Into the Pedagogical Woods

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Into the Pedagogical Woods

• David Wiley, Ph.D.
• Dept. of Instructional Technology
• Utah State University

2
Overview

• LODAS
• Scope / grain size
• Sequence / combination
• OSOSS

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LODAS

• Learning Object Design and Sequencing Theory

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LODAS - Background

• Synthesis of
• van Merriënboers 4C/ID
• Reigeluths Elaboration Theory
• Gibbons et al.s Work Model Synthesis
• Bundersons et al.s Domain Theory
• Pedagogy
• Problem and activity centered
• Instruction plays supporting role

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Grain Size

• How big is big enough?
• How big is too big?
• How big should my learning objects be?

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Multigrain

• Whats the right size?
• Naïve
• Misleading
• Multiple levels are both practical and ideal

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Synthesize Work Models

• Traditional task/job analysis
• Low-level objectives
• Partially recombine objectives
• Actionable description of valuable performances
• Top level LO is a Work Model

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Hollowness on Two Levels

• Work Model is only a specification / design
  construct
• Determine simplifying conditions, simplest
  real-world case (epitome)
• Several work model re-statements (S?C)
• Each mid-level LO is a Case Type

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Fundamental Elements

• Case Type is another specification
• Create several Specific Problems based on each
  Case Type
• Specific Problems are the actual learning
  activities with which learners interact

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Scope Review
Work Model Dark Green Case Types Mint
Green Specific Problems White
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Sequencing / Combining Objects

• Whats the right sequence?
• When LOlow-level objective, sequenceprereq
  hierarchy/tree
• But when LOmultigrained, multiple sequences
  strategies are necessary

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Multigrain Sequencing

• Work Models simple to complex
• Case Types elaboration order
• Specific Problems random
• Is it really that simple?

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Multidimensional Multigrain

• Simple to complex assumes comparison on a number
  line
• Numeric values assignable to WMs using IRT
  techniques
• Do all WMs belong on the same number line?

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Example

• Language learning domain (Strong-Krause, 2001)
• Vocabulary
• Reading
• Writing
• Speaking
• Listening
• Assuming uni-d when your data is multi-d makes
  for yucky analyses

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Charting Domain Dimensionality

• First draft
• Lit reviews and practice-based hunches
• Iterative drafts
• Data driven (factor analysis, smallest space
  analysis)

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Splitting Your Multigrains

• WMs must be assigned to a uni-d number line
• S?C ordering along common uni-d

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Catch Your Breath

• WMs, Case Types, Specific Problems
• Multidimentionality of domain
• Each WM associated with appropriate uni-d

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Period.

• Without this kind of rigorous domain mapping
  process our scope and sequence decisions are
  guesses.
• Period.

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A Real World Example

• Beginning undergraduate music theory
• Wiley Welch (2001)

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Scope Decisions

• Identify or construct scales given key signatures
• Major
• minor
• Identify or construct key signatures
• Major
• minor
• Identify or construct triads
• Major
• minor
• diminished
• augmented
• Hear and write intervals
• Take melodic dictation

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Dimensionality Guesses

• Cognitive skills
• Aural Skills

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Difficulty Guesses

• Scales
• Key Signatures
• Chords
• Case Types ordered as elaborated

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Dimensionality Results

• Three (not two) uni-ds
• Cognitive
• Basic
• Advanced
• Aural

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Difficulty Results
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Can you say orthogonal?
We teach
They learn
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Practical Results

• The traditional sequence does not fit student
  growth models
• An integrative (problem-based) approach would fit
  better
• Britney Spears, Protestant Hymn, Bach Chorale

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LO Taxonomy

• Single
• Combined-closed
• Combined-open
• Generative-presentation
• Generative-instructional

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Gen. Inst. as Case Type
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ltwhinegtIts Complicated!lt/whinegt

• and expensive and will never fit into our ID
  process!
• Data gathering 10 minutes
• Data entry scrubbing 2 hours
• Data analysis 4 hours
• Id est, about one day.

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Its the context, stupid.

• Individual LOs are decontextualized
• To do ID is to contextualize
• Is juxtaposition/sequencing of LOs enough?
• If not, where do we get context?

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1. Integrative Info at the WM Level

• Design additional context-linked SCOs to Intro
  the Work Model
• Design additional context-linked SCOs to
  Summarize the Work Model with assessments

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2. Cross uni-d Work Models

• Most models (Cisco) assume domain uni-d-ness
• Additional integrative WMs will have to
  vertically integrate across several uni-ds

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Its Possible Now!

• Work Model as Aggregation
• Case Type as SCO
• Specific Problem (CT/GI) as Asset
• SCORM 1.2 already gives us
• Tree-based sequencing
• Mastery-determined advancement

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Daves Directions

• Merrill
• Cognitive Psychology paradigm
• Information Processing Model
• Single-processor!
• Wiley
• Social Constructivist paradigm
• Grid / Distributed Processing Model

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Distributed Computing (P2P)

• Cycle sharing / distributed computation
• SETI_at_home
• Genome_at_home
• Distributed.net
• File sharing / distributed storage
• Napster
• GNUtella/LimeWire/BearShare
• Morpheus/Kazaa/FastTrack

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Distributed Comparison

• Cycle sharing / distributed comp
• File sharing / distributed storage

• Collaborative learning strategies
• Distributed expertise / resource sharing

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OSOSS

• Online self-organizing social system
• Osu -- Whats up? in Japanese
• Wiley Edwards (2002)
• NSF CAREER grant

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Characteristics

• Very large (30,000)
• Increasingly (fully) decentralized
• No omniscient expert
• Increasingly democratic
• All voices initially equal
• Peer feedback (review) critical role
• Bio self-org (pheromonal, stygmergy)

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OSOSS Pedagogy / SCORM?

• Collaborative Problem-Solving (Nelson, 1999)
• Reusable instructional resources
• Catalyze/crystalize CPS process
• Slurping OSOSS exchanges as SCO

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6 Degrees of Separation

• Church State/Strategy Content?
• Content is generally inert
• Human beings and authentic probs
• Strategies
• Contextual glue

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Innovation?

• Resource queries without metadata
• Resource reuse without digital libraries
• Scalable learning support rich with human
  interaction
• Collaborative problem solving around authentic
  problems

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The End

• http//wiley.ed.usu.edu/
• david.wiley_at_usu.edu