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Game-Based Literacies

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Halo 3 104. Madden NFL (no specific version) 77. Solitaire 65. Dance Dance Revolution 60 ... 62 male 8th grade students randomly assigned to three conditions ... – PowerPoint PPT presentation

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Title: Game-Based Literacies


1
Game-Based Literacies Learning
  • Hiller A. SpiresProfessor Senior Research
    Fellow
  • College of Education
  • NC State University

2
What is the New Literacies Collaborative (NLC)?
A multidisciplinary team of researchers and
educators who promote research, professional
development, and global connections around new
literacies.
New literacies emerge from the theoretical and
practical intersection of literacy, technology,
and media.
3
Join Us!
  • New Literacies Collaborative
  • www.newlit.org
  • New Literacies Teacher Leader Institute
  • http//www.fi.ncsu.edu/newliteraciesinstitute.html
  • July 12 17, 2009 at the Friday Institute

4
Pew Internet American Life Project(September,
2008)
  • Game playing is universal--almost all 12-17 year
    olds play games.
  • Most popular game categories (puzzle, sports,
    action and adventure).
  • Game playing is social--most teens play games
    with others at least some of the time.
  • Almost a third of teens play games that are
    listed as appropriate only for people older than
    they are.

5
10 Most Frequently Played Games
  • Guitar Hero 158
  • Halo 3 104
  • Madden NFL (no specific version) 77
  • Solitaire 65
  • Dance Dance Revolution 60
  • Madden NFL 08 59
  • Tetris 59
  • Grand Theft Auto (no specific version) 58
  • Halo (no specific version) 57
  • The Sims (no specific version) 54
  •  

6
Games and 21st Century Learning
  • American Federation of Scientists (2006)
  • Game players are able to
  • Rapidly analyze new situations
  • Interact with characters they dont really know
  • Solve problems quickly and independently
  • Think strategically in a chaotic world
  • Collaborate effectively in teams

Becker Wade, 2004
7
NLC Research Game-based Learning
  • Bayesian Pedagogical Agents for Dynamic High
    Performance Inquiry-Based Science Learning
    Environment (NSF-0632450)
  • Research Team
  • James Lester, Computer Science
  • Hiller Spires, Literacy Technology
  • John Nietfeld, Educational Psychology
  • Scott McQuiggan, Kim Turner, Eleni
  • Lobeni, Kristin Hoffman, Sunyoung
  • Lee - Graduate Assistants
  • Betty Welsh Ada Lopez - Teachers

8
Research Questions
  • What are the effects of game-based performance on
    science content learning?
  • What game-based student performance profiles can
    be derived from time series data of student
    actions and plot points?
  • How do individual student differences contribute
    to clusters of game-based performance?

9
Methods
  • Participants
  • 54 female and 62 male 8th grade students randomly
    assigned to three conditions
  • Curricular Development
  • Five Curricular Goals
  • Defining pathogens
  • Defining virtual, bacterial, and fungal pathogens
  • Integration and comparisons of different types of
    pathogens
  • Scientific method and hypothesis testing
  • Treatment and prevention of pathogenic illnesses

10
Methods
  • Measures
  • Microbiology Content Pre- and Post-Test
  • Problem Solving Measure (PISA, 2006)
  • Computer and Gaming Interest Survey
  • Interest in the Intervention Survey
  • Procedures
  • Three conditions CI Narrative (n 58), CI
    Narrative-Lite (n 55), and Control (n 34)

11
Results Among Experimental Conditions
  • Science Content Learning
  • Problem-Solving
  • No differences across conditions

CI Narrative CI Narrative-Lite Control
12
Results Across Experimental Conditions
  • Self-Reported Interest in Intervention

CI Narrative CI Narrative-Lite
Control
13
Clusters of Navigation Traces within the
Narrative Condition
  • Navigation traces describe how each student
    maneuvered through the game environment
  • Operationalized by the number of cumulative
    actions, number of plot points completed, and
    completion time
  • Hierarchical clustering, using SAS JMP, to
    cluster students into three groups

14
Navigation Traces
15
Think Aloud Verbal Unit Distribution
Student Name Logistic Aesthetic Efferent Total Verbal Units
David 84 (57.93) 38 ( 26.21) 23 (15.86 ) 145
Henry 34 (34.34) 38 (38.38) 27 (27.27) 99
Steven 26 (23.64) 46 (41.82) 38 ( 34.55) 110
Peter 91 (47.15) 50 (25.91) 52 (26.94) 193
Sydney 9 (16.36) 34 (61.82) 12 (21.82) 55
Elizabeth 30 (28.57) 60 (57.14) 15 (14.29) 105
Nick 12 (14.29) 53 (63.10) 19 (22.62) 84
TOTAL 286 (36.16) 319 (40.33) 186 (23.51) 791
16
Theoretical Implications
  • Narrative Centered Learning Theory
  • Transactional Theory (Rosenblatt, 1983, 2004
    McEneaney, 2006)
  • Cognitive Load Theory (Sweller, 1999, 2005
    Mayer, 2005, 2008)
  • Extraneous processing
  • Essential processing
  • Generative processing

17
Future Studies
  • Implement multiple assessment measures, including
    performance-based assessment
  • Provide intelligent scaffolding informed by
    students game behaviors
  • Pair think-aloud protocols with navigation traces
    to determine transactional strategy use
  • Assess effects of student collaborative
    problem-solving

18
The Promise and Peril of Games
  • Child Guess what? I got to spend 15 extra
    minutes playing a computer game at school today.
  • Mom Oh great. What were you learning with the
    game?
  • Child sigh Mom, you dont learn stuff with
    games you just play.

2nd Grader
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