Mathematics, Foreign Language, and Science Coursetaking and the NELS:88 Transcript Data. Working Paper No. 2003-01
Author: Burkam, David T.
Date: 2003-01-00
Type: Reports - Evaluative
Subjects: Course Selection (Students),High School Students,Mathematics Instruction,Second Language Instruction,Science Instruction,Credits,Grades (Scholastic),Educational Attainment,Enrollment Trends,Correlation,Prediction,Biology,Physics,Chemistry

This report describes efforts to create and test variables measuring students' high-school coursetaking in mathematics, foreign language, and science, using data from the National Education Longitudinal Study (NELS) NELS:88 transcript file (National Center for Education Statitstics (NCES) projects 1.2.4.13 and 1.2.4.39). The first project (exploring mathematics coursetaking) was completed in September, 1996. The second project (exploring foreign language and science coursetaking) was completed in December, 1997. Both are summarized in this report. As the NCES-sponsored study of mathematics coursetaking and curriculum using the NELS school effects supplement (HSES) data makes use of these same constructs, it made sense to carefully explore the best way to capture the mathematics coursetaking construct with transcript data. As the first section of this report describes in some detail, the authors have conceptualized this construct in two ways: (1) course credits and (2) a pair of pipeline indices based on the most advanced course in a particular subject that students took in high school. Although they also explored the idea of creating a &quot;weighted grades&quot; measure, they argue against this idea in the report. An important part of the report is the exploration of the mathematics course credit and mathematics pipeline measures in bivariate and multivariate analyses (summarized in the second section). The multivariate regression models explore the measures used in two ways: (1) as outcomes, investigating coursetaking as a function of students' demographic and academic background, and (2) as predictors of mathematics achievement, taking students' background characteristics into account. This section is designed to demonstrate to future researchers the possible use of this and other pipeline measures. Building on the success of earlier work in mathematics, parts 3 and 4 of this report explore similar pipeline measures in foreign language and science coursetaking. Foreign language coursework, like mathematics coursework, is relatively sequential, and conceptualizing and constructing language pipelines is relatively straightforward. Science coursework, on the other hand, is far less sequential, and the underlying logic behind pipeline measures is necessarily more complicated. The Appendix includes SPSS programs used to generate all the described measures. The authors conclude the report with some recommendations based on their analyses. The results of these small studies are instructive. They hope that their variables and the analyses that demonstrate their &quot;behavior&quot; may be useful to other researchers who wish to investigate how high-school coursetaking influences students' achievement and learning in mathematics, foreign language, and/or science. Although many researchers like to construct variables measuring important constructs themselves, others may find the work helps to make their work easier, more coherent, and more consistent with other relevant studies.