Laboratory Replication of Scientific Discovery Processes

Fourteen subjects were tape-recorded while they undertook to find a law to summarize numerical data they were given. The source of the data was not identified, nor were the variables labeled semantically. Unknown to the subjects, the data were measurements of the distances of the planets from the sun and the periods of their revolutions about it—equivalent to the data used by Johannes Kepler to discover his third law of planetary motion. Four of the 14 subjects discovered the same law as Kepler did (the period varies as the 3/2 power of the distance), and a fifth came very close to the answer. The subiects' protocols provide a detailed picture of the problem-solving searches they engaged in, which were mainly, but not exclusively, in the space of possible functions for fitting the data, and provide explanations as to why some succeeded and the others failed. The search heuristics used by the subjects are similar to those embodied in the BACON program, computer simulation of certain scientific discovery processes. The experiment demonstrates the feasibility of examining some of the processes of scientific discovery by recreating, in the laboratory, discovery situations of substantial historical relevance. It demonstrates also, that under conditions rather similar to those of the original discoverer, a law can be rediscovered by persons of ordinary intelligence (i.e., the intelligence needed for academic success in a good university). The data for the successful subjects reveal no “creative” processes in this kind of a discovery situation different from those that are regularly observed in all kinds of problem-solving settings.     

Concept Discovery in a Scientific Domain

The scientific reasoning strategies used to discover a new concept in a scientific domain were investigated in two studies. An innovative task in which subjects discover new concepts in molecular biology was used. This task was based upon one set of experiments that Jacob and Monod used to discover how genes are controlled, and for which they were awarded the Nobel prize. In the two studies reported in this article, subjects were taught some basic facts and experimental techniques in molecular biology, using a simulated molecular genetics laboratory on a computer. Following their initial training, they were then asked to discover how genes are controlled by other genes. In Study 1, subjects found no evidence that was consistent with their initial hypothesis. Subjects then set one of two goals for conducting experiments and evaluating data. One goal was to search for evidence consistent with the current hypothesis (and they did not attend to the features of discrepant findings); none of the subjects who only had this goal succeeded at discovering how the genes were controlled. Other subjects in Study 1 used a different goal: Upon noticing evidence inconsistent with their current hypothesis, these subjects set a new goal of attempting to explain the cause of the discrepant findings. Using this goal, a subset of these subjects discovered the correct solution to the problem. Study 2 was conducted to test the hypothesis that subjects' goals of finding evidence consistent with their current hypothesis blocks consideration of alternate hypotheses and generation of new goals, it was predicted that if subjects could achieve their initial goal of discovering evidence consistent with their current hypothesis, they would then attend to particular features of discrepant evidence and solve the problem. To test this prediction, an additional mechanism of genetic control that was consistent with subjects' initial goal was added to the genes. Here, subjects had to discover two mechanisms of control: one mechanism consistent with their current hypothesis, and one inconsistent with their hypothesis. Twice as many subjects reached the correct solution in Study 2 than in Study 1. The findings of the two studies indicate that goals provide a powerful constraint on the cognitive processes underlying scientific reasoning and that the types of goals that are represented determine many of the reasoning errors that subjects make.     

科学发现的真正方法

一般情况下,很多人误认为作为科学常用的数学逻辑方法就是科学发现的方法,作者通过列举了归纳法和演绎法的不足,指出它们的错误,提出科学发现的真正方法应该是怀疑论和逆推论。认为科学家要像一位神秘的侦探,充分发挥自己的想象力和创造力,不断地进行质疑和反思;持有怀疑态度的想象是创造力的源泉;他们不应该迷信任何人,而应该大胆怀疑,敢于创新。他还从科学史角度列举了很多科学发现的事例,无不说明批判性的创造性思维的重要性。科学家并不是坐在实验室里对乌鸦的颜色、太阳明天升起、每天都将喂养火鸡等进行归纳概括。——伯顿·S·格特…     

Collaborative Discovery in a Scientific Domain

This study compares Pairs of subjects with Single subjects in a task of discovering scientific laws with the aid of experiments. Subjects solved a molecular genetics task in a computer micro-world (Dunbar, 1993). Pairs were more successful in discovery than Singles and participated more actively in explanatory activities (i.e., entertaining hypotheses and considering alternative ideas and justifications). Explanatory activities were effective for discovery only when the subjects also conducted crucial experiments. Explanatory activities were facilitated when paired subjects made requests of each other for explanation and focused on them. The study extends from individual to collaborative discovery activities the importance to the discovery process of setting goals to find hypotheses and evidence (Dunbar, 1993) and to construct explanations of phenomena and processes encountered in examples (Chi, Bassok, Lewis, & Glaser, 1989).     

Cognitive Shocks: Scientific Discovery and Mobilization

Science, through the generation of new knowledge, has the ability to transform commonly held beliefs. Occasionally scientific discoveries produce “cognitive shocks”, which refer to new information that can restructure an individual's beliefs or understandings about the world in a way that affects attitudes toward, and support for, social change. Social movements can play a key role in deploying, framing, and in some cases, producing, cognitive shocks that affect public opinion and political advocacy. Three case studies of scientific cognitive shocks illuminate the interplay between social movements and science and the resulting effects on attitudes and activism: studies finding that smoking cigarettes and exposure to secondhand smoke have harmful health effects, studies suggesting that sexual orientation has a biological basis, and scientific evidence for cetacean intelligence. Cognitive shocks emphasize how compelling shifts in conceptual and logical perceptions can act as powerful motivators of activism and, by doing so, complement existing work done in social movement literature on the role of emotions in mobilization. It is likely that a combination of emotional and rational motivators sustain activism, and a more thorough understanding of how both of these processes affect mobilization can serve to better elucidate the mechanisms underlying opinions toward, and action taken for, social change.     

Scientific Discovery as Creative Exploration: Faraday's Experiments

In this article, I address the distance between historical and psychological approaches to creativity (particularly cognitive approaches). I argue that neither can get very far without the other, and I offer examples from the creative work of Michael Faraday, the eminent 19th-century physicist. These examples display similarities between fine detail of Faraday's creative work and the broad sweep of his development and illustrate the tension between historians' attention to particular features of creativity and cognitive scientists' desire for general, preferably computable features. I conclude with a discussion of the difficult issue of finding a common language based on agreement about appropriate levels of abstraction.     

Scientific Discovery on Positive Data via Belief Revision

A model of inductive inquiry is defined within a first-order context. Intuitively, the model pictures inquiry as a game between Nature and a scientist. To begin the game, a nonlogical vocabulary is agreed upon by the two players along with a partition of a class of structures for that vocabulary. Next, Nature secretly chooses one structure (the real world) from some cell of the partition. She then presents the scientist with a sequence of atomic facts about the chosen structure. With each new datum the scientist announces a guess about the cell to which the chosen structure belongs. To succeed in his inquiry, the scientist's successive conjectures must be correct all but finitely often, that is, the conjectures must converge in the limit to the correct cell. A special kind of scientist selects his hypotheses on the basis of a belief revision operator. We show that reliance on belief revision allows scientists to solve a wide class of problems.     

Learning With Real Machines or Diagrams: Application of Knowledge to Real-World Problems

In this study, we investigated how learning from different media, either from real pulley systems or from simple line diagrams, affected mechanical learning and problem solving. Novice subjects learned about pulley systems by comparing the efficiency of different systems and receiving feedback on their accuracy. The main outcome measures were subjects' ability to compare pulley system efficiency, their level of mechanical reasoning, and their ability to apply knowledge of system efficiency and construction details. Experiment 1 showed that (a) subjects learning with the two types of media made equal improvement on the learning task, and (b) all subjects showed an increase in quantitative understanding as they learned, but (c) subjects who learned hands-on, by manipulating real pulley systems, solved application problems more accurately than those who learned from diagrams. Experiment 2 showed that both the realism of the stimuli and the opportunity to manipulate systems contributed to the improved performance on application problems.     

由血管生成抑制剂的发现谈福克曼的科研思维

1　奇怪的现象———问题的发现60年代初期 ,福克曼和他的同事在研究无细胞的血代用品使培养中的甲状腺细胞保持存活的能力时 ,在甲状腺表面放了少量兔子的黑瘤细胞。根据使用正常血液组织培养的经验 ,他们设想黑瘤细胞会迅速生长下去。结果却出乎他们意料 :当黑瘤细胞长到形成豌豆大小的肿瘤时 ,便停止生长了。肿瘤为什么会停止生长 ?一闪而过的现象 ,并没有被福克曼轻易放过 ,“这个问题让我为之工作了很多年。”[1]2　合理的解释———假设的提出反复比较出现不同结果的培养条件 ,福克曼发现 ,问题的关键在于血代用品和血细胞的不同。因…     

科学发现学习的新近研究

随着建构主义学习理论的发展及计算机模拟等技术在教育中的广泛应用,发现学习受到了越来越多的重视,且研究的重点从概念发现学习转向了科学发现学习。该文综述了有关科学发现学习的认知过程及机制的新近研究,包括双重搜索模型、科学推理研究等。     

初二学生的科学观及其与科学发现学习的关系

该研究旨在通过问卷法和实验法考察初二学生在自然科学领域中的认识论观念及其对学习过程和策略的影响.研究一发现,在科学的动态性、有限性、客观性、理论价值取向、公众性以及对科学的态度兴趣等六种基本观念上,初二学生总体上持有较混合的看法;对科学的积极态度与学习者的物理学习成绩相关显著.研究二考察了科学观对科学发现学习的影响.科学的公众性观念与灵活应用测验成绩相关显著,科学的客观性观念及智力水平对科学发现学习中的控制性实验策略有重要影响.     

The Processes of Scientific Discovery: The Strategy of Experimentation

Hans Krebs' discovery, in 1932, of the urea cycle was a major event in biochemistry. This article describes a program, KEKADA, which models the heuristics Hans Krebs used in this discovery. KEKADA reacts to surprises, formulates explanations, and carries out experiments in the same manner as the evidence in the form of laboratory notebooks and interviews indicates Hans Krebs did. Furthermore, we answer a number of questions about the nature of the heuristics used by Krebs, in particular: How domain-specific are the heuristics? To what extent are they idiosyncratic to Krebs? To what extent do they represent general strategies of problem-solving search? The relative generality of KEKADA allows us to view the control structure of KEKADA and its domain-independent heuristics as a model of scientific experimentation that should apply over a broad domain.     

Building Cognition: The Construction of Computational Representations for Scientific Discovery

Novel computational representations, such as simulation models of complex systems and video games for scientific discovery (Foldit, EteRNA etc.), are dramatically changing the way discoveries emerge in science and engineering. The cognitive roles played by such computational representations in discovery are not well understood. We present a theoretical analysis of the cognitive roles such representations play, based on an ethnographic study of the building of computational models in a systems biology laboratory. Specifically, we focus on a case of model‐building by an engineer that led to a remarkable discovery in basic bioscience. Accounting for such discoveries requires a distributed cognition (DC) analysis, as DC focuses on the roles played by external representations in cognitive processes. However, DC analyses by and large have not examined scientific discovery, and they mostly focus on memory offloading, particularly how the use of existing external representations changes the nature of cognitive tasks. In contrast, we study discovery processes and argue that discoveries emerge from the processes of building the computational representation. The building process integrates manipulations in imagination and in the representation, creating a coupled cognitive system of model and modeler, where the model is incorporated into the modeler's imagination. This account extends DC significantly, and we present some of the theoretical and application implications of this extended account.     

The Journey from Discovery to Scientific Change: Scientific Communities,Shared Models,and Specialised Vocabulary

Scientific communities as social groupings and the role that such communities play in scientific change and the production of scientific knowledge is currently under debate. I examine theory change as a complex social interaction among individual scientists and the scientific community, and argue that individuals will be motivated to adopt a more radical or innovative attitude when confronted with striking similarities between model systems and a more robust understanding of specialised vocabulary. Two case studies from the biological sciences, Barbara McClintock and Stanley Prusiner, help motivate the idea that sharing of models and specialised vocabulary fill the gap between discovery and scientific change by promoting the dispersal of important information throughout the scientific community.     

Diagrams as sketches

This article puts forward the notion of ??evolving diagram?? as an important case of mathematical diagram. An evolving diagram combines, through a dynamic graphical enrichment, the representation of an object and the representation of a piece of reasoning based on the representation of that object. Evolving diagrams can be illustrated in particular with category-theoretic diagrams (hereafter ??diagrams*??) in the context of ??sketch theory,?? a branch of modern category theory. It is argued that sketch theory provides a diagrammatic* theory of diagrams*, that it helps to overcome the rivalry between set theory and category theory as a general semantical framework, and that it suggests a more flexible understanding of the opposition between formal proofs and diagrammatic reasoning. Thus, the aim of the paper is twofold. First, it claims that diagrams* provide a clear example of evolving diagrams, and shed light on them as a general phenomenon. Second, in return, it uses sketches, understood as evolving diagrams, to show how diagrams* in general should be re-evaluated positively.     

Why Feynman Diagrams Represent

There are two distinct interpretations of the role that Feynman diagrams play in physics: (i) they are calculational devices, a type of notation designed to keep track of complicated mathematical expressions; and (ii) they are representational devices, a type of picture. I argue that Feynman diagrams not only have a calculational function but also represent: they are in some sense pictures. I defend my view through addressing two objections and in so doing I offer an account of representation that explains why Feynman diagrams represent. The account that I advocate is a version of that defended by Kendall Walton, which provides us with a basic characterization of the way that representations in general work and is particularly useful for understanding distinctively pictorial representations – in Walton’s terms, depictions. The question of the epistemic function of Feynman diagrams as pictorial representations is left for another time.     

Diagrams: Socrates and Meno's slave

Abstract

When do two mental items belong to the same life? We could be content with the answer ‐just when they have certain volitional qualities in common. An affinity is noted between that theory and Berkeley's early doctrine of the self. Some rivals of the volitional theory invoke a spiritual or physical owner of mental items. They run a risk either of empty formality or of causal superstition. Other rivals postulate a non‐transitive and symmetrical relation in the set of mental items. They must allow in consequence either for joint ownership of one and the same mental item, or for incompatible simultaneous decisions by one and the same person, or for new forms of death. This makes them disquieting. Another rival invokes a transitive and symmetrical relation defined in terms of co‐consciousness. Even that allows for incongruous simultaneities. The volitional theory is free from such disadvantages.     

Word Diagrams in Teaching Classical Conditioning

The Psychological Record - The present experiment examined the value of word diagrams on the concept learning of university students. All students learned the concept of classical conditioning by...     

Teaching Legal Theory with Venn Diagrams

Venn diagrams, which are widely used in introductory logic courses, provide a convenient and illuminating way of presenting the various theories concerning the nature of law. When combined with the Aristotelian square of opposition, these diagrams show not only how the theories are related to one another, logically, which is essential to understanding them, but also which theories are compossible. One surprising result of this approach is that it shows the substantive compatibility of the theories of law set forth by H. L. A. Hart and Ronald Dworkin, who are usually pitted against one another. I show, through quotation and visual representation, that there is no essential disagreement between these jurisprudential stalwarts concerning the relation of law and morality.