Planning early for careers in science

Science

Volumn 312, Issue 5777, 2006, Pages 1143-1144

  Tai, Robert H ^a   Liu, Christine Qi ^a   Maltese, Adam V ^a   Fan, Xitao ^a  

^a UNIVERSITY OF VIRGINIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

INFORMATION DISSEMINATION; PROFESSIONAL ASPECTS; SOCIETIES AND INSTITUTIONS; STUDENTS;

SCIENCE DEGREE; YOUNG ADOLESCENTS;

EDUCATION;

YOUNG POPULATION;

CAREER PLANNING; EDUCATION PROGRAM; ENGINEERING; GOAL ATTAINMENT; GRADUATE; JUVENILE; LEADERSHIP; LOGISTIC REGRESSION ANALYSIS; MOTIVATION; NATURAL SCIENCE; PRIORITY JOURNAL; SCIENCE; SHORT SURVEY; STUDENT; UNITED STATES; ADOLESCENT; ARTICLE; BIOMEDICINE; DECISION MAKING; EDUCATION; HUMAN; LONGITUDINAL STUDY; MATHEMATICS; PROBABILITY; RISK; STATISTICAL MODEL;

ADOLESCENT; BIOLOGICAL SCIENCES; CAREER CHOICE; ENGINEERING; HUMANS; LOGISTIC MODELS; LONGITUDINAL STUDIES; MATHEMATICS; NATURAL SCIENCES; ODDS RATIO; PROBABILITY; SCIENCE; UNITED STATES;

EID: 33744483744     PISSN: 00368075     EISSN: 10959203     Source Type: Journal    
DOI: 10.1126/science.1128690     Document Type: Short Survey

References (10)

1. National Research Council, Rising Above the Gathering Storm: Energizing and Employing America for a Brighter Future (National Research Council, Washington, DC, 2005).
2. Data obtained through WebCASPAR (http://caspar.nsf.gov/).
3. National Center for Educational Statistics, User's Manual: National Education Longitudinal Study of 1988 (NCES, Washington, DC, 2004).
4. D. A. Rock, J. M. Pollack, "Psychometric report for the NELS:88 base test battery" (Tech. Rep. NCES 91-468, National Center for Educational Statistics, Washington, DC, 1991).
5. N. Hativa, M. Marincovich, Disciplinary Differences in Teaching and Learning: Implications for Practice (Jossey-Bass, San Francisco, CA, 1995).
6. Occupational classifications are highly complex and, in this analysis, only limited data were available on parents' specific occupations. We paid special attention to parental occupation in this analysis, because conventional wisdom suggest: that children whose parents have careers in science may be more likely to choose similar careers. However, the existing data related to parents' occupations were reported in categories that did not specify whether jobs were science related. As a result, we chose to use the broad categories of professional versus nonprofessional.
7. For a more detailed discussion of this technique, please see J. S. Long, J. Freese, Regression Models for Categorical Dependent Variables Using STATA® (STATA, College Station, TX, 2001).
8. National Science Board, An Emerging and Critical Problem of the Science and Engineering Labor Force: A Companion to the Science and Engineering Indicators 2004 (National Science Board, Washington, DC, 2004); available online (www.nsf.gov/statistics/nsb0407/nsb0407.pdf).
9. S. Dillon, "Schools cuts back subjects to push reading and math," The New York Times, 26 March 2006 (www.nytimes.com/2006/03/26/ education/26child.html).
10. This study was funded in part through a grant from NSF, Directorate of Education and Human Resources, Division of Research, Evaluation, and Communication, Research on Learning and Education Program (REC 0440002, Project Crossover). We thank L. E. Suter (NSF), D. Herschbach (Harvard University), and D. R. Webb (Proctor and Gamble) for their comments.