Barraquand, F., Ezard, T.H.G., Jorgensen, P.S. et al. (5 more authors) (2014) Lack of quantitative training among early-career ecologists: a survey of the problem and potential solutions. PeerJ, 2. e285. ISSN 2167-8359
Abstract
Proficiency in mathematics and statistics is essential to modern ecological science, yet few studies have assessed the level of quantitative training received by ecologists. To do so, we conducted an online survey. The 937 respondents were mostly early-career scientists who studied biology as undergraduates. We found a clear self-perceived lack of quantitative training: 75% were not satisfied with their understanding of mathematical models; 75% felt that the level of mathematics was “too low” in their ecology classes; 90% wanted more mathematics classes for ecologists; and 95% more statistics classes. Respondents thought that 30% of classes in ecology-related degrees should be focused on quantitative disciplines, which is likely higher than for most existing programs. The main suggestion to improve quantitative training was to relate theoretical and statistical modeling to applied ecological problems. Improving quantitative training will require dedicated, quantitative classes for ecology-related degrees that contain good mathematical and statistical practice.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2014 Barraquand et al. Distributed under Creative Commons CC-BY 3.0 |
Keywords: | Education; Statistics; Mathematics; Ecology student; Teaching; University curriculum; Student |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Science (Sheffield) > School of Biosciences (Sheffield) > Department of Animal and Plant Sciences (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 06 Jan 2017 13:04 |
Last Modified: | 23 Jun 2017 15:37 |
Published Version: | https://doi.org/10.7717/peerj.285 |
Status: | Published |
Publisher: | PeerJ |
Refereed: | Yes |
Identification Number: | 10.7717/peerj.285 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:108167 |