation for all the evidence in the graphic. Media lever 4: make the fodder long audio files of whole solutions. Outcome: problem solving is backgrounded, listening is foregrounded and cognitive load reduced.
  • 29. Media levers point to: The need for a framework for cognitive task design work. The need for a pattern language for professional deliberation.
  • 30. CALL cognitive task design work Designer NEEDS A pattern language? www.patternlanguage.com Designer WANTS …The language, and the processes which stem from it, merely release the fundamental order which is native to us. They do not teach us, they only remind us of what we know already, and of what we shall discover time and time again, when we give up our ideas and opinions, and do exactly what emerges from ourselves. Christopher Alexander, The Timeless Way of Building
  • 31. Tensions (to germinate pattern language) Typical tensions in CALL work Learner – PC Learner – software Learner – target content Learner – interface Instructor intervention – learner performance Content presentation style – learner performance Ubiquity – learner motivation
  • 32. Tensions (to germinate pattern language) Hunter's tensions of interest Interface/task – learner perception of curriculum Representation – message comprehension Processing type – learner persistence Processing variation – learning effectiveness/efficiency Use of metalanguage – learner attack style Representation type – cognitive load in task scenario Representation type – degree of abstraction – curriculum transparency Representation type – degree of abstraction – task success
  • 33. Tensions (to germinate pattern language) Hunter's tensions of interest Interface/task – learner perception of curriculum Representation – message comprehension Processing type – learner persistence Processing variation – learning effectiveness/efficiency Use of metalanguage – learner attack style Representation type – cognitive load in task scenario Representation type – degree of abstraction – curriculum transparency Representation type – degree of abstraction – task success
  • 34. “Processing”: a pattern language element L2 processing Information processing Language -> information identify sounds/words/phrases Recognize symbols find L1 equivalent Identify a pattern find mental construct equivalent Identify a problem identify anaphora/exophora Select a transformation identify discourse pattern Select a technique identify discourse intent Apply a technique Evaluate results Information -> language mimic sounds/symbols create sounds/symbols encode visual impressions encode discourse impressions encode text impressions build discourse from intention
  • 35. “Processing” types PROCESSING TYPES Remembering OUTPUT TASKS INPUT TASKS Accumulating Transforming Pointing Listening Naming Moving Looking Describing Watching Classifying Making a noise Reading a symbol Comparing Speaking Reading text Finding an answer to a question Selecting an answer to a question Drawing Feeling Applying a rule Writing Smelling Describing a rule Making Tasting Discovering a rule Sequencing Applying a process By carefully monitoring the modes Inferring Analyzing of task input and output, Synthesizing the designer can lead the learner to Evaluating Deciding a wide variety of cognitive activities (here "processing").
  • 36. “Processing” immediacy and presence Immediate processing Tests Dictation Conversation for points Chat Classroom Classroom questioning paper tasks Minimum Maximum presence Point n’ click SMS presence chat Drag n’ drop email chat Cell phone push Homework Delayable processing
  • 37. Pro-con Cause-effect Classification Description Sequence Comparison Inference Remembering Accumulating Transforming Naming Describing Classifying to decide task type Comparing Finding an answer to a question Selecting an answer to a question Applying a rule Describing a rule Discovering a rule Sequencing Applying a process Inferring Merging content and processing Analyzing Synthesizing Evaluating Deciding
  • 38. Sequencing of tasks Remembering Accumulating Transforming Sample 1: False beginners (repeating same content in each task) Naming Describing Aural only Classifying A1:listen and repeat Comparing A2-listen and repeat cumulative Finding an answer to a question A3-listen and draw/signify graphically Selecting an answer to a question A4-listen and complete pattern clozes Applying a rule A5-listen and problem-solve Describing a rule Read/write Discovering a rule W1-reverse of A3 Sequencing W2-A4 with no listening Applying a process W3-Read cases and discover rules Inferring W4-Read cases and draw scenarios Analyzing W5-Read cases and solve problems Synthesizing Evaluating Deciding
  • 39. An essential pattern language element: Baddeley and Hitch’s 1986 model of working memory, with its 3 components. Three-component model of working memory -assumes an attentional controller, the central executive, aided by two subsidiary systems: 1. the phonological loop, capable of holding speech-based information, and 2.the visuospatial sketchpad, which performs a similar function for visual information. The two subsidiary systems form active stores that are capable of combining information from sensory input, and from the central executive. Hence a memory trace in the phonological store might stem either from a direct auditory input, or from the subvocal articulation of a visually presented item such as a letter.
  • 40. Working memory model extended (2000) Phonological loop: Central Executive Important for short-term storage -ALSO for long term phonological learning Phonological Visuo-spatial Loop Sketchpad Visual Episodic Language semantics LTM Associated with -development of vocabulary in children -speed of FLA in adults Baddeley, A. D. (2000) The episodic buffer: a new component of working memory? Trends in cognitive sciences 4(11) 417-423.
  • 41. Working memory model extended (2000) Phonological loop effects: Central Executive 1. Phonological similarity 2. Word-length 3. Articulatory suppression Phonological Visuo-spatial 4. Code transfer Loop Sketchpad 5. Central rehearsal code, not operation Visual Episodic Language semantics LTM Baddeley, A. D. (2000) The episodic buffer: a new component of working memory? Trends in cognitive sciences 4(11) 417-423.
  • 42. A most promising task design tool: Baddeley’s model of working memory, Central Executive with its (since 2000) 4 components. The episodic buffer: -assumed capable of storing infor- Phonological Episodic Visuo-spatial mation in a multi-dimensional Loop Buffer Sketchpad code. -thus provides a temporary interface between the slave Visual Episodic systems and LTM. semantics LTM Language -assumed to be controlled by the central executive Shaded areas: ‘crystallized’ cognitive systems -serves as a modelling space that capable of accumulating long-term knowledge is separate from LTM, but which forms an important stage in Unshaded areas: ‘fluid’ capacities (such as longterm episodic learning. attention and temporary storage), themselves unchanged by learning. Baddeley, A. D. (2000) The episodic buffer: a new component of working memory? Trends in cognitive sciences 4(11) 417-423.
  • 43. Shall we compose a pattern language for CALL? ...a promising notion …The language, and the processes which stem from it, merely release the fundamental order which is native to us. They do not teach us, they only remind us of what we know already, and of what we shall discover time and time again, when we give up our ideas and opinions, and do exactly what emerges from ourselves. Christopher Alexander, The Timeless Way of Building
  • 44. Thanks for your attention. Downloads from http://lawriehunter.com/presns/tw4/ http://www.core.kochi-tech.ac.jp/hunter/ http://slideshare.net/rolenzo/ Contact (please)