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Introducing Desirable Difficulties for Educational Applications in Science

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Title: Introducing Desirable Difficulties for Educational Applications in Science


1
Introducing Desirable
Difficulties for Educational
Applications
in Science
www.psych.ucla.edu/iddeas
  • Robert A. Bjork
  • University of California, Los Angeles
  • Marcia C. Linn
  • University of California, Berkeley

2
Desirable Difficulties
  • Spacing rather than massing study
  • Interleaving rather than blocking practice on
    separate topics or tasks
  • Varying contextual cues
  • Reducing feedback to the learner
  • Testing rather than re-presenting

3
Learning versus performance
  • What we can observe is performance, what we must
    infer is learning
  • and the former is an unreliable index of the
    latter
  • Instructors are, therefore, susceptible to
    choosing less-effective conditions of learning
    over more-effective conditions
  • And as learners, we, too, are susceptible to
    confusing performance with learning

4
Generation Interleaving
Spacing
5
Goals of the IDDEAS project
  • Do such findings extend to to-be-learned
    materials and retention intervals that are
    realistic from an educational standpoint?
  • And, more broadly, what design principles are
    fundamental in optimizing educational materials
    and practices?

6
WISE (web-based inquiry science environment)
http//wise.berkeley.edu
  • Advantages as a tool for teachers
  • Supports authoring and customization
  • Contains a library of tested projects
  • Enables collaborative learning, visible thinking,
    autonomous investigation
  • Transportable
  • Advantages as an IDDEAS research tool

7
Current Projects
  • WISE Platform
  • 2 laboratory studies, UCLA
  • 2 classroom studies, UCB
  • Design Principles
  • 2 studies, UCLA

8
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9
Interleaving
  • Motor tasks patterns, force production, bank
    machine transactions (Lee Magill, 1983, Simon
    Bjork, 1990 Charles et. al, 1990, Jamieson
    Robers, 2000)
  • Sports badminton, volleyball, baseball (Bortoli
    et al, 1992, Goode Magill, 1986, Hall et al,
    1994)
  • Abstract learning tasks mazes, tracking
    (Carleson et.al, 1989, Jelsma Van Merrienboer,
    1989, Jelsma Pieters, 1989)
  • Logic rules, boolean operators (Schneider et al,
    1995, Carleson Yaure, 1990)

10
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11
Example of generation effects
12
Study 1 Overview
  • Uses an existing WISE astronomy module
  • How scientists determine the habitability of
    planets
  • Design4 groups
  • Mass and distance slides either blocked or
    interleaved
  • Some evidence re-studied via generation or
    reading
  • Forty-eight hour retention interval
  • Posttest

13
Posttest questions
  • Simple sentence-completion Information presented
    and re-studied via generation or reading, or only
    presented
  • E. g. The amount of heat and light emitted by
    the sun in our solar system has increased by
    ____ since the beginning of earths history.
  • Integration questions across mass slides or
    across distance slides
  • E. g., Would an object weigh more on the planets
    in our solar system made mostly of gas or made
    mostly of rock? Why?
  • Integration questions across mass and distance
    slides
  • E. g., Imagine a planet that is smaller than
    Earth and that was located 1.5 AUs from its sun,
    which is the same strength as the Earths sun.
    How would this planets potential for life
    compare to Earths?

14
Figure 1. UCLA Study 1 - Interleaving by type of
Posttest Integration Question.

15
Figure 2 UCLA Study 1 -Generation effects on
single fact materials
16
Generation manipulations
  • Study 1 (UCLA) Sentence Completion
  • Generate ____-type planets are mostly made up
    of gases.
  • Read Jovian-type planets are mostly made up of
    gases.
  • Study 2, (UCLA and UCB Classroom Studies 1 and
    2)
  • Sentence level generation
  • E.g., Describe in a sentence how the size of one
    planet's mass can affect another planet.
  • Knowledge required for successful generation
  • Mass or distance Only
  • Both mass and distance

17
Projects in Progress using WISE
  • Interactions between Generation Interleaving
    (UCLA and Classroom)
  • Integration of M D
  • Integration of M or D
  • Increase Contextual Interference (UCLA and
    Classroom)
  • Habitability and Detectability
  • Visual Support for Generation (Classroom)
  • Static versus Animated

18
Design Principle Interleaving
  • Interleaving as spacing Practical advantages
  • But are effects of interleaving more than the
    effects of spacing?
  • Contextual interference ideas (Battig, 1972,
    1979)
  • Benefits dues to
  • Reloading/ Reconstruction (e.g. Lee Magill,
    1983, 1985)
  • And/or Development of a higher order
    representation to differentiate interleaved
    materials (Shea Zimny, 1983, 1988)

19
Disentangling Interleaving and Spacing
  • Initial experiment with second-language materials
    (courtesy of Hal Pashler)
  • Designed to
  • Maximize contextual interference
  • Co-vary (i.e., unconfound) interleaving and
    spacing

20
Learning Materials
English word
bird
dege
lind
Estonian
Swahili
-8 English words learned in both foreign
languages (16 word pairs total) -6 repetitions
(anticipation trials) of each word pair
21
Sample anticipation-method learning trial
What is tree in Swahili?
mufuma
?
The correct word is mfufumaji
22
Sample Test Trial
What is tree in Swahili?
?
in Estonian?
?
23
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24
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25
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26
Implications and necessary next steps
  • Interleaving can cause intrusions and errors
    during learning that then foster long-term
    retention--and, possibly, transfer
  • The effects of interleaving and spacing
  • May be independent and additive,
  • But contextual interference (competition) maybe
    be necessary to demonstrate benefits of
    interleaving that go beyond the benefits of
    spacing
  • And, from an educational standpoint, it is
    essential to see whether the same pattern obtains
    with more complex and cumulative materials

27
Our thanks to
  • The Institute for Education Sciences and the
    Cognition and Student Learning program
  • Other members of the IDDEAS research team
  • Lindsey E. Richland, Ph.D, (UCLA)
  • Britte H. Cheng (UC Berkeley)
  • Jason R. Finley (UCLA)
  • And a number of undergraduate students,
    especially Jeff Beyers, Fernando Cervantes, and
    Alexandra Hessenius
  • Relevant Links
  • IDDEAS http//www.psych.ucla.edu/iddeas
  • WISE http//wise.berkeley.edu
  • SCALE (Synergy Communities Aggregating
    Learning about Education) - http//scale.soe.berke
    ley.edu
  • TELS (Technology Enhanced Learning in Science) -
    http//www.telscenter.org
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