The importance of understanding: Model space moderates goal specificity effects

The three-space theory of problem solving predicts that the quality of a learner's model and the goal specificity of a task interact on knowledge acquisition. In Experiment 1 participants used a computer simulation of a lever system to learn about torques. They either had to test hypotheses (nonspecific goal), or to produce given values for variables (specific goal). In the good- but not in the poor-model condition they saw torque depicted as an area. Results revealed the predicted interaction. A nonspecific goal only resulted in better learning when a good model of torques was provided. In Experiment 2 participants learned to manipulate the inputs of a system to control its outputs. A nonspecific goal to explore the system helped performance when compared to a specific goal to reach certain values when participants were given a good model, but not when given a poor model that suggested the wrong hypothesis space. Our findings support the three-space theory. They emphasize the importance of understanding for problem solving and stress the need to study underlying processes.     

A selectionist explanation for the success and failures of science

I argue that van Fraassen’s selectionist explanation for the success of science is superior to the realists’ explanation. Whereas realists argue that our current theories are successful because they accurately reflect the structure of the world, the selectionist claims that our current theories are successful because unsuccessful theories have been eliminated. I argue that, unlike the explanation proposed by the realist, the selectionist explanation can also account for the failures of once successful theories and the fact that sometimes two competing theories are both equally successful.

A Pragmatic Case against Pragmatic Scientific Realism

Pragmatic Scientific Realism (PSR) urges us to take up the realist aim or the goal of truth although we have good reason to think that the goal can neither be attained nor approximated. While Newton-Smith thinks that pursuing what we know we cannot achieve is clearly irrational, Rescher disagrees and contends that pursuing an unreachable goal can be rational on pragmatic grounds—if in pursuing the unreachable goal one can get indirect benefits. I have blocked this attempt at providing a pragmatic justification for the realist aim of PSR on precisely the same pragmatic grounds—since there is a competing alternative to PSR, and the alternative can provide whatever indirect benefits PSR can offer while being less risky than it is, prudential reasoning favours the alternative to PSR. This undermines the pragmatic case for the realist aim of science since the instrumentalist alternative does not aim at the truth.     

Emerging Infectious Diseases: Coping with Uncertainty

The world’s scientific community must be in a state of constant readiness to address the threat posed by newly emerging infectious diseases. Whether the disease in question is SARS in humans or BSE in animals, scientists must be able to put into action various disease containment measures when everything from the causative pathogen to route(s) of transmission is essentially uncertain. A robust epistemic framework, which will inform decision-making, is required under such conditions of uncertainty. I will argue that this framework should have reasoning at its center and, specifically, that forms of reasoning beyond deduction and induction should be countenanced by scientists who are confronted with emerging infectious diseases. In previous articles, I have presented a case for treating certain so-called traditional informal fallacies as rationally acceptable forms of argument that can facilitate scientific inquiry when little is known about an emerging disease. In this article, I want to extend that analysis by highlighting the unique features of these arguments that makes them specially adapted to cope with conditions of uncertainty. Of course, such a view of the informal fallacies must at least be consistent with the reasoning practices of scientists, and particularly those scientists (viz. epidemiologists) whose task it is to track and respond to newly emerging infectious diseases. To this end, I draw upon examples of scientific reasoning from the UK’s BSE crisis, a crisis that posed a significant threat to both human and animal health.

Perelman’s Pseudo-Argument as Applied to the Creationism Controversy

If you want to challenge or at least weaken the adhesion to a system of values, you can basically adopt two radically opposed rhetorical strategies. Either you will attack the system in a frontal way: for instance, fundamentalists or fascists deny any validity to democratic values and human rights. Or you will pretend to argue from within the system (by saying that you accept some of its basic premises), while subtly distorting the process of reasoning in order to get to your conclusions. If the audience is naïve or poorly informed, you will be able to defend positions that are fundamentally at odds with liberal-democratic values while seeming to argue from inside the system. I would like to show how such a process of “perverse” translation works in the context of the Darwinism/Creationism “controversy”. The attacks on the teaching of evolutionary biology began approximately one century ago. The way Creationists have argued and changed several times their rhetorical strategies seems very interesting to me, in that it exemplifies an important contemporary phenomenon, which I call “perverse translation” or “the wolf in the sheepfold”.     

Learning from the existence of models: On psychic machines,tortoises, and computer simulations

Using four examples of models and computer simulations from the history of psychology, I discuss some of the methodological aspects involved in their construction and use, and I illustrate how the existence of a model can demonstrate the viability of a hypothesis that had previously been deemed impossible on a priori grounds. This shows a new way in which scientists can learn from models that extends the analysis of Morgan (1999), who has identified the construction and manipulation of models as those phases in which learning from models takes place.     

Models and fictions in science

Non-actual model systems discussed in scientific theories are compared to fictions in literature. This comparison may help with the understanding of similarity relations between models and real-world target systems. The ontological problems surrounding fictions in science may be particularly difficult, however. A comparison is also made to ontological problems that arise in the philosophy of mathematics.

Perilous thoughts: comment on van Fraassen

Bas van Fraassen’s empiricist reading of Perrin’s achievement invites the question: whose doubts about atoms did Perrin put to rest? This comment recontextualizes the argument and applies the notion of empirical grounding to some contemporary work in behavioral biology.     

科技人员创造动机与创造力的研究

本研究初步探讨了我国科技人员创造动机与创造力的关系及其基本特征。 1 74名科技人员回答了成就目标、内部动机与外部动机、创造动机和创造力问卷。研究结果表明我国科技人员有较高的创造力和创造动机水平 ,在动机中内部动机水平最高。在动机与创造力的关系上 ,内部动机对创造力的直接与间接影响均达到了显著水平 ,外部动机对创造力的负面影响没有达到显著水平 ,任务目标对创造力无影响 ,自我目标对创造力的积极影响未达到显著水平。