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The Potential of Games & Simulations for Learning and Assessment. Richard Wainess: wainess@cse.ucla.edu Presented Monday, January 22, 2007 at the 2007 CRESST Conference. Overview. Do games & simulations foster learning? Issues affecting learning from games & simulations

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the potential of games simulations for learning and assessment

The Potential ofGames & Simulationsfor Learning and Assessment

Richard Wainess: wainess@cse.ucla.edu

Presented Monday, January 22, 2007 at the 2007 CRESST Conference

overview
Overview
  • Do games & simulations foster learning?
  • Issues affecting learning from games& simulations
  • Assessments using games & simulations
  • Embedding instructional methods into games& simulations
  • The bottom line
the promise of game sim based learning
The promise of game/sim-based learning
  • General belief is games & simulations improve instruction
    • Provide complex and diverse approaches to learning
    • Provide learner control
    • Can address both cognitive and affective needs
    • Motivate learners
what the evidence shows
What the evidence shows
  • Positive outcomes?
    • Numerous knowledge outcomes are attributed to games and simulations
      • Studies also warn about anecdotal and descriptive evidence(Leemkuil et al., 2003; Wolfe, 1997)
    • Generalizable skills outcomes have been cited(Day et al. 2001; Green & Bavelier, 2003; Greenfield et al., 1994)
  • Negative or null outcomes?
    • Reviews and meta-analyses cite mixed or negative reviews(Dekkers & Donatti, 1981; Druckman, 1995)
    • Positive attitude toward games (i.e., motivation) doesn’t necessarily equal learning(Brougere, 1999; Salas et al., 1998; Salomon, 1984)
what the evidence shows cont d
What the evidence shows(cont’d)

So, do games & simulationsfoster learning?

NO!!!!

  • Learning is related to Instructional Methods, not media (games/simulations, book, lectures, etc.)(de Jong & van Joolingen, 1998; Garris et al., 2002; Gredler, 1996; Leemkuil et al., 2003; Thiagarajan, 1998)
implied model of games simulations
Implied model of games & simulations

based on erroneous and/or unsupported research conclusions

Games and simulations

Increased Learning

true model of games simulations
True model of games & simulations

based on empirical evidence

Games and simulations

Studying

Student

Attitude

Student

Ability

Prior

Knowl.

Instructional

Components

Teacher

Training

Teacher

Attitude

Increased Learning?

cognitive load
Cognitive load

= burden placed on our working memory

  • Affected by instructional components
    • Number and nature of elements needing processing (Cooper, 1998; Paas et al., 2003)
    • Message complexity, stimulus features(Daniels & Moore, 2000)
  • Particular to computer media & interactivity
    • Additional media-related cognitive demands(Daniels & Moore, 2000)
    • Level of learner control and autonomy(Dias, Gomes, & Correia, 1999)
task difficulty

Enjoyment of a game/simis linked mental effort

Mental effort is linked totask difficulty

More

Effort

Less

More

Task difficulty

Task difficulty
  • Relationship of taskdifficulty to mental effortis an inverted U(Clark, 1999; Malone & Lepper, 1987)
    • Too easy = player gets bored
    • Too hard = player disengages
  • Optimal cognitive load = neither too hard nor too easy
sources of cognitive load
Sources of cognitive load
  • Intrinsic Cognitive Load
  • Germane Cognitive Load
  • Extraneous Cognitive Load
  • Learner Control
sources of cognitive load1
Sources of cognitive load
  • Intrinsic Cognitive Load
    • Load incurred by the to-be-learned material(Brunken et al., 2003; Paas et al., 2003)
      • (i.e., metacognition, forming schema, chunking, automating)
  • Germane Cognitive Load
    • Cognitive load imposed by instruction; methods and strategies required to process intrinsic load(Renkl & Atkinson, 2003)
      • (e.g., instruction, examples, reading, searching, problem solving, interface elements)
sources of cognitive load2
Sources of cognitive load
  • Extraneous Cognitive Load
    • Imposed by an unnecessary stimuli (e.g., interface artwork, extraneous sounds)(Brunken et al. 2003)
      • Seductive details(Mayer et al., 2001; Schraw, 1998)
  • Learner Control
    • Pacing & navigation(Barab et al., 1999; Cutmore et al., 2000)
    • Metacognitive processes(Clark, 2003; Daniels & Moore, 2000; Dillon & Gabbard, 1998)
      • Goal setting and planning, monitoring, selecting, organizing, etc.)
issues pertaining to games
Issues pertaining to games

Extraneous details, split attention, learner control

Tom Clancy’s Ghost Recon (Red Storm Entertainment, 2002)

issues pertaining to simulations
Issues pertaining to simulations

Extraneous & seductive details, split attention, learner control (cognitive load issues)

issues pertaining to simulations1
Issues pertaining to simulations

Experiential/Discovery-based Learning(metacognitive and cognitive load issues)

Developed by the University of Southern California’s Center for Cognitive Technology (USC/CCT) using iRidesAuthor

what s bad about games sims
What’s bad about games/sims?
  • Extraneous and Seductive details
  • Learner Control
  • Mindless manipulation
  • Potential for unguided learning
what s good about games sims
What’s good about games/sims?
  • Authentic tasks
  • Personalization
  • Presence/immersion
  • Motivation(and persistence)
what game sim elements are detrimental
What game/sim elements are detrimental?
  • Rich, engaging content
  • Immersive environments
  • Impressive sound tracks
  • Spectacular effects
  • Compelling fantasy
  • Gives learner control
  • Can promote mindlessmanipulation
what game sim elements are beneficial
What game/sim elements are beneficial?
  • Rich, engaging content?
  • Immersive environments?
  • Impressive sound tracks?
  • Spectacular effects?
  • Compelling fantasy?
  • Gives learner control?
  • Opportunity to experiment?
  • Potential for adaptive learning
computer based assessments
Computer-based assessments

Requirements

  • Ability of computer to assess and report performance
  • Ability of computer to use outcomes to adapt learning
  • Ability to assess meaningful learning
    • Applying knowledge and skills
    • Authentic task performance
computer based assessments cont d
Computer-based assessments(cont’d)

Examples

  • Retention assessments(assess memory)
    • Fill-in-the-blank
    • Knowledge maps
  • Performance based assessments(assess problem solving, decision-making)
    • Knowledge maps
    • Fill-in-the-blank
    • Process maps
    • Authentic tasks
embedding assessments
Embedding assessments
  • Pre-assessments(diagnostic assessment)
    • Adaptive instruction
    • Assess learning gains
  • In-course assessments(formative assessment)
    • Signaling/Priming/Cueing
    • Feedback/Monitoring
    • Authentic tasks
  • Post-assessments(summative assessment)
    • Assess learning outcomes
    • Provide predictions of future performance (transfer)

Developed by the University of Southern California’sCenter for Cognitive Technology (USC/CCT) using iRidesAuthor

embedded guidance
Embedded Guidance
  • Instruction
  • Worked examples
  • Practice opportunities
    • With goals
  • Signaling/cueing
  • Other learning scaffolds(instructional methods/strategies)

Developed by the University of Southern California’sCenter for Cognitive Technology (USC/CCT) using iRidesAuthor

the bottom line1
The bottom line

Can we learn from games and simulations?

YESWith proper instructional methods

Can games and simulations provideeffective assessments?

YESParticularly if they exploit the capabilities of computers