I was one of those who responded negatively, but I did so because the emphasis was on computer simulation modelling. I think that modelling in the broad sense is an essential part of science, but I object to the idea that anything comprehensible without a powerful computer is not a model.
To give a practical example, the principle of conservation of energy is a useful model, even though some ecologists (notably Larry Slobodkin) object to it. If I see a system where secondary production is higher than primary production it motivates me to ask where the extra energy came from, a point which often confuses my experimental colleagues. Currently I am modelling the environmental impacts of fish farms, and while my calleagues understand the importance of quantitative data on nutrient and carbon fluxes which can be plugged into computer models, they are confused about how to include the stench of hydrogen sulfide bubbling up from the bottom, or the presence of slugworms and dead fish - but surely any model of environmental impact should include these factors! One frustrating aspect of the emphasis on teaching computer simulation models is that even though they implement systems of equations, which is just one kind of model, they often ignore fundamental mathematical issues such as stability and resilience. As for non-mathematical models, although they are subject to the same protocols as with mathematical models, because they are not considered models they are not evaluated critically enough. I recall once at a fisheries workshop advancing some ideas about the spawning behaviour of cod, only to be told that the matter had already been settled by experimental work which I should have known. Afterwards I asked for the reference, and it turned out to be a paper on spawning behaviour of Tilapia in Lake Victoria. As a modeller I would be inclined to ask whether a freshwater pelagic fish in Africa is a good model for a demersal gadoid in the Atlantic Ocean, but the idea that assumptions must be clearly stated and critically reviewed did not occur to anyone else. I have published a number of papers on modelling, including the following, and while I have read other papers reflecting similar views, I am currently on holidays in Florida and do not have references handy. Bill Silvert Silvert, William. 2001. Modelling as a Discipline. Int. J. General Systems 30: 261-282. A Polish translation was published in the "Projektowanie i Systemy" volume XVII in 2004. ----- Original Message ----- From: "John Petersen" <[EMAIL PROTECTED]> To: <[email protected]> Sent: Friday, January 20, 2006 11:23 AM Subject: Re: Role of modeling courses in the undergraduate curriculum > Back in September of '05 I sent out an announcement about a conference > at Oberlin College that would focus on the role of computation and > modeling in the undergraduate curriculum. I was very interested when > several colleagues responded on this list-serve expressing a rather > negative view regarding the value of teaching modeling to > undergraduates. To summarize, the arguments seemed to focus on the > notion that the development of specialized and technical computer skills > involved in modeling represents a counterproductive distraction. Has > anyone seen this argument made anywhere in any literature? I would > greatly appreciate references to papers or book chapters that adopt this > view or otherwise criticize the value of modeling education for > undergraduates. Beyond that I would appreciate suggestions for > literature that takes any position on the pedagogical role of modeling > in the undergraduate curriculum. > > Thanks! > John Petersen > Associate Professor of Environmental Studies and Biology > Oberlin College >
