2005 - Estimating Correlates of Growth Between Mathematics and Science Achievement Via a Multivariate Multilevel Design with Latent Variables

Attribution: Ma, Lingling, & Ma, Xin
Researchers: Lingling MaXin Ma
University Affiliation: University of Kentucky
Email: n.ma@uky.edu
Research Question:
Examined the relationship between growth in mathematics and science achievement during middle and high school among students and schools, and we demonstrated that such a model was more sensitive to this relationship.
Published: 1
Journal Name or Institutional Affiliation: Studies in Educational Evaluation
Journal Entry: Vol. 31, No. 1, pp. 79-98
Year: 2005
Findings:
  • The correlation between the rates of growth in mathematics and science achievement was not zero but not large, and student and school characteristics had little or no influence on the correlation.
  • The correlation between the average rates of growth in mathematics and science achievement was rather strong among schools (indicating consistency between the average rates of growth in mathematics and science achievement among schools); conclude that this consistency was influenced by student and school characteristics.
  • Perhaps it is school curriculum and instruction rather than school context and climate that promote balanced learning in mathematics and science. Implies that learning difficulties in mathematics and science are indeed likely to occur simultaneously among students.
  • Relationship between the rates of growth in mathematics and science achievement was stronger at the school level than at the student level.
Keywords: Academic AchievementCompositionMathScienceSESSES CompositionTeacher QualityRegions: NationalMethodologies: QuantitativeResearch Designs: Secondary Survey DataAnalysis Methods: Regression Sampling Frame:National
Sampling Types: RandomAnalysis Units: SchoolStudentData Types: Quantitative-Panel Data
Data Description:
  • Longitudinal Study of American Youth (LSAY)
  • Six-year panel study of mathematics and science education of public middle and high school students
  • About 60 students in the 7th grade (approximate age of 11 – 12) were randomly selected from each of the 52 sampled schools, and these students were followed for six years from Grade 7 to Grade 12.
  • The sample contained 3116 students in the 7th grade, 2798 in the 8th grade, 2748 in the 9th grade, 2583 in the 10th grade, 2409 in the 11th grade, and 2215 in the 12th grade.
  • Students wrote mathematics and science achievement tests and completed a student questionnaire annually.
  • Parent, teacher, and principal questionnaires were additional instruments in the LSAY that were regularly administered to collect information about student and school characteristics
  • DV: Math achievement (measured as scores in basic skills, algebra, geometry, and quantitative literacy); science achievement (measured as scores in biology, physics, and environmental science)
  • IV: Student characteristics (i.e., gender, age, and race-ethnicity), family characteristics (i.e., parental socioeconomic status (SES), number of parents, and number of siblings), race, parental SES (measured as mother’s and father’s educational and occupational status, and household possessions), family structure; school-level measures included enrollment, location, percent of minority students, percent eligible for federal lunch assistance, teaching experience, educational level of teachers, teacher to student ratio, computer to student ratio, disciplinary environment, parental involvement, principal leadership, teacher autonomy, teacher commitment, general support for mathematics, extracurricular activity
Theoretical Framework:
Relevance:
Archives: K-12 Integration, Desegregation, and Segregation Abstracts