Start the week with one of the founding fathers of cognitive science: in ‘The scientist as problem solver‘, Herb Simon (1916-2001) gives a short retrospective of his scientific career.
To tell the story of the research he has done, he advances a thesis: “The Scientist is a problem solver. If the thesis is true, then we can dispense with a theory of scientific discovery – the processes of discovery are just applications of the processes of problem solving.”. Quite aside from the usefulness of this perspective, the paper is an reminder of intoxicating possibility of integration across the physical, biological and social sciences: Simon worked on economics, management theory, complex systems and artificial intelligence as well as what we’d call now cognitive psychology.
He uses his own work on designing problem solving algorithms to reflect on how he – and other scientists – can and should make scientific progress. Towards the end he expresses what would be regarded as heresy in many experimentally orientated psychology departments. He suggests that many of his most productive investigations lacked a contrast between experimental and control conditions. Did this mean they were worthless, he asks. No:
…You can test theoretical models without contrasting an experimental with a control condition. And apart from testing models, you can often make surprising observations that give you ideas for new or improved models…
Perhaps it is not our methodology that needs revising so much as the standard textbook methodology, which perversely warns us against running an experiment until precise hypotheses have been formulated and experimental and control conditions defined. How do such experiments ever create surprise – not just the all-too-common surprise of having our hypotheses refuted by facts, but the delight-provoking surprise of encountering a wholly unexpected phenomenon? Perhaps we need to add to the textbooks a chapter, or several chapters, describing how basic scientific discoveries can be made by observing the world intently, in the laboratory or outside it, with controls or without them, heavy with hypotheses or innocent of them.
REFERENCE
Simon, H. A. (1989). The scientist as problem solver. Complex information processing: The impact of Herbert A. Simon, 375-398.
Mind Hacks 
Three thoughts:
1- If you look at the discovery process as circular, i.e., theory –> hypothesis –> observation –> re-evaluating theory –> hypothesis, etc., then it doesn’t really matter where you start. Experimentation can be done deductively (as is traditionally taught) or inductively!
2- One advantage of Simon’s (inductive) approach is that it minimizes confirmation bias.
3- Which is better? When I teach Research Methods, I tell my students “whichever approach your professor is biased towards…if you define “better” as your receiving a higher grade.”
The title of this article caught my attention, as in my experience working with scientists I have become convinced that in the real and practical world they are the worst problem solvers of all.
The problem a scientist has to solve is, for the most part, how to isolate an observation from the effects of the environment, and in this way find a fundamental principle of nature. This might be good enough to find a formula or express a theory. But, as businessmen and engineers know well, there is no way you can isolate anything from the environment. Thus, to solve a real-world problem, every small detail –even the detail that there’s no way of knowing– has to be seriously considered and provided for. At this, scientists suck.
A friend of mine has a saying, “Scientists can predict what will happen, other things being equal. Engineers know that other things are never equal.”