Scientific Model Construction Research Articles

Multiple Levels of Heuristic Reasoning Processes in Scientific Model Construction.

Science historians have recognized the importance of heuristic reasoning strategies for constructing theories, but their extent and degree of organization are still poorly understood. This paper first consolidates a set of important heuristic strategies for constructing scientific models from three books, including studies in the history of genetics and electromagnetism, and an expert think-aloud study in the field of mechanics. The books focus on qualitative reasoning strategies (processes) involved in creative model construction, scientific breakthroughs, and conceptual change. Twenty four processes are examined, most of which are field-general, but all are heuristic in not being guaranteed to work. An organizing framework is then proposed as a four-level hierarchy of nested reasoning processes and subprocesses at different size and time scales, including: Level (L4) Several longer-time-scale Major Modeling Modes, such as Model Evolution and Model Competition; the former mode utilizes: (L3) Modeling Cycle Phases of Model Generation, Evaluation, and Modification under Constraints; which can utilize: (L2) Thirteen Tactical Heuristic Processes, e.g., Analogy, Infer new model feature (e.g., by running the model), etc.; many of which selectively utilize: (L1) Grounded Imagistic Processes, namely Mental Simulations and Structural Transformations. Incomplete serial ordering in the framework gives it an intermediate degree of organization that is neither anarchistic nor fully algorithmic. Its organizational structure is hypothesized to promote a difficult balance between divergent and convergent processes as it alternates between them in modeling cycles with increasingly constrained modifications. Videotaped think-aloud protocols that include depictive gestures and other imagery indicators indicate that the processes in L1 above can be imagistic. From neurological evidence that imagery uses many of the same brain regions as actual perception and action, it is argued that these expert reasoning processes are grounded in the sense of utilizing the perceptual and motor systems, and interconnections to and possible benefits for reasoning processes at higher levels are examined. The discussion examines whether this grounding and the various forms of organization in the framework may begin to explain how processes that are only sometimes useful and not guaranteed to work can combine successfully to achieve innovative scientific model construction.

Modeling intentional agency: a neo-Gricean framework

This paper analyzes three contrasting strategies for modeling intentional agency in contemporary analytic philosophy of mind and action, and draws parallels between them and similar strategies of scientific model-construction. Gricean modeling involves identifying primitive building blocks of intentional agency, and building up from such building blocks to prototypically agential behaviors. Analogical modeling is based on picking out an exemplary type of intentional agency, which is used as a model for other agential types. Theoretical modeling involves reasoning about intentional agency in terms of some domain-general framework of lawlike regularities, which involves no detailed reference to particular building blocks or exemplars of intentional agency (although it may involve coarse-grained or heuristic reference to some of them). Given the contrasting procedural approaches that they employ and the different types of knowledge that they embody, the three strategies are argued to provide mutually complementary perspectives on intentional agency.

The role of disciplinary perspectives in an epistemology of scientific models

The purpose of this article is to develop an epistemology of scientific models in scientific research practices, and to show that disciplinary perspectives have crucial role in such an epistemology. A transcendental (Kantian) approach is taken, aimed at explanations of the kinds of questions relevant to the intended epistemology, such as “How is it possible that models provide knowledge about aspects of reality?” The approach is also pragmatic in the sense that the questions and explanations must be adequate and relevant to concrete scientific practice. First it is explained why the idea of models as representations in terms of similarity or isomorphism between a model and its target is too limited as a basis for this epistemology. An important finding is that the target-phenomenon is usually not something that can be observed in a straightforward manner, but requires both characterization in terms of measurable variables and subsumption under (scientific) concepts. The loss of this basis leads to a number of issues, such as: how can models be interpreted as representations if models also include conceptually meaningful linguistic content; how can researchers identify non-observable real-world target-phenomena that are then represented in the model; how do models enable inferential reasoning in performing epistemic tasks by researchers; and, how to justify scientific models. My proposal is to deal with these issues by analyzing how models are constructed, rather than by looking at ready-made models. Based on this analysis, I claim that the identification of phenomena and the construction of scientific models is guided and also confined by the disciplinary perspective within which researchers in a scientific discipline have learned to work. I propose a Kuhnian framework by which the disciplinary perspective can be systematically articulated. Finally, I argue that harmful forms of subjectivism, due to the loss of the belief that models objectively represent aspects of reality, can be overcome by making the disciplinary perspective(s) in a research project explicit, thereby enabling its critical assessment, for which the proposed Kuhnian framework provides a tool.

Development of the Teacher Training Material for Scientific Model Construction Activity on the Unit of Excretion

Development of the Teacher Training Material for Scientific Model Construction Activity on the Unit of Excretion

Idealization and abstraction in scientific modeling

I argue that we cannot adequately characterize idealization and abstraction and the distinction between the two on the grounds that they have distinct semantic properties. By doing so, on the one hand, we focus on the conceptual products of the two processes in making the distinction and we overlook the importance of the nature of the thought processes that underlie model-simplifying assumptions. On the other hand, we implicitly rely on a sense of abstraction as subtraction, which is unsuitable for explicating scientific model construction. Instead, I argue that a sense of abstraction as extraction is more suitable. Finally, I suggest a different way to distinguish the two processes that avoids these problems. Namely, that both idealization and abstraction could be understood as particular modes of application of the same cognitive process: selective attention.

중학교 과학수업에서 과학적 모형의 사회적 구성을 촉진하는 교사 스캐폴딩 분석

중학교 과학수업에서 과학적 모형의 사회적 구성을 촉진하는 교사 스캐폴딩 분석

과학적 모형 구성 과정에서 나타난 사고 질문의 개념적 자원 활성화의 이해 -인식론적 프레이밍과 위치 짓기 프레이밍을 중심으로-

과학적 모형 구성 과정에서 나타난 사고 질문의 개념적 자원 활성화의 이해 -인식론적 프레이밍과 위치 짓기 프레이밍을 중심으로-

The (dis)unity of nursing science.

This paper looks at the implications of contemporary work in philosophy of science for nursing science. Early work on the nature of theories in nursing was strongly influenced by logical empiricism, and this influence remains even long after nurse scholars have come to reject logical empiricism as an adequate philosophy of science. Combined with the need to establish nursing as an autonomous profession, nursing theory's use of logical empiricism has led to serious conceptual problems. Philosophers of science have also rejected many of the central tenets of logical empiricism, including its focus on the logical justification of theories and the idea that science is, or should be, unified. Instead, there has been an increasing focus on the practice of science, which in turn has led to a pluralist understanding of science that emphasizes the construction of scientific models that are appropriate for certain purposes or in certain contexts. I suggest that this approach to philosophy of science may provide better resources for nursing science.

과학적 모델의 사회적 구성 수업에서 구현된 두 과학 교사의 실천적 지식의 내용

이 연구는 과학적 모델의 사회적 구성 과정을 목적으로 설계된 수업을 실행한 두 과학 교사의 과학 수업에서 형성되었던 실천적 지식의 내용을 Elbaz가 제시한 실천적 지식의 5가지 내용 범주를 준거로 조사하였다. 이를 위해 두 과학 교사의 과학 수업에 대한 참여 관찰 및 수업 촬영 비디오 자료를 바탕으로 행위 동안의 반성 과정 및 수업 후 면담에 반영된 교사들의 내러티브를 통한 행위에 대한 반성 과정을 질적으로 분석하였다. 연구 결과, 1) 두 과학 교사의 수업 실행 과정에서 학생들이 과학적인 모델을 구성할 수 있도록 지원하는 비계를 제공할 때 교과내용 지식에 대한 실천적 지식이 발현되는 것을 볼 수 있었다. 2) 교육 과정에 대한 교사의 지식이 어려운 과학 개념의 이해와 전달에서 주어진 학습 목표에 적절한 모델 형성으로 수업의 목표를 변화하는데 중요함을 알 수 있었다. 3) 참여 교사의 교수법 지식의 실행은 과학적 모델의 사회적 구성 수업의 의도에 맞추어 학생들의 모둠 활동과 모델 생성 활동을 지원하는 방향으로 변화하였다. 4) 교사의 자아에 대한 실천적 지식은 학생들이 모둠 활동을 통해 과학적 모델을 구성하는 것을 지원할 수 있으려면, 교사는 조력자, 안내자, 그리고 격려자로서 자신의 역할을 인식하고 변화된 역할을 적절하게 수행하는 것이 중요함을 보여주었다. 5) 두 참여 교사의 학습 환경에 대한 실천적 지식은 수업을 진행하는 동안 각 모둠과 교사가 형성한 상호작용의 양상을 통해 발현되었으며, 두 교사는 함께 뛰는 운동 선수 또는 그라운드 옆의 코치와 같은 양상을 보였다. 이상의 결과를 바탕으로 과학적 모델 구성에 대한 영역 특이적 실천적 지식의 특성에 대해 논의하였다. This study investigated two science teachers' practical knowledge shaped during their science classes which intend to realize social construction of scientific models. The teachers' practical knowledge was qualitatively examined in terms of five content categories defined by Elbaz through the reflection-in-action based on video data of their teaching as well as the reflection-on-action based on their narratives and interview data obtained after their classes. The results shows: 1) two science teachers implemented their practical knowledge on appropriate subject matter knowledge when they provided students with scaffoldings to support building scientific models during the classes. 2) The teachers' knowledge about science curriculum played important roles to change the purposes of the classes from the transmission of difficult science concepts to the construction of scientific model appropriate to learning goals. 3) The teachers' implementation of pedagogical knowledge changed toward supporting students' group activities and model generations aligned to the intention of social construction of scientific models. 4) The teachers' practical knowledge about their 'selves' showed that a teacher's perception and implementation of his/her roles of helper, guide, or facilitator are important for students to construct scientific models through group activities. 5) The two teachers' practical knowledge the milieu of schooling is realized by their modes of interactions with student groups during their classes. Two teachers acted like a co-player with his students or like a coach to students near a playground. We discussed domain-specific characteristics about scientific model construction.

Documenting the use of expert scientific reasoning processes by high school physics students

We describe a methodology for identifying evidence for the use of three types of scientific reasoning. In two case studies of high school physics classes, we used this methodology to identify multiple instances of students using analogies, extreme cases, and Gedanken experiments. Previous case studies of expert scientists have indicated that these processes can be central during scientific model construction; here we code for their spontaneous use by students. We document evidence for numerous instances of these forms of reasoning in these classes. Most of these instances were associated with motion- and force-indicating depictive gestures, which we take as one kind of evidence for the use of animated mental imagery. Altogether, this methodology shows promise for use in highlighting the role of nonformal reasoning in student learning and for investigating the possible association of animated mental imagery with scientific reasoning processes.

The Relation between Idealisation and Approximation in Scientific Model Construction

The notions of ‘idealisation’ and ‘approximation’ are strongly linked to the question of ‘how our theories represent the phenomena in their scope’. Although there is no consensus amongst Philosophers on the nature of the process of idealisation and how it affects theoretical representation, at the level of science education much can be gained from the insights of existing philosophical analyses. Traditionally, teaching methodologies treat the observed divergence between theoretical predictions and experimental data by appealing to the more common-sensical notion of ‘approximation’. The use of the latter notion, however, to explicate discrepancies between theory and experiment obscures the theory/experiment relation. It does so, I argue, because from the viewpoint of scientific modelling ‘approximation’ either depends upon or piggybacks on ‘idealisation’.

A Theory of Scientific Model Construction: The Conceptual Process of Abstraction and Concretisation

The process of abstraction and concretisation is a label used for an explicative theory of scientific model-construction. In scientific theorising this process enters at various levels. We could identify two principal levels of abstraction that are useful to our understanding of theory-application. The first level is that of selecting a small number of variables and parameters abstracted from the universe of discourse and used to characterise the general laws of a theory. In classical mechanics, for example, we select position and momentum and establish a relation amongst the two variables, which we call Newton’s 2nd law. The specification of the unspecified elements of scientific laws, e.g. the force function in Newton’s 2nd law, is what would establish the link between the assertions of the theory and physical systems. In order to unravel how and with what conceptual resources scientific models are constructed, how they function and how they relate to theory, we need a view of theory-application that can accommodate our constructions of representation models. For this we need to expand our understanding of the process of abstraction to also explicate the process of specifying force functions etc. This is the second principal level at which abstraction enters in our theorising and in which I focus. In this paper, I attempt to elaborate a general analysis of the process of abstraction and concretisation involved in scientific- model construction, and argue why it provides an explication of the construction of models of the nuclear structure.