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Minimize RSR Award Detail

Research Spending & Results

Award Detail

Awardee:UNIVERSITY OF OKLAHOMA
Doing Business As Name:University of Oklahoma Norman Campus
PD/PI:
  • Yingtao Liu
  • (405) 325-4757
  • yingtao@ou.edu
Co-PD(s)/co-PI(s):
  • Zahed Siddique ~000260270
Award Date:11/27/2017
Estimated Total Award Amount: $ 243,316
Funds Obligated to Date: $ 243,316
  • FY 2018=$243,316
Start Date:12/15/2017
End Date:11/30/2020
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: Multi-Scale Experimental Mechanics Education Module
Federal Award ID Number:1712178
DUNS ID:848348348
Parent DUNS ID:046862181
Program:IUSE
Program Officer:
  • Karen Crosby
  • (703) 292-4629
  • kcrosby@nsf.gov

Awardee Location

Street:201 Stephenson Parkway
City:NORMAN
State:OK
ZIP:73019-9705
County:Norman
Country:US
Awardee Cong. District:04

Primary Place of Performance

Organization Name:University of Oklahoma Norman Campus
Street:
City:
State:OK
ZIP:73019-9705
County:Norman
Country:US
Cong. District:04

Abstract at Time of Award

This project focuses on combining solid mechanics experimentation and material visualization to enhance undergraduate solid mechanics education and assist students to develop appropriate mental models of abstract engineering concepts to enhance learning. This effort employs multiple length scale material characterization and visualization for solid mechanics education, web-based education modules, and experiential learning. A broad impact of this research is a contribution to the education of future professional engineers in fundamental solid mechanics and increase in the critical number of individuals who are capable of translating STEM advances into engineering innovations. This research project is pilot testing the effectiveness of mechanics education by establishing the relation of material structure and solid mechanics, which can assist students in understanding complex and abstract concepts in engineering. To understand whether the proposed approach can improve student learning and retention of course materials covered, Primary Trait Analysis, Student Assessment of Learning Gains Surveys, and individual student interviews are being used to analyze and compare students' learning outcomes with conventional methods. Changes in Student Mental Model Representation are being analyzed through a language-oriented methodology for text and graphical representations of open problems. Pre- and post-experiments are being used to compare and track changes in students' mental representation. The measures are also being used to compare control and treatment groups. Students' perceptual and motivational characteristics are being assessed using a multi-scale questionnaire instrument previously designed and validated by project personnel.

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