| Francis Stage
NSF
Participation in math/science pipeline
FINAL REPORT:
Study 1: Science achievement growth trajectories: Understanding factors related to gender and racial-ethnic differences in precollege science achievement. (Co-authors: P. Muller, and J. Kinzie)
The purpose of this study was to gain a more complete understanding of the differences in science, mathematics and engineering education among racial-ethnic and gender subgroups by exploring factors related to precollege science achievement and growth rates. Using multi-wave, longitudinal data from the first three waves of the National Education Longitudinal Study (NELS:88) we examined precollege science achievement and growth rates. Previous analyses have examined science achievement at a fixed point in time (Hanson, 1996) or used two-wave difference scores which are problematic for measuring student growth (Willet, 1988). This study extends previous analyses by using a multilevel model technique to also study the structure and predictors of individual growth in science knowledge and reasoning. Specifically, we sought to identify the factors that are related to racial-ethnic and gender differences in precollege science achievement growth.
Study 2: Symbolic Discourse and Understanding in a College Mathematics Classroom
This paper focused on students' understandings of lectures in a college mathematics course. Videotaped segments of the class focusing on symbolic notation in the lecture were replayed individually to the instructor and to students who were then interviewed and asked to explain material being presented. Transcripts of students' interviews varied when compared with the instructor's explanation. When test results over the material were compared with quality of students' explanations, discrepancies arose. Discussion focuses on the nature of symbolic discourse in college mathematics classes as well as the often limited performance expectationsfor students by instructors, particularly in mathematics courses.
Study 3: The Use and Interpretation of Logistic Regression in Higher Educatio Journals: 1988-1999. (Co-authors: C.J. Peng, T.H. So, E.P. St. John)
This paper examines the use and interpretation of logistic regression in three leading higher education research journals from 1988 to 1999. The journals were selected because of their emphasis on research, relevance to higher education issues, broad coverage of research topics, and reputable editorial policies. The term "logistic regression" encompasses logit modeling, probit modeling, and tobit modeling and the significance tests of their estimates. A total of 52 articles were identified as using logistic regression. Our review uncovered an increasingly sophisticated use of logistic regression for a wide range of topics. At the same time, there continues to be confusion over terminology. The sample sizes used did not always achieve a desired level of stability in the parameters estimated. Discussion of results in terms of delta-P's and marginal probabilities was not always cautionary, according to definitions. The review is concluded with recommendations for journal editors and researchers in formulating appropriate editorial policies and practice for applying the versatile logistic regression technique and in communicating its results with readers of higher education research.
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