Mathematics Learning Patterns Across Two Groups of African American Students

L10 11

Views: 63

  • Title: Mathematics Learning Patterns Across Two Groups of African American Students: A Multilevel Approach
  • Author(s): John K. Rugutt, Mohamed A. Nur-Awaleh
  • Publisher: Common Ground Research Networks
  • Collection: Common Ground Research Networks
  • Series: The Learner
  • Journal Title: The International Journal of Learning: Annual Review
  • Keywords: Analysis of Change, Hierarchical Linear Modeling, Multilevel Models, Longitudinal Study, Growth in Mathematics Achievement, Socio-economic Status and Change in Mathematics
  • Volume: 17
  • Issue: 11
  • Date: February 15, 2011
  • ISSN: 1447-9494 (Print)
  • ISSN: 1447-9540 (Online)
  • DOI: https://doi.org/10.18848/1447-9494/CGP/v17i11/47338
  • Citation: Rugutt, John K., and Mohamed A. Nur-Awaleh. 2011. "Mathematics Learning Patterns Across Two Groups of African American Students: A Multilevel Approach." The International Journal of Learning: Annual Review 17 (11): 353-372. doi:10.18848/1447-9494/CGP/v17i11/47338.
  • Extent: 20 pages

All Rights Reserved

Copyright © 2011, Common Ground Research Networks, All Rights Reserved

Abstract

This study investigated individual achievement change over time in mathematics for two groups of Africa American learners, with and without free/reduced cost lunch and whether this differs from student to student. The major findings of the study showed that: 1) Initial differences in achievement levels were evident in mathematics at grade 4 with students not on lunch program demonstrating somewhat higher mean scores in mathematics; 2) mathematics intercepts for the two groups of learners (the lunch and non-lunch program) were statistically significant, an indication that students vary significantly in their knowledge of mathematics at entry into grade four; 3) mathematics slopes (rate of change) were positive and statistically significant from zero with the non-lunch group students demonstrating somewhat higher slope parameters in mathematics; 4) the heterogeneity in the regression slopes indicates presence of true individual differences among students’ learning growth rates, thus lending support to differences in students’ mathematics learning rates; 5) the variance estimates of mathematics slopes were statistically significant with students not on lunch program depicting higher variance parameters in mathematics, an indication that students not on lunch program were more variable in their mathematics learning rates than those on lunch program and that these differences were observed at lower grade levels; 6) the correlations between the intercept and slope within lunch programs were positive and statistically significant from zero, an indication that where a student starts in domain achievement is related to his or her future growth (mean level) in mathematics.