Wastewater treatment models in teaching and training: The mismatch between education and requirements for jobs

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Abstract

As mathematical modeling of wastewater treatment plants has become more common in research and consultancy, a mismatch between education and requirements for model-related jobs has developed. There seems to be a shortage of skilled people, both in terms of quantity and in quality. In order to address this problem, this paper provides a framework to outline different types of model-related jobs, assess the required skills for these jobs and characterize different types of education that modelers obtain "in school" as well as "on the job". It is important to consider that education of modelers does not mainly happen in university courses and that the variety of model related jobs goes far beyond use for process design by consulting companies. To resolve the mismatch, the current connection between requirements for different jobs and the various types of education has to be assessed for different geographical regions and professional environments. This allows the evaluation and improvement of important educational paths, considering quality assurance and future developments. Moreover, conclusions from a workshop involving practitioners and academics from North America and Europe are presented. The participants stressed the importance of non-technical skills and recommended strengthening the role of realistic modeling experience in university training. However, this paper suggests that all providers of modeling education and support, not only universities, but also software suppliers, professional associations and companies performing modeling tasks are called to assess and strengthen their role in training and support of professional modelers. © IWA Publishing 2009.

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Hug, T., Benedetti, L., Hall, E. R., Johnson, B. R., Morgenroth, E., Nopens, I., … Vanrolleghem, P. A. (2009). Wastewater treatment models in teaching and training: The mismatch between education and requirements for jobs. Water Science and Technology, 59(4), 745–753. https://doi.org/10.2166/wst.2009.595

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