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Investigating the Achievement Gap in...
~
Bhowmick, Nandini.
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Investigating the Achievement Gap in Mathematics: An Analysis of Fifth Grade School Data.
Record Type:
Electronic resources : Monograph/item
Title/Author:
Investigating the Achievement Gap in Mathematics: An Analysis of Fifth Grade School Data./
Author:
Bhowmick, Nandini.
Description:
104 p.
Notes:
Source: Dissertation Abstracts International, Volume: 76-01(E), Section: A.
Contained By:
Dissertation Abstracts International76-01A(E).
Subject:
Mathematics education. -
Online resource:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3635092
ISBN:
9781321160147
Investigating the Achievement Gap in Mathematics: An Analysis of Fifth Grade School Data.
Bhowmick, Nandini.
Investigating the Achievement Gap in Mathematics: An Analysis of Fifth Grade School Data.
- 104 p.
Source: Dissertation Abstracts International, Volume: 76-01(E), Section: A.
Thesis (D.Ed.)--University of Minnesota, 2014.
This item must not be sold to any third party vendors.
The problem of the achievement gap gained widespread attention after the initiation of the No Child Left Behind (NCLB) Act of 2001 (U.S. Department of Education, 2002). According to NCLB, schools, districts, and state educational systems are required to meet annual targets for improvement in identified academic areas (mathematics, reading, and science), not only for their student populations as a whole, but for several identified subgroups: (a) Black, (b) Hispanic, (c) white, (d) economically disadvantaged, (e) special education students and (f) limited English proficiency (LEP). Schools, districts, and states were seen as ultimately accountable for the achievement rate of any of these subgroups of students. The purpose of this study was to use the concept of an education production function to measure students' current year performance in mathematics (output, measured by test scores) as a combination of inputs: (a) students' previous year's test score, (b) teacher quality (measured by National Board Certification), (c) socioeconomic status (measured by free and reduced lunch population), (d) school setting (urban, suburban), and (e) student demographics (measured by ethnicity and special needs student population). To analyze these relationships, this study utilized quantitative methods, particularly multiple regression analysis. The results show that students' current year performance in mathematics is significantly related with students' previous year's performance, socioeconomic status, and student demographics defined by special needs population. A statistically significant relationship was also found between students' academic performance in mathematics and ethnicity. Teacher quality measured by National Board Certification has significant influence on students' academic performance in mathematics. Looking at urban and suburban school setting, results show that there is not any significant relationship with students' academic performance in mathematics and school setting.
ISBN: 9781321160147Subjects--Topical Terms:
641129
Mathematics education.
Investigating the Achievement Gap in Mathematics: An Analysis of Fifth Grade School Data.
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Adviser: Frank A. Guldbrandsen.
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The problem of the achievement gap gained widespread attention after the initiation of the No Child Left Behind (NCLB) Act of 2001 (U.S. Department of Education, 2002). According to NCLB, schools, districts, and state educational systems are required to meet annual targets for improvement in identified academic areas (mathematics, reading, and science), not only for their student populations as a whole, but for several identified subgroups: (a) Black, (b) Hispanic, (c) white, (d) economically disadvantaged, (e) special education students and (f) limited English proficiency (LEP). Schools, districts, and states were seen as ultimately accountable for the achievement rate of any of these subgroups of students. The purpose of this study was to use the concept of an education production function to measure students' current year performance in mathematics (output, measured by test scores) as a combination of inputs: (a) students' previous year's test score, (b) teacher quality (measured by National Board Certification), (c) socioeconomic status (measured by free and reduced lunch population), (d) school setting (urban, suburban), and (e) student demographics (measured by ethnicity and special needs student population). To analyze these relationships, this study utilized quantitative methods, particularly multiple regression analysis. The results show that students' current year performance in mathematics is significantly related with students' previous year's performance, socioeconomic status, and student demographics defined by special needs population. A statistically significant relationship was also found between students' academic performance in mathematics and ethnicity. Teacher quality measured by National Board Certification has significant influence on students' academic performance in mathematics. Looking at urban and suburban school setting, results show that there is not any significant relationship with students' academic performance in mathematics and school setting.
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