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Research Spending & Results

Award Detail

Awardee:VANDERBILT UNIVERSITY, THE
Doing Business As Name:Vanderbilt University
PD/PI:
  • Gautam Biswas
  • (615) 343-6204
  • gautam.biswas@vanderbilt.edu
Award Date:05/06/2021
Estimated Total Award Amount: $ 510,902
Funds Obligated to Date: $ 338,028
  • FY 2021=$338,028
Start Date:06/01/2021
End Date:05/31/2024
Transaction Type:Grant
Agency:NSF
Awarding Agency Code:4900
Funding Agency Code:4900
CFDA Number:47.076
Primary Program Source:040106 NSF Education & Human Resource
Award Title or Description:Collaborative Research: Computational Modeling for Integrating Science and Engineering Design: Model Construction, Manipulation, and Exploration
Federal Award ID Number:2055597
DUNS ID:965717143
Parent DUNS ID:004413456
Program:ECR-EHR Core Research
Program Officer:
  • Xiufeng Liu
  • (703) 292-8329
  • xiliu@nsf.gov

Awardee Location

Street:Sponsored Programs Administratio
City:Nashville
State:TN
ZIP:37235-0002
County:Nashville
Country:US
Awardee Cong. District:05

Primary Place of Performance

Organization Name:Vanderbilt University-ISIS
Street:1025 16th Avenue South Suite 102
City:Nashville
State:TN
ZIP:37212-2328
County:Nashville
Country:US
Cong. District:05

Abstract at Time of Award

Computational Modeling for Integrating Science and Engineering Design (CMISE) will conduct a series of experiments to systematically compare different computational modeling activities on 5th and 6th grade students’ engineering design processes, their understanding of engineering, science and computational thinking concepts, as well as science teachers’ confidence and ability to implement integrated STEM and computing curricula. Computational modeling involves a high cognitive load, and research to date is unclear whether the payoff primarily entails learning computing or whether students’ science and engineering learning benefit as well. CMISE will investigate how different types of computational modeling activities promote integrated student learning of science and engineering. CMISE will have immediate impacts on STEM + Computing offerings for the Metro Nashville Public School district where the project will be conducted; broadly it will also help strengthen and grow a diverse STEM workforce by bringing authentic and compelling science and engineering opportunities to fifth and sixth grade students. This project will also provide designers and researchers with empirical evidence for how to effectively integrate computer modeling with science and engineering learning activities in different settings. The CMISE curriculum and teacher support materials will be made freely available through project website, allowing these resources to reach a wide range of teachers beyond those included in the study. CMISE will leverage a previously developed and refined Next Generation Science Standards-aligned curriculum unit that integrates the Earth Science concept of urban water runoff with a meaningful engineering design problem for fifth- and sixth grade students to conduct fundamental research to better understand how different types of computational modeling activities mediate the connections between science and engineering learning. CMISE will conduct a series of design experiments to systematically compare the affordances of three computational modeling activities on students’ engineering design processes, their understanding of engineering, science and computational thinking (CT) concepts and practices, as well as science teachers’ confidence and ability to implement integrated STEM and computing curricula. The three activities being compared are computational model (CM) construction (where students model a science phenomenon in a given programming language), CM manipulation (where students inspect either the code or the simulation for a given CM of a science phenomenon), and CM exploration (where students explore a given simulation of a science phenomenon without viewing the underlying code). CMISE adopts a strong theoretical framing and a systematic design experiment approach to contribute to the learning theory of how students interact with and learn using different types of computational modeling activities. It will apply quantitative and qualitative analysis methods to combine established statistical analysis methods with novel analytics approaches and derive relations between students' learning behaviors and performance in the three experimental conditions. This design experiment studies will disentangle how these conditions influence the synergistic learning of science, engineering, and CT. This project is co-funded by the EHR Core Research (ECR) and CS for All: Research and RPPs programs. ECR supports work that advances fundamental research on STEM learning and learning environments, broadening participation in STEM, and STEM workforce development. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

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