Lack of quantitative training among early-career ecologists: a survey of the problemand potential solutions

Barraquand, Frederic, Ezard. Thomas H. G., Jorgensen, Peter S., Zimmerman, Naupaka, Chamberlain, Scott, Salguero-Gomez, Roberto, Curran, Timothy J. and Poisot, Timothee (2014) Lack of quantitative training among early-career ecologists: a survey of the problemand potential solutions. PeerJ, 2013 1: 1-14. doi:10.7717/peerj.285


Author Barraquand, Frederic
Ezard. Thomas H. G.
Jorgensen, Peter S.
Zimmerman, Naupaka
Chamberlain, Scott
Salguero-Gomez, Roberto
Curran, Timothy J.
Poisot, Timothee
Title Lack of quantitative training among early-career ecologists: a survey of the problemand potential solutions
Journal name PeerJ   Check publisher's open access policy
ISSN 2167-8359
Publication date 2014-03-04
Sub-type Article (original research)
DOI 10.7717/peerj.285
Open Access Status DOI
Volume 2013
Issue 1
Start page 1
End page 14
Total pages 14
Place of publication London United Kingdom
Publisher PeerJ
Language eng
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.
Keyword Education
Statistics
Mathematics
Ecology student
Teaching
University curriculum
Student
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2015 Collection
School of Biological Sciences Publications
 
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