Application of Markov Chains to Analyze and Predict the Mathematical Achievement Gap between African American and White American Students
Vivian R Moody* and Kanita K DuCloux
Department of Mathematics, Western Kentucky University, Bowling Green, KY, USA
- *Corresponding Author:
- Vivian R Moody
Department of Mathematics
Western Kentucky University
Bowling Green, KY, USA
Tel: 1 270 745 6209
E-mail: [email protected]
Received Date: March 12, 2014; Accepted Date: April 07, 2014; Published Date: April 14, 2014
Citation: Moody VR, DuCloux KK (2014) Application of Markov Chains to Analyze and Predict the Mathematical Achievement Gap between African American and White American Students. J Appl Computat Math 3:161 doi: 10.4172/2168-9679.1000161
Copyright: © 2014 Moody VR, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
A stochastic, mathematical model known as a discrete Markov Chain was used to show how to estimate the probability that the mathematical achievement gap between African Americans and White Americans would close during a particular calendar year. The implications of race in the achievement of mathematics in the United States are profound and well-documented in mathematics education research literature. The authors used historical data drawn from the National Assessment of Educational Progress (NAEP) to examine trends of mathematical achievement between African Americans and White Americans during the assessment years of 1973–2012. The authors provide a discussion of NAEP data in the context of the discrete Markov Chain model and describe how specific properties of the Markov process were used to estimate the probability that the mathematical achievement gap will close within the next 50 years.