Effectively teaching statistics to chemical engineers as a core professional attribute

Batstone, Damien, Laycock, Bronwyn, Birkett, Greg, Wilson, Richard and Farre, Maria Jose (2013). Effectively teaching statistics to chemical engineers as a core professional attribute. In: Charles Lemckert, Graham Jenkins and Susan Lang-Lemckert, Proceedings of the 24th Annual Conference of the Australasian Association for Engineering Education: AAEE2013 Proceedings. AAEE 2013: 24th Annual Conference of the Australasian Association for Engineering Education, Gold Coast, QLD, Australia, (). 8-11 December, 2013.

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Name Description MIMEType Size Downloads
Author Batstone, Damien
Laycock, Bronwyn
Birkett, Greg
Wilson, Richard
Farre, Maria Jose
Title of paper Effectively teaching statistics to chemical engineers as a core professional attribute
Conference name AAEE 2013: 24th Annual Conference of the Australasian Association for Engineering Education
Conference location Gold Coast, QLD, Australia
Conference dates 8-11 December, 2013
Proceedings title Proceedings of the 24th Annual Conference of the Australasian Association for Engineering Education: AAEE2013 Proceedings
Place of Publication Nathan, QLD, Australia
Publisher Griffith School of Engineering, Griffith University
Publication Year 2013
Sub-type Fully published paper
Open Access Status
ISBN 9780992409906
Editor Charles Lemckert
Graham Jenkins
Susan Lang-Lemckert
Total pages 9
Collection year 2014
Language eng
Formatted Abstract/Summary
BACKGROUND Engineering statistics has been historically a challenge to teach due to a focus in engineering on uncertainty observation and process optimisation rather than population analysis and active experimentation. This is particularly the case in chemical engineering statistics, with a strong process focus, continuous rather than discrete data sets, and underlying system (and model) non-linearity. However, to properly understand and apply advanced techniques, a basic understanding of inferential statistics is required. This offers an opportunity to approach statistics from a process orientated approach at an early stage to allow chemical engineers to develop statistics capabilities as a core attribute.

PURPOSE In this paper, we approach statistics from a process engineering point of view, to implement process experimentation and statistics at an early stage (2nd year undergraduate level).

DESIGN/METHOD A course was developed linking inferential statistics to chemical engineering from the ground up, separating major topics into observation, estimation, and propagation of uncertainty. This was a mixed-mode course with lecture, practical, computing tutorial, and project management elements addressing all components. Due to classic inferential and engineering statistics not covering major elements at a basic level (e.g., nonlinear regression, uncertainty propagation), a substantial amount of new material needed to be developed.

RESULTS The course has now run consecutively for two years (126 students year 1, 145 students year 2) as CHEE2010 at UQ. 2013 results are not yet available, but 2012 indicated very strong student satisfaction with clear understanding of the links between professional attributes and the material being delivered. Pass rate was high (92%), and engagement was very high.

CONCLUSIONS There are strong benefits to teaching statistics in a process engineering context and this can provide vertical integration and ancillary skills development that provide a better subsequent programme experience, and substantially assist with key graduate attributes, particularly related to addressing risk and uncertainty.
Keyword Statistics, parameter estimation, uncertainty, risk
Parameter estimation
Uncertainty
Risk
Q-Index Code E1
Q-Index Status Provisional Code
Institutional Status UQ

 
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Created: Thu, 12 Dec 2013, 14:20:47 EST by Dr Damien Batstone on behalf of School of Chemical Engineering