A New Mechanism for Transfer Between Conceptual Domains in Scientific Discovery and Education

Confronted with problems or situations that do not yield toknown theories and world views, scientists and students are alike. Theyare rarely able to directly build a model or a theory thereof. Rather,they must find ways to make sense of the circumstances using theircurrent knowledge and adjusting what is recognized in the process. Thisway of thinking, using past ways of perceiving the physical world tobuild new ones does not follow a logical path and cannot be described astheory revision. Likewise, in many situations it is awkward, indeedoften impossible, to resort to analogical reasoning to account for it.This paper presents a new mechanism, called `tunnel effect', that mayexplain, in part, how scientists and students reason while constructinga new conceptual domain. `Tunnel effect' is also contrasted withanalogical reasoning.     

地质学科技期刊中四组常见词使用辨析

科技期刊及其编辑在促进科技术语规范化表达的进程中承担着重要责任。在地质学科技论文编校过程中,经常发现学科术语的混用、错用现象。文章列举了四组常见词汇,通过中国知网文献检索发现其混淆使用现象比较普遍。借助词典、地质行业标准、全国科技名词委审定公布的科技名词及百度学术搜索引擎,对“勘查”“勘察”、 “降水量”“降雨量”的词义及使用语境进行分析,对“平硐”“平洞”、 “硐室”“洞室”的正误使用进行辨析。最后提出建议:期刊学科编辑需要加强对科技术语规范化表达的重视,工作中遇到把握不准的词要查证辨析,做到改必有据;编辑部可以通过期刊网站等平台公布易混淆词汇,促进作者和读者重视科技术语的规范化表达,并在科技论文写作中正确使用。     

Model-Based and Manipulative Abduction in Science

What I call theoretical abduction (sentential and model-based)certainly illustrates much of what is important in abductive reasoning, especially the objective of selecting and creating a set of hypotheses that are able to dispense good (preferred) explanations of data, but fails to account for many cases of explanation occurring in science or in everyday reasoning when the exploitation of the environment is crucial. The concept of manipulative abduction is devoted to capture the role of action in many interesting situations: action provides otherwise unavailable information that enables the agent to solve problems by starting and performing a suitable abductive process of generation or selection of hypotheses. Many external things, usually inert from the epistemological point of view, can be transformed into what I callepistemic mediators, which are illustrated in the last part of the paper, together with an analysis of the related notions of ``perceptual and inceptual rehearsal' and of ``external representation'.     

Main Problems of Diagrammatic Reasoning. Part I: The generalization problem

The paper attempts to analyze in some detail the main problems encountered in reasoning using diagrams, which may cause errors in reasoning, produce doubts concerning the reliability of diagrams, and impressions that diagrammatic reasoning lacks the rigour necessary for mathematical reasoning. The paper first argues that such impressions come from long neglect which led to a lack of well-developed, properly tested and reliable reasoning methods, as contrasted with the amount of work generations of mathematicians expended on refining the methods of reasoning with formulae and predicate calculus. Next, two main groups of problems occurring in diagrammatic reasoning are introduced. The second group, called diagram imprecision, is then briefly summarized, its detailed analysis being postponed to another paper. The first group, called collectively the generalization problem, is analyzed in detail in the rest of the paper. The nature and causes of the problems from this group are explained, methods of detecting the potentially harmful occurrences of these problems are discussed, and remedies for possible errors they may cause are proposed. Some of the methods are adapted from similar methods used in reasoning with formulae, several other problems constitute new, specifically diagrammatic ways of reliable reasoning.     

Multiple Roles for Analogies in the Genesis of Fluid Mechanics: How Analogies Can Cooperate with Other Heuristic Strategies

When Johann and Daniel Bernoulli founded fluid dynamics they encountered several problems. To go beyond the vision of Newtonian particles, a new set of images was needed in order to deal with the spatial extensibility and lack of form of fluids. I point to evidence that analogy was an essential abductive strategy in the creation of this imagery. But its heuristic behavior is complex: analogy can provide an initial model or proto-model that establishes the starting point of a theoretical process, but it can play other roles as well. The historical genesis analyzed here shows that the participation of analogy in physicists’ creativity is not so restricted and that its richness opens up the field for very different roles and strategies in model-based discovery processes. Analogies can crop up intermittently in the evolution of a theory; and they can cooperate with images, extreme case reasoning and thought experiments, and even activate these processes at origin. Although it may seem that the contributions of analogy are generative in the sense of helping to discover new aspects of reality, we must stress the evaluative function that sometimes is performed by analogical reasoning in order to gain confidence. The study of the Bernoulli’s genesis of the foundations of fluid dynamics generates interesting hypotheses about the multiple roles that analogy can play in scientific model-based reasoning.     

Visual Models in Analogical Problem Solving

Visual analogy is believed to be important in human problem solving. Yet, there are few computational models of visual analogy. In this paper, we present a preliminary computational model of visual analogy in problem solving. The model is instantiated in a computer program, called Galatea, which uses a language for representing and transferring visual information called Privlan. We describe how the computational model can account for a small slice of a cognitive-historical analysis of Maxwell’s reasoning about electromagnetism.     

Greenhouse Effects in Global Warming based on Analogical Reasoning

Using an analogy in science and everyday life is a double-edged sword because they are accompanied by alternative ideas, in addition to scientific concepts. Schools and public education explain global warming by making a common analogy between this phenomenon and greenhouse effects (Chen in Philos Cogn Sci 105–114, 2012). Unfortunately, this analogy sometimes produces various incorrect explanatory mental models. To construct a correct understanding of global warming, it is necessary: first, to investigate the attributes of analogical reasoning; second, to understand these features by restructuring the greenhouse analogy; and third, to explore the problems and benefits of the greenhouse analogy. The characteristics of relations, rather than objects, must be mapped according to the principle of systematicity, but the public tends to preserve the attributes of the base domain, which is mapped relatively easily. In conclusion, certain facets of the prevailing greenhouse analogy cause a distorted public view of climate change. We must use the greenhouse analogy and yet simultaneously emphasize the relations and attributes highlighted and hidden in the analogy during evaluation.     

Comparing resemblance measures

In the paper some types of equivalences over resemblance measures and some basic results about them are given. Based on induced partial orderings on the set of unordered pairs of units a dissimilarity between two resemblance measures over finite sets of units can be defined. As an example, using this dissimilarity standard association coefficients between binary vectors are compared both theoretically and computationally.Extended version of the paper presented at DISTANCIA'92, June 22–26, 1992, Rennes, France. This work was supported in part by the Ministry for Science and Technology of Slovenia, J2-6191-101-94. We would like to thank the editor and two anonymous referees for numerous remarks and suggestions that significantly improved the presentation of the material.     

Mining Supervised Classification Performance Studies: A Meta-Analytic Investigation

There have been many comparative studies of classification methods in which real datasets are used as a gauge to assess the relative performance of the methods. Since these comparisons often yield inconclusive or limited results on how methods perform, it is often believed that a broader approach combining these studies would shed some light on this difficult question. This paper describes such an attempt: we have sampled the available literature and created a dataset of 5807 classification results. We show that one of the possible ways to analyze the resulting data is an overall assessment of the classification methods, and we present methods for that particular aim. The merits and demerits of such an approach are discussed, and conclusions are drawn which may assist future research: we argue that the current state of the literature hardly allows large-scale investigations. This work was sponsored by the MOD Corporate Research Programme, CISP, as part of a larger project on technology assessment. We would like to express our appreciation to Andrew Webb for his support throughout the entire project, and to Wojtek Krzanowski for valuable comments on a draft of this paper. We would also like to thank the anonymous referees for some very interesting comments, some of which we hope to pursue in future work.     

Covariance/Invariance: A Cognitive Heuristic in Einstein's Relativity Theory Formation

Relativity Theory by Albert Einstein has been so far littleconsidered by cognitive scientists, notwithstanding its undisputedscientific and philosophical moment. Unfortunately, we don't have adiary or notebook as cognitively useful as Faraday's. But physicshistorians and philosophers have done a great job that is relevant bothfor the study of the scientist's reasoning and the philosophy ofscience. I will try here to highlight the fertility of a `triangulation'using cognitive psychology, history of science and philosophy of sciencein starting answering a clearly very complex question:why did Einstein discover Relativity Theory? Here we arenot much concerned with the unending question of precisely whatEinstein discovered, that still remains unanswered, for we have noconsensus over the exact nature of the theory's foundations(Norton 1993). We are mainly interested in starting to answer the`how question', and especially the following sub-question: what(presumably) were his goals and strategies in hissearch? I will base my argument on fundamental publications ofEinstein, aiming at pointing out a theory-specific heuristic, settingboth a goal and a strategy: covariance/invariance.The result has significance in theory formation in science, especiallyin concept and model building. It also raises other questions that gobeyond the aim of this paper: why was he so confident in suchheuristic? Why didn't many other scientists use it? Where did he keep ? such a heuristic? Do we have any other examples ofsimilar heuristic search in other scientific problemsolving?     

Defeasible Reasoning + Partial Models: A Formal Framework for the Methodology of Research Programs

In this paper we show that any reasoning process in which conclusions can be both fallible and corrigible can be formalized in terms of two approaches: (i) syntactically, with the use of defeasible reasoning, according to which reasoning consists in the construction and assessment of arguments for and against a given claim, and (ii) semantically, with the use of partial structures, which allow for the representation of less than conclusive information. We are particularly interested in the formalization of scientific reasoning, along the lines traced by Lakatos’ methodology of scientific research programs. We show how current debates in cosmology could be put into this framework, shedding light on a very controversial topic.     

Towards a Theory of Mathematical Argument

In this paper, I assume, perhaps controversially, that translation into a language of formal logic is not the method by which mathematicians assess mathematical reasoning. Instead, I argue that the actual practice of analyzing, evaluating and critiquing mathematical reasoning resembles, and perhaps equates with, the practice of informal logic or argumentation theory. It doesn’t matter whether the reasoning is a full-fledged mathematical proof or merely some non-deductive mathematical justification: in either case, the methodology of assessment overlaps to a large extent with argument assessment in non-mathematical contexts. I demonstrate this claim by considering the assessment of axiomatic or deductive proofs, probabilistic evidence, computer-aided proofs, and the acceptance of axioms. I also consider Jody Azzouni’s ‘derivation indicator’ view of proofs because it places derivations—which may be thought to invoke formal logic—at the center of mathematical justificatory practice. However, when the notion of ‘derivation’ at work in Azzouni’s view is clarified, it is seen to accord with, rather than to count against, the informal logical view I support. Finally, I pose several open questions for the development of a theory of mathematical argument.     

Direct multicriteria clustering algorithms

In a multicriteria clustering problem, optimization over more than one criterion is required. The problem can be treated in different ways: by reduction to a clustering problem with the single criterion obtained as a combination of the given criteria; by constrained clustering algorithms where a selected critetion is considered as the clustering criterion and all others determine the constraints; or by direct algorithms. In this paper two types of direct algorithms for solving multicriteria clustering problem are proposed: the modified relocation algorithm, and the modified agglomerative algorithm. Different elaborations of these two types of algorithms are discussed and compared. Finally, two applications of the proposed algorithms are presented. Elaborated version of the talks presented at the First Conference of the International Federation of Classification Societies, Aachen, 1987, at the International Conference on Social Science Methodology, Dubrovnik, 1988, and at the Second Conference of the International Federation of Classification Societies, Charlottesville, 1989. This work was supported in part by the Research Council of Slovenia.     

Logics in Scientific Discovery

In this paper I argue for a place for logic inscientific methodology, at the same level asthat of computational and historicalapproaches. While it is well known that a awhole generation of philosophers dismissedLogical Positivism (not just for the logicthough), there are at least two reasons toreconsider logical approaches in the philosophyof science. On the one hand, the presentsituation in logical research has gone farbeyond the formal developments that deductivelogic reached last century, and new researchincludes the formalization of several othertypes of reasoning, like induction andabduction. On the other hand, we call for abalanced Philosophy of Science, one inwhich both methods, the formal and thehistorical may be complementary, togetherproviding a pluralistic view of science, inwhich no method is the predominant one.     

Problems with Peirce's Concept of Abduction

Abductive reasoning takes place in forming``hypotheses' in order to explain ``facts.' Thus, theconcept of abduction promises an understanding ofcreativity in science and learning. It raises,however, also a lot of problems. Some of them will bediscussed in this paper. After analyzing thedifference between induction and abduction (1), Ishall discuss Peirce's claim that there is a ``logic'of abduction (2). The thesis is that this claim can beunderstood, if we make a clear distinction betweeninferential elements and perceptive elements ofabductive reasoning. For Peirce, the creative act offorming explanatory hypotheses and the emergence of``new ideas' belongs exclusively to the perceptive sideof abduction. Thus, it is necessary to study the roleof perception in abductive reasoning (3). A furtherproblem is the question whether there is arelationship between abduction and Peirce's concept of``theorematic reasoning' in mathematics (4). Both formsof reasoning could be connected, because both arebased on perception. The last problem concerns therole of instincts in explaining the success ofabductive reasoning in science, and the questionwhether the concept of instinct might be replaced bymethods of inquiry (5).     

探天人奥秘 索古今真义：《天人古义》评介

该文是对中国科技大学李志超教授科学史论著《天人古义-中国科学史论纲》所作的介绍和评议,文章认为,《天人古义》是一部优秀的科学史读物,它内涵丰蕴,立意新疑,在多种学科领域尤其是在中国科学思想史的研究上,有许多精深独到的见解,该书作者之所论,有些是被传统史学和哲学所忽略了的大问题。在具体科学史问题的基础上,该书也有许多重要突破,在研究方法和风格上,该书同样存在诸多值得称道之处。     

Remodeling the Past

In some of the papers in which she develops and defends the mental modelview of thought experiments in physics, Nersessian expresses the belief that her account has implications for thought experiments in other domains as well. In this paper, I argue, firstly, that counterfactual reasoning has a legitimate place in historical inquiry, and secondly, that the mental model view can account for such "alternative histories". I proceed as follows. Firstly, I review the main accounts of thought experiments in physics and point at some explanatory advantages of the mental model view. Subsequently, I argue that historians cannot dispense with counterfactual reasoning altogether and qualify a number of principled objections against the explicit use of alternative histories for theoretical purposes. Finally, I show that the mental model view can account for such thought experiments in history.     

建构科学人文主义的桥梁——基于东南大学“自然辩证法”课程教学调研

在我国研究生培养体制中,自然辩证法是针对理、工、农、医专业的硕士研究生开设的一门政治理论公共课,定位是马克思主义哲学的一个重要组成部分。课程的授课对象与学科性质决定了其文理融合的独特属性。笔者基于东南大学自然辩证法课程的教学调研,认为自然辩证法本身兼具科学理性与人文特质;而自然辩证法教学,则是从实践层面引导理工科研究生体察科学精神与人文精神的内在关联,促进科学文化与人文文化的沟通、实现科学人文主义的重要桥梁与现实路径。