| Goods |
Award Abstract #1119312
Collaborative Research: An Agent-Based Simulation Environment for Predictive Longitudinal Modeling of High School Math Performance
NSF Org: DRL
Division Of Research On Learning
divider line
Initial Amendment Date: November 13, 2011
divider line
Latest Amendment Date: August 10, 2012
divider line
Award Number: 1119312
divider line
Award Instrument: Standard Grant
divider line
Program Manager: Elizabeth VanderPutten
DRL Division Of Research On Learning
EHR Direct For Education and Human Resources
divider line
Start Date: November 15, 2011
divider line
End Date: October 31, 2013 (Estimated)
divider line
Awarded Amount to Date: $76,109.00
divider line
Investigator(s): Paul Resta resta@mail.utexas.edu (Principal Investigator)
divider line
Sponsor: University of Texas at Austin
3925 W Braker Lane, Ste 3.340
Austin, TX 78759-5316 (512)471-6424
divider line
NSF Program(s): DISCOVERY RESEARCH K-12
divider line
Program Reference Code(s): 9177, SMET
divider line
Program Element Code(s): 7645
ABSTRACT
This collaborative proof-of-concept study involves The University of California at Santa Cruz, The University of Texas at Austin, and the Los Alamos National Laboratory. The PIs will test the efficacy of using agent-based simulation and visualization models to identify the factors that predict mathematics achievement for students from the 8th grade to the 12th grade and beyond. The team are using a data set that includes 14 years of data on student grade reports, coursework, demographics, teacher variables such as years of service, professional development courses take, years of service, and other artifacts. The investigators hypothesize that agent-based modeling can be used to improve mathematics education. The research questions is What are the predictors of success in mathematics of public school 8th grade students and beyond as measured by a) mathematics performance (test scores) broken down by different mathematical skills? b) enrollment in algebra class (8th grade and high school)? and c) algebra and mathematics grades in 8th grade and high school? This exploratory study will analyze data using three tasks. The first task involves data assessment. The first task will involve discovering distributional information in general. They will explore visual and analytical processes of different variables so that different synthetic data can be simulated. The second task involves collaborating with a statistical science team to incorporate distributional information so that multivariate samples can be generated to form synthetic populations to use to build the agent-based model. The third task involves using the actual data from two large school districts to understand and quantify variability in the data.
Education systems do not have a valid way to measure progressions of mathematics education to evaluate outcomes associated with mathematics learning outcomes. This project will provide a baseline understanding of student's progression in mathematics achievement that is critical in helping educators and policy makers set goals and standards for mathematics education within the United States.
Please report errors in award information by writing to: awardsearch@nsf.gov.
|