ugame-icompute funded by the national science foundation’s innovative technology experiences for...
TRANSCRIPT
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Gaming to LearnComputational Thinking
Jacqueline Leonard, Ph.D.Ruben Gamboa, Ph.D.Joy B. Johnson, Ph.D.
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Background
uGame-iCompute• Funded by the National Science Foundation’s
Innovative Technology Experiences for Students and Teachers (ITEST) from 2013-2016
• Combines game design and culture to improve middle school students’ computational thinking (CT)
• Implemented in Rocky Mountain West
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Project Goals
• To develop implement and study four components of an iterative intervention– Enhancing Students’ Attitudes toward STEM– Enhancing Students’ Computational Thinking– Professional Development for Teachers– Culturally Responsive Pedagogy
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Rationale • Need for mathematicians and computer
scientists will grow by 22% and 24%, respectively
• Engineering growing faster than other professions
• Limited information about engineering and what the field entails
• Gaming and game design is a pathway to STEM careers
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Messaging in the media…
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Definition of CT
• According to the International Society for Technology in Education (ISTE), CT is a problem solving process that involves:– formulating problems– logical organization of data– representation of data through abstractions– Identifying and automating solutions through algorithmic
thinking– analyzing and implementing possible solutions– generalizing and transferring the problem solving process
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The Research Study
• Pilot study on combined gaming/robotics conducted from 8-12 weeks
• Total of 133 students (35 females and 98 males; 35 underrepresented students) from seven schools in Wyoming
• AgentSheets (Scalable Game Design) used to learn programming and computational thinking
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Theoretical Framework
• Saxe Model– Goals for learning
structured by common cultural practices
– Cognitive forms and functions created and used to reach goals
– Interplay across learning in different contexts
• Edelson (Learning for Use (LfU)) Model– Knowledge is
incremental– Learning is directed– Knowledge is situated– Procedural knowledge
supports conceptual knowlegde
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Review of Literature
Computational Thinking• CT is a cognitive skill that all students can use
across disciplines in multiple contexts (Yadav et al., 2011)
• Digital game playing linked to development of CT (Barr et al., 2011; Repenning et al., 2010)
• Gaming linked to success in problem solving and social practices that support strategic thinking and data handling (Chang et al, 2012; Li, 2010)
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Research Questions
1. How did student participants’ self-efficacy and STEM attitudes, and 21st Century Skills change as a result of the pilot study?
2. What computational thinking strategies did student participants demonstrate during computer game design?
3. What elements of culture and/or place did student participants exhibit in their game design?
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Research Methodology
Mixed Methods Design• Quantitative and qualitative methods used to
collect data during the pilot study• Data Sources– Self-Efficacy in Technology and Science instrument
(SETS, Ketelhut, 2010) – Student Attitudes toward STEM survey (Friday
Institute for Educational Innovation, 2012)– 21st Century Skills – Student artifacts
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Data Analysis
• Descriptive statistics used to show trends in student efficacy, STEM attitudes, and 21st Century skills
• Threshold analysis used to determine growth trends on above skills
• Rubric used to measure CT• Games analyzed for elements of culture and
place
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Results
Findings: Year 1 Pilot Study
• Student self-efficacy on video gaming and computer use increased
• Student self-efficacy on computer gaming decreased slightly
• STEM attitudes were fairly stable• Measures for 21st Century Skills decreased
slightly
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Self-Efficacy Constructs
Pre-Score Std. Dev Post-Score Std. Dev.
Video gaming (n=61) 3.93 0.36 3.91 0.95
Computer Gaming (n=67) 3.82 0.76 3.74 0.90
Computer Use (n=68) 4.01 0.74 3.79* 0.94
Table 1: Comparison of Pre-Post Self-Efficacy
Self-Efficacy in Technology and Science
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STEM Domain Pre-Score Std. Dev Post-Score Std. Dev.
Mathematics (n=69) 3.76 0.83 3.66 0.91
Science (n=62) 3.20 0.70 3.25 0.74
Engineering/Technology
(n=67)3.74 0.79 3.70 0.90
21st Century Skills (n=64) 4.04 0.53 3.91 0.66
Table 2: Pre-Post Student Attitudes & 21st Century Skills
STEM Attitudes and 21st Century Skills
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Evaluating CT
• Rubric developed using definition of CT using a 3-point scale: emerging (1), moderate (2), substantive (3)– Students who used AgentSheet tutorial scored
lower in 1.6-2.0 range– Students who learned to program using
Agentsheets scored higher at 3.0
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Student Identifier
Problem Identification & Decomposition
Abstraction Logical Thinking
Algorithms Debugging & Connections
Average CT Rating
A 2 2 1 1 2 1.6
B 1 3 2 1 3 2.0
C 3 3 3 3 3 3.0
D 3 3 3 3 3 3.0
Focal Students’ Computational Thinking
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Evidence of Place
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Evidence of Culture
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Discussion
UGIC Program• Short time frame may not have been enough
to create significant change in student efficacy, attitude and 21st century skills
• Students may have realized difficulty in programming language that influenced efficacy and attitudes
• Teachers need more professional development on AgentSheets tool
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References CitedBarr, D., Harrison, J., & Conery, L. (2011). Computational thinking: A digital age. Learning & Leading with Technology, 20-23.Chang, K., Wu, L., Weng, S., & Sung, Y. (2012). Embedding game-based problem-solving phase into problem-posing system for mathematics learning. Computers & Education, 58(2), 775-786. Edelson, D. C. (2001). Learning-for-Use: A framework for the design of technology-supported inquiry activities. Journal of Research in Science Teaching, 38(3), 335–385.Li, Q. (2010). Digital game building: Learning in a participatory culture. Educational Reserch, 52(4), 427-443.Repenning, A., Webb, D., & Ioannidou, A. (2010). Scalable game design and the development of a checklist for getting computational thinking into public schools. Proceedings of the 41st ACM technical symposium on computer science education (pp. 265-269). Milwaukee, WI. Saxe, G. (1999). Cognition, development, and cultural practices. In E. Turiel (Ed.), Culture and development: New directions in child psychology (pp. 19–36). San Francisco, CA: Jossey-Bass.Yadav, A., Zhou, N., Mayfield, C., Hambrusch, S., & Korb, J. T. (2011, March). Introducing computational thinking in education courses. Proceedings of the 42nd ACM technical symposium on computer science education (pp. 465-470). Dallas, Texas.
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ITEST RESEARCH TEAMPrincipal Investigator: Jacqueline Leonard [email protected]
Co-Principal Investigator: Ruben Gamboa [email protected] Manager, Joy B. Johnson [email protected]
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THANK YOU