A Model of “Integrated Scientific Method” i and its Application for the ...

A Model of "Integrated Scientific Method"

i

and its Application for the Analysis of Instruction

? 1997 : A PhD dissertation submitted by Craig F. Rusbult, under the supervision of Professor James H. Stewart, at the University of Wisconsin-Madison.

ABSTRACT:

A model of `integrated scientific method' (ISM) was constructed as a framework for describing the process of science in terms of activities (formulating a research problem, and inventing and evaluating actions -- such as selecting and inventing theories, evaluating theories, designing experiments, and doing experiments -- intended to solve the problem) and evaluation criteria (empirical, conceptual, and cultural-personal). Instead of trying to define the scientific method, ISM is intended to serve as a flexible framework that -- by varying the characteristics of its components, their integrated relationships, and their relative importance -- can be used to describe a variety of scientific methods, and a variety of perspectives about what constitutes an accurate portrayal of scientific methods.

This framework is outlined visually and verbally, followed by an elaboration of the framework and my own views about science, and an evaluation of whether ISM can serve as a relatively neutral framework for describing a wide range of science practices and science interpretations.

ISM was used to analyze an innovative, guided inquiry classroom (taught by Susan Johnson, using Genetics Construction Kit software) in which students do simulated scientific research by solving classical genetics problems that require effect-to-cause reasoning and theory revision. The immediate goal of analysis was to examine the `science experiences' of students, to determine how the `structure of instruction' provides opportunities for these experiences. Another goal was to test and improve the descriptive and analytical utility of ISM.

In developing ISM, a major objective was to make ISM educationally useful. A concluding discussion includes controversies about "the nature of science" and how to teach it, how instruction can expand opportunities for student experience, and how goal-oriented intentional learning (using ISM) might improve the learning, retention, and transfer of thinking skills. Potential educational applications of ISM could involve its use for instructional analysis or design, or for teaching students in the classroom; or ISM and IDM (a closely related, generalized `integrated design method') could play valuable roles in a `wide spiral' curriculum designed for the coordinated teaching of thinking skills, including creativity and critical thinking, across a wide range of subjects.

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CHAPTER 1

AN OVERVIEW

Introduction In every field of learning, at every level of education, creativity and critical thinking are essential. These complementary skills are intimately integrated in the problem-solving methods used by scientists. The ability to combine creative and critical thinking in a mutually supportive system, as exemplified by scientists in their pursuit of scientific knowledge, can play a valuable role in education. The practical value of `scientific thinking skills' is described, by a group of scientists and educators who are trying to improve science education, There are certain thinking skills associated with science, mathematics, and technology that young people need to develop during their school years. These are mostly, but not exclusively, mathematical and logical skills that are essential tools for both formal and informal learning and for a lifetime of participation in society as a whole. (Rutherford & Ahlgren, 1990, p. 171) Because these skills are considered so important, many educators are making a large investment of time, effort, and money, with the goal of developing instructional methods that will be more effective in helping students improve their thinking skills. As a way to contribute to this ongoing effort, an explicit articulation of the problem-solving methods used by scientists seems to have the potential to become a powerful tool for improving education. My dissertation research attempts to develop this potential more fully by pursuing the following objectives: 1. Construct an integrative model of `scientific method'. 2. Use this model to analyze the instruction -- including both the planned activities and the

ways in which these activities are put into action, by teacher and students, in the classroom -- that occurs in an innovative, inquiry-oriented science course.

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These two objectives are described briefly in the remainder of Chapter 1, and will be discussed more thoroughly in Chapters 2 and 3.

Objective 1 A model of `integrated scientific method' (ISM) is a descriptive framework that can be used to describe the activities of scientists -- what they think about, and what they do -- during scientific research. The ISM framework is based on my own knowledge of science (from personal experience working in research labs, reading about the activities of scientists, and talking with scientists) and on my analysis of science. When constructing this framework I have adopted a multidisciplinary approach, selecting and synthesizing existing ideas from scientists and from contemporary scholars who study the history, philosophy, psychology, and sociology of science. Thus, the components of ISM are conventional; it is my expectation that some added value will come from their organization into a coherent, integrated model. The process of development has been guided by two main goals. The first goal is to construct ISM as a framework that can be used to describe scientific activity in a wide variety of contexts, and to express divergent viewpoints about what constitutes an accurate portrayal of scientific method. The second goal is for ISM to be useful as a tool that can improve education by facilitating the analysis and design of instruction, and by helping teachers and students to understand `the nature of science' and to develop their thinking skills. The content of ISM is expressed using two educationally useful formats: a visual model that shows how multiple factors enter into the generation, evaluation, and application of scientific theories, and a written commentary describing the substance and interrelationships of these factors. A brief sketch of ISM follows: Motivated by curiosity and by questions arising from inadequately explained observations, scientists invent one or more theories that, if true, might explain what they have observed. A theory -- in association with supplementary theories, and relative to competitive theories -- is evaluated using empirical factors (comparisons of experimental observations with `if-then' deductive predictions) and conceptual factors (judgments about internal consistency and logical

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structure, and external consistency with other theories). During the activities of science -- which include selecting or inventing theories, evaluating theories, designing experiments, and doing experiments -- scientists are also influenced by cultural-personal factors that operate in the scientific community and in society as a whole.

As described above, the first goal is to develop ISM as a framework for describing science. But since I agree with the current consensus of scholars that no single `method' is used by all scientists, I am not trying to discover or define the scientific method. Instead, ISM has been constructed as a framework that provides structure yet is flexible. This flexibility -- by per-mitting variations in defining the characteristics of different activities and evaluation factors, describing the interrelationships between them, and placing emphasis on them -- gives ISM the capability of describing the wide variety of actual scientific practice (as it has occurred in various times and places, in different fields of science) and the wide range of views about how to interpret science and scientists. The second goal, to develop ISM as a framework that is useful for improving education, begins in Objective 1 and continues in Objective 2.

Objective 2 A major goal of many educators is to improve the teaching of thinking skills, including the types of skills that are used by scientists in their pursuit of knowledge. When an instructional program is developed in an effort to achieve this goal, an evaluation of this program, for the purpose of determining the ways in which it contributes to achieving educational objectives, is an important component of curriculum decisions and instructional development. Evaluation provides essential input for making curriculum decisions about instructional policies (such as deciding whether to continue, discontinue, or modify existing instruction) and also for developing new approaches to instruction. Reliable knowledge provides a firm foundation for the evaluation that occurs during curriculum decisions and instructional development. One source of knowledge is empirical data that involves learning outcomes (what students learn) or instructional methods (including what the teacher does, and the activities students are asked to do) or student actions (what students do during an

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instructional activity). Based on these three types of data -- which will be called outcome-data, methods-data, and action-data -- an evaluation of instructional effectiveness can be primarily empirical or conceptual.

What I am calling an empirical evaluation of instruction occurs by gathering empirical outcome-data. For example, educators might examine students who had participated in the program, to assess their thinking skills and their understanding of the nature of science, and how these were affected by the program. Then this data is used to evaluate the effectiveness of the program.

What I am calling conceptual evaluation can occur by using either methods-data or methodsdata plus action-data. As an example of a conceptual evaluation, consider an extreme case where the dual objectives of a program are to help students learn about the nature of science and to improve their thinking skills, yet the methods-data indicates that the nature of science is never discussed, nor are thinking strategies, and students are never given an opportunity to engage in scientific problem solving. Even with no outcome-data, it is easy to predict that this program -- due to the obvious mismatch between objectives and methods -- will not be successful in achieving its objectives.

But compared with this simple example in which there is an extreme mismatch, in most real-life situations the application of conceptual criteria will be more difficult, the meaning of conceptual evaluation will be open to a wider range of interpretations, and the conclusions that are reached will be viewed with caution. For example, conceptual criteria might be useful in defining conditions that are "necessary but not sufficient" for successful instruction -- i.e., if a certain condition (such as a good match between methods and objectives) is absent the instruction probably will not be successful, but if this condition is present there is no guarantee of success, because many other factors (besides the specified condition) will influence the outcomes of instruction, and might also be necessary if the instruction is to be effective.

If a conceptual evaluation is to have practical value, it should be based on a deep, accurate understanding of what happens during instruction. This understanding begins with the collection of reliable data for either methods or methods-and-actions, and continues with an interpretation of this data. My claim is that an understanding of instruction can be enhanced by using ISM to analyze

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