into the pedagogical woods david wiley, ph.d. dept. of instructional technology utah state...

Into the Pedagogical Woods

David Wiley, Ph.D.Dept. of Instructional TechnologyUtah State University

March 12, 2002 David Wiley, Utah State University 2

Overview

LODAS Scope / grain size Sequence / combination

OSOSS


LODAS

Learning Object Design and Sequencing Theory


LODAS - Background

Synthesis of van Merriënboer’s 4C/ID Reigeluth’s Elaboration Theory Gibbons et al.’s Work Model Synthesis Bunderson’s et al.’s Domain Theory

Pedagogy Problem and activity centered “Instruction” plays supporting role


Grain Size

How big is big enough?

How big is too big?

How big should my learning objects be?


Multigrain

“What’s the right size?” Naïve Misleading

Multiple levels are both practical and ideal


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”


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 (SC)

Each mid-level LO is a “Case Type”


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


Scope Review

Work Model – Dark Green

Case Types – Mint Green

Specific Problems – White


Sequencing / Combining Objects

What’s the right sequence?

When LO=low-level objective, sequence=prereq hierarchy/tree

But when LO=multigrained, multiple sequences strategies are necessary


Multigrain Sequencing

Work Models: simple to complex

Case Types: elaboration order

Specific Problems: random

Is it really that simple?


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?


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


Charting Domain Dimensionality

First draft Lit reviews and practice-based hunches

Iterative drafts Data driven (factor analysis, smallest

space analysis)


Splitting Your Multigrains

WMs must be assigned to a uni-d number line

SC ordering along common uni-d


Catch Your Breath

WMs, Case Types, Specific Problems

Multidimentionality of domain

Each WM associated with appropriate uni-d


Period.

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

Period.


A Real World Example

Beginning undergraduate music theory

Wiley & Welch (2001)


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


Dimensionality Guesses

Cognitive skills

Aural Skills


Difficulty Guesses

1. Scales2. Key Signatures3. Chords

Case Types ordered as elaborated


Dimensionality Results

Three (not two) uni-ds Cognitive

Basic Advanced

Aural


Difficulty Results


Can you say “orthogonal”?

We teach They learn


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


LO Taxonomy

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


Gen. Inst. as Case Type


<whine>It’s Complicated!</whine>

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.


“It’s 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?


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


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


It’s Possible Now!

Work Model as Aggregation Case Type as SCO Specific Problem (CT/GI) as Asset

SCORM 1.2 already gives us:1. Tree-based sequencing2. Mastery-determined advancement


Daves’ Directions

Merrill Cognitive Psychology paradigm Information Processing Model Single-processor!

Wiley Social Constructivist paradigm Grid / Distributed Processing Model


Distributed Computing (P2P)

Cycle sharing / distributed computation SETI@home Genome@home Distributed.net

File sharing / distributed storage Napster GNUtella/LimeWire/BearShare Morpheus/Kazaa/FastTrack


Distributed Comparison

Cycle sharing / distributed comp

File sharing / distributed storage

Collaborative learning strategies

Distributed expertise / resource sharing


OSOSS

Online self-organizing social system

“Osu” -- “What’s up?” in Japanese

Wiley & Edwards (2002)

NSF CAREER grant


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)


OSOSS Pedagogy / SCORM?

Collaborative Problem-Solving (Nelson, 1999)

Reusable instructional resources1. Catalyze/crystalize CPS process2. Slurping OSOSS exchanges as SCO


6 Degrees of Separation

Church & State/Strategy & Content?

Content is generally inert

Human beings and authentic probs Strategies Contextual glue


Innovation?

Resource queries without metadata

Resource reuse without digital libraries

Scalable learning support rich with human interaction

Collaborative problem solving around authentic problems

The End

http://wiley.ed.usu.edu/

[email protected]

into the pedagogical woods david wiley, ph.d. dept. of instructional technology utah state...

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