Games for Learning:
Understanding what makes an
Effective Game for Learning
Ken Perlin and Jan Plass, NYU
Research Objectives
Guiding Principles
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Focus on STEM (Science, Technology, Engineering, & Mathematics) fields
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“NSF programs planned for FY 2008 that will make investments in computing
education …”
– Jeanette Wing, Assistant Director for CISE
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Understanding effective uses of games in middle school curricula
Problem Statement
Underserved populations
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Specific populations
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Children from Inner-cities
Children in rural communities
Children in impoverished nations regions
Problems they face
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Lack of access to computers
Lack of engaging materials relative to their experiences
Poorly funded educational environments
Rapidly fluctuating, intensely varied technology platforms
Platforms
Of particular interest:
Making games for learning on mobile platforms
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Mobile gaming platforms
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Sony PSP
Nintendo DS
Platforms
Making games for learning on mobile platforms
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Cellular Phones
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J2ME (Java 2 Mobile Environment)
Flash
Overview
Game-based Learning Approach
Curricular
Educational Game
Design Principles
Educational
Games
Integration
Factual
Knowledge
Conceptual
Knowledge
Procedural
Knowledge
Meta-cognitive
Knowledge
Affective
Outcomes
Research Plan
Research Questions
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Identify Design factors (cognitive, emotional, socio-cultural) for
effective educational games
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Study how the way games are integrated into authentic settings
affects their educational effectiveness
– What are effective integration practices?
– What support do teachers require?
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Study impact of learner characteristics (gender, age, prior
knowledge, cognitive ability, self-regulation skills) on educational
effectiveness of games
Research Plan
Overview
Observation of
Game Play
Features of Effective
Educational Games
Review Research
on Games
Development
Team: Implement
Game Prototypes
Education Team:
Empirical Research
Game Design
Principles
Research Plan
Measures
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Learner Characteristics
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Survey of gaming experience
Tests of cognitive abilities
Tests of interest, motivation, attitudes
Embedded measures in game:
Self-regulation, prior knowledge
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Learning Process
– Log file data (pattern analysis)
– Video data (rubrics);
Think-aloud protocols (rubrics)
– Fun, Engagement (multiple measures)
– Embedded measures in game
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Learning Outcomes
– Learning outcome tests on multiple levels
– Embedded measures in game
Research Plan
Learning Outcome Measures
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Retention (Recall of factual knowledge)
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Comprehension (Understanding of key ideas)
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Metacognitive test, Cued recall (open-ended)
Concept maps
Game behavior/performance
Transfer (Ability to apply knowledge to new situations)
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Metacognitive test
Problem solving test (open-ended)
Design tests (open-ended)
Game behavior/performance
Metacognitive knowledge (Learning/exploration strategies)
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Game behavior/performance (logs)
Research Plan
Affect Outcome Measures
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Fun, Engagement
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Self-reports
In-Game behavior/performance
Flow experience
Overall player behavior:
SNS, game play usage patterns
Interest, Motivation, Attitudes
– Self-reports
– Game behavior/performance
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Subject-specific self-efficacy
– Self-reports
Results
Anticipated Outcomes
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Validated Design Principles for Educational Games
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Series of Validated Educational Games
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Data Analysis Toolkit for Educational Game Research
WILL ALLOW US TO
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Positively influence
Positively influence
Positively influence
into curriculum
Positively influence
the field of educational game design
educational game research models
the integration of educational games
students’ achievement in STEM areas
Funding Sources
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NSF Opportunities, based on the mandate for computational thinking
and education
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E.g., Repunsel- www.repunsel.org/
Corporate Funding
– Negotiation ongoing
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Educational Partners
– Teaming with several other universities and researchers to optimize skills,
while minimizing expenses