Do advanced mathematics skills predict success in biology and chemistry degrees?

Adkins, Michael; Noyes, Andrew

Abstract

The mathematical preparedness of science undergraduates has been a subject of debate for some time. This paper investigates the relationship between school mathematics attainment and degree outcomes in biology and chemistry across England, a much larger scale of analysis than has hitherto been reported in the literature. A unique dataset which links the National Pupil Database for England (NPD) and Higher Education Statistics Agency (HESA) data is used to track the educational trajectories of a national cohort of 16-year-olds through their school and degree programmes. Multilevel regression models indicate that students who completed advanced mathematics qualifications prior to their university study of biology and chemistry were no more likely to attain the best degree outcomes than those without advanced mathematics. The models do, however, suggest that success in advanced chemistry at school predicts outcomes in undergraduate biology and vice versa. There are important social background differences and the impact of the university attended is considerable. We discuss a range of possible explanations of these findings.

Citation

Adkins, M., & Noyes, A. (2018). Do advanced mathematics skills predict success in biology and chemistry degrees?. International Journal of Science and Mathematics Education, 16(3), 487-502. https://doi.org/10.1007/s10763-016-9794-y

• Journal Article Type: Article
• Acceptance Date: Dec 25, 2016
• Online Publication Date: Jan 13, 2017
• Publication Date: 2018-02
• Deposit Date: Jan 12, 2017
• Publicly Available Date: Jan 13, 2017
• Journal: International Journal of Science and Mathematics Education
• Print ISSN: 1571-0068
• Electronic ISSN: 1573-1774
• Publisher: Springer Verlag
• Peer Reviewed: Peer Reviewed
• Volume: 16
• Issue: 3
• Pages: 487-502
• DOI: https://doi.org/10.1007/s10763-016-9794-y
• Keywords: Mathematics, Biology, Chemistry, Degree outcomes, Multilevel modelling
• Public URL: https://nottingham-repository.worktribe.com/output/840425
• Publisher URL: http://link.springer.com/article/10.1007/s10763-016-9794-y
• Additional Information: The final publication is available at Springer via http://dx.doi.org/10.1007/s10763-016-9794-y.
• Contract Date: Jan 12, 2017