Creative Model Construction in Scientists and Students. The Role of Analogy, Imagery, and Mental Simulation

Transcription

1 Creative Model Construction in Scientists and Students The Role of Analogy, Imagery, and Mental Simulation Clement_FM.indd i

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3 John J. Clement Creative Model Construction in Scientists and Students The Role of Imagery, Analogy, and Mental Simulation Clement_FM.indd iii

4 John J. Clement University of Massachusetts Amherst, MA USA ISBN e-isbn Library of Congress Control Number: Springer Science + Business Media B.V. No part of this work may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, microfilming, recording or otherwise, without written permission from the Publisher, with the exception of any material supplied specifically for the purpose of being entered and executed on a computer system, for exclusive use by the purchaser of the work. Printed on acid-free paper springer.com Clement_FM.indd iv

5 Acknowledgments I would like to acknowledge the contributions of the following persons in preparing this book: First to my wife Barbara Morrell for all her support; and to the following for very valuable discussions: Ryan Tweney, Carol Smith, Lynn Stephens, Neil Stillings, David Brown, Melvin Steinberg, Tom Murray, William Barowy, and Jack Lochhead. The research reported in this document was supported by the National Science Foundation under Grants MDR , DRL , and REC Any opinions, findings, and conclusions or recommendations expressed in this book are those of the author and do not necessarily reflect the views of the National Science Foundation. v Clement_FM.indd v

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7 Contents Acknowledgments v 1 Introduction: A Hidden World of Nonformal Expert Reasoning Part One Analogies, Models and Creative Learning in Experts and Students Section I Expert Reasoning and Learning via Analogy Major Processes Involved in Spontaneous Analogical Reasoning Methods Experts Use to Generate Analogies Methods Experts Use to Evaluate an Analogy Relation Expert Methods for Developing an Understanding of the Analogous Case and Applying Findings Section II Expert Model Construction and Scientific Insight Case Study of Model Construction and Criticism in Expert Reasoning Creativity and Scientific Insight in the Case Study for S Section III Creative Nonformal Reasoning in Students and Implications for Instruction Spontaneous Analogies Generated by Students Solving Science Problems vii Clement_FM.indd vii

8 viii Contents 9 Case Study of a Student Who Counters and Improves His Own Misconception by Generating a Chain of Analogies Using Analogies and Models in Instruction to Deal with Students Preconceptions by John J. Clement and David E. Brown Part Two Advanced Uses of Imagery and Investigation Methods in Science and Mathematics Section IV Imagery and Physical Intuition in Experts and Students Analogy, Extreme Cases, and Spatial Transformations in Mathematical Problem Solving by Experts Depictive Gestures and Other Case Study Evidence for Use of Imagery by Experts and Students Physical Intuition, Imagistic Simulation and Implicit Knowledge Section V Advanced Uses of Imagery in Analogies, Thought Experiments, and Model Construction The Use of Analogies, Imagery, and Thought Experiments in both Qualitative and Mathematical Model Construction Thought Experiments and Imagistic Simulation in Plausible Reasoning An Evolutionary Model of Investigation and Model Construction Processes Imagistic Processes in Analogical Reasoning: Transformations and Dual Simulations How Grounding in Runnable Schemas Contributes to Producing Flexible Scientific Models in Experts and Students Section VI Conclusions Summary of Findings on Plausible Reasoning and Learning in Experts I: Basic Findings Clement_FM.indd viii

9 Contents ix 20 Summary of Findings on Plausible Reasoning and Learning in Experts II: Advanced Topics Creativity in Experts, Nonformal Reasoning, and Educational Applications References Name Index Subject Index Clement_FM.indd ix

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11 Detailed Table of Contents Acknowledgments v 1 Introduction: A Hidden World of Nonformal Expert Reasoning Why Study Nonformal Reasoning? The Need for a Theory of Learning with Understanding A Strong Parallel Between Expert and Student Learning Processes The Background from Which I Approached This Work Novice Problem Solving Expert Studies Background of Work on Expertise and Science Studies and Remaining Gaps in Our Understanding of Scientific Thinking Educational Applications of Expert Studies Summary Generative Methodology: Qualitative Nature of the Study Descriptive Case Studies Exploratory Documentation of Imagery and Mental Simulation Instructional Applications General Features of the Analysis Method Used: Contact Between Data and Theory General Theoretical Framework Section Summaries and Approaches to Reading This Book Creativity, Imagery, and Natural Reasoning xi Clement_FM.indd xi

12 xii Detailed Table of Contents Part One Analogies, Models and Creative Learning in Experts and Students Section I Expert Reasoning and Learning via Analogy Major Processes Involved in Spontaneous Analogical Reasoning Some Major Issues in Analogical Reasoning Historic Recognition of Importance of Analogy Definitions of Analogy Theories of Analogical Reasoning Preview of Alternative Processes for Analogical Reasoning Identified in This Book Method of Study Data Collection Initial Observations Initial Results on Frequency of Analogy Use Observations from Transcripts Evaluating the Analogy Relation Major Processes Used in Analogical Reasoning Analogies from a Second Subject Analysis of Major Events in S3 s Transcript Conclusion Methods Experts Use to Generate Analogies Introduction Definitions of Basic Concepts and Observations Definition of Spontaneous Analogy Observed Spontaneous Analogies Analogy Generation Methods Frequency of Different Analogy Generation Methods Summary of Observations with Respect to Analogy Generation Discussion The Presence of Analogies in the Solutions Generation Methods and Invention Summary Methods Experts Use to Evaluate an Analogy Relation The Importance of Establishing the Validity of an Analogy Relation Examples from Case Studies Evaluating Analogies for the Sisyphus Problem Bridging Analogies Clement_FM.indd xii

13 Detailed Table of Contents xiii A Pulley as an Analogy for the Wheel Analogy Evaluation in the Doughnut Problem Bridging from Tori to Cylinders Discussion of Findings and Connections to History of Science Discussion of Findings on Bridging Analogies and Bridges in the History of Science Beyond Bridging Summary Expert Methods for Developing an Understanding of the Analogous Case and Applying Findings Evaluating and Developing an Understanding of the Analogous Case Direct Methods Indirect Methods Summary: Developing Understanding of the Source Analogue Transferring Findings Why Are Analogies Useful? Data on Transfer Section I Summary for Creative Analogy Generation Section II Expert Model Construction and Scientific Insight Case Study of Model Construction and Criticism in Expert Reasoning Issues Surrounding Theory Formation Background Questions from Philosophy of Science The Source and Pace of Theory Change Philosophical Positions: Empiricism vs. Rationalism How are Theoretical Hypotheses Formed in the Individual Scientist? Answer 1: Hypothetico-deductive Method Plus Induction Answer 2: Creative Intuition Answer 3: Analogies as a Source of Theoretical Hypotheses Definitions of Model : A Thorny Issue Protocol Evidence on Construction Cycles That Use Analogies Purpose of Case Study S2 s Protocol Analysis of Insight Episode Clement_FM.indd xiii

14 xiv Detailed Table of Contents 6.5 Summary of Evidence for a Model Construction Cycle as a Noninductive Source for Hypotheses Model Construction Cycles Explanatory vs. Nonexplanatory ( Expedient ) Models Major Nonformal Reasoning Patterns in the Preceding Chapters Appendix: Introduction to Concepts of Torque and Torsion Creativity and Scientific Insight in the Case Study for S Eureka or Accretion? The Question of Insight in S2 s Protocol Defining a Pure Eureka Event Is There a Sudden Reorganizing Change in S2 s Understanding? Does the Subject Use Extraordinary Reasoning Processes? Defining Insight Summary Creative Mental Processes Anomalies and Persistence in Protocols and Paradigms Transformations, Invention, and Memory Provocation Productive Processes: Constrained Successive Refinement vs. Blind Variation Darwin s Theory of Natural Selection Initial List of Features of Creative Thinking from This Case Study and Remaining Challenges Creative Thought Limitations of the Case Study Section III Creative Nonformal Reasoning in Students and Implications for Instruction Spontaneous Analogies Generated by Students Solving Science Problems Use of Analogies by Students Frequency Features of Spontaneously Generated Analogies Conclusion Similarities Between Experts and Students Implications Appendix: Examples of Problems and Spontaneous Analogies Chariot Problem Clement_FM.indd xiv

15 Detailed Table of Contents xv Space Carts Problem Forces on a Stationary Cart Problem Rocket Problem Skaters Problem Case Study of a Student Who Counters and Improves His Own Misconception by Generating a Chain of Analogies Spontaneous Analogies in a Student s Problem Solution Protocol for S Protocol Summary Protocol Observations: Creative Case Generation Developing Hypotheses about Cognitive Events that can Account for the Observations Conclusion: Expert-Novice Similarities Instructional Implications Using Analogies and Models in Instruction to Deal with Students Preconceptions John J. Clement and David E. Brown 10.1 Introduction Teaching Strategy Introducing the Target Anchoring Case Bridging Strategy Teaching Interviews Tutoring Session Discussion of First Case Study A Second Case Study Explanatory Models Abstract Transfer vs. Explanatory Model Construction Summary of Cases Applications to Classroom Teaching Study of Classroom Lessons Conclusion Persistent Misconceptions Explanatory Models vs. Specific Analogous Cases Two Roles for Anchors Plausible Reasoning vs. Logical Proof Processes in Learning Role of Thought Experiments vs. Observation Activities in Instruction Clement_FM.indd xv

16 xvi Detailed Table of Contents Part Two Advanced Uses of Imagery and Investigation Methods in Science and Mathematics Section IV Transformations, Imagery and Simulation in Experts and Students Analogy, Extreme Cases, and Spatial Transformations in Mathematical Problem Solving by Experts Introduction Case Study of Analogical Reasoning in a Mathematics Problem Method Results on the Use of Analogies for Eight Subjects Analogy Generation Methods Evaluating the Cylinder Conjecture Other Creative Nonformal Reasoning Processes Extreme Cases Partitioning and Symmetry Arguments Reassembly of a Partition Embedding Discussion Imagistic Reasoning Conserving Transformations Conclusion Depictive Gestures and Other Case Study Evidence for Use of Imagery by Experts and Students Introduction Hand Motions Imagery Questions and Hypotheses Previous Research on Hand Motions Limitations of Previous Research Constructing Observational and Theoretical Descriptors Proposed Set of Hypotheses Relations Between Observations and Hypotheses Case Studies An Expert Protocol Analysis of S15 s Protocol Evidence Supporting the Use of Imagery in the Solution Argument Structure A Student Protocol Analysis of S20 s Protocol Summary of S20 Analysis Clement_FM.indd xvi

17 Detailed Table of Contents xvii 12.4 Discussion Types of Processes Associated with Motions Can Depictive Hand Motions be a Direct Product of Imagery? Summary of Relations Between Observations and Hypotheses Relationship of These Findings to Others in the Literature The Existence of Kinesthetic Imagery Depictive Motions Are Not Simply Translated from Sentences Movements Are a Partial Reflection of Core Meaning or Reasoning Gestures Can Reflect Imagery Conclusion Sources of Information About Imagery and Simulation Limitations Appendix 1 Detailed Justification for Using Evidence of Imagery from Hand Motions in S15 s Protocol Motions Are Concurrent with Solution Process Motions Can Be a Direct Product of Solution Process Motions Not Translated from Verbal Sentences Evidence for Imagery Appendix 2 Observation Categories in Numerical Order Physical Intuition, Imagistic Simulation and Implicit Knowledge Introduction: Issues in the Area of Imagery, Simulation and Physical Intuition Abstract vs. Concrete Thinking in Experts Initial Examples of Physical Intuition Intuition Reports Defining Features and Observable Behaviors Associated with Intuitions Physical Intuitions Imagery Reports and Imagistic Simulation Moving from the Findings in Chapter 12 to Models of Imagistic Simulation Schema-driven Imagistic Simulation Processes Precedents in the Literature on Perceptual/Motor Schemas Relations Between Observations and Hypotheses Clement_FM.indd xvii 5/24/2008 9:39:37 AM

18 xviii Detailed Table of Contents Importance of Concrete Intuitions and Imagistic Simulation Implicit Knowledge Distinguishing Different Levels of Implicit Knowledge Evidence for Unconscious Knowledge Knowledge Can Be Dynamic Different Uses of the Term Simulation Knowledge Experienced in Imagistic Simulations Is Not Static Conclusion: The Role of Concrete Physical Intuitions and Simulations in Embodied Thinking by Experts Summary of an Initial Framework for Modeling Physical Intuition and Mental Simulation via Perceptual/Motor Schemas and Imagery Imagery Intuitions and Imagistic Simulation How Is New Knowledge Generated from an Elemental Simulation? Using Perceptual/Motor Schemas as an Initial Foothold for Understanding the Use of Intuitions and Imagistic Simulation Imagery, Intuitions, and Anchoring Section V Advanced Uses of Imagery in Analogies, Thought Experiments, and Model Construction The Use of Analogies, Imagery, and Thought Experiments in both Qualitative and Mathematical Model Construction Introduction to Chapter Stages in Model Construction Leading up to Quantitative Modeling During the Solution Issues in the Field Ways to Read this Chapter Composite Protocol Monologue for the Spring Problem I. Efforts to Develop an Initial Qualitative Description or Prediction for the Targeted Relationship II. Searching for and Evaluating Initial, Qualitative, Explanatory Model Elements III. Seeking a More Fully Imageable and Causally Connected (Integrated) Model: Attempts to Align and Elaborate the Model Clement_FM.indd xviii 5/24/2008 9:39:37 AM

19 Detailed Table of Contents xix So as to Have Elements That Are Fully Connected Spatiotemporally IV. Increasing the Geometric Level of Precision of the Spatial and Physical Relationships Projected from the Model into the Target Until They Are Ready to Support Quantitative Predictions V. Developing a Quantitative Model on the Foundation of the New Qualitative and Geometric Models Stages in the Solution Some Possible Precision Levels for Relationship R Between X and Y Transforms to Close Analogies in Later Stages of Solution Summary Building a Theoretical Distinction: Explanatory Models vs. Expedient Analogies Expedient Analogies Source Analogues Triangular, Not Dual, Relation in Model Construction Source analogues are Projected into the Composite Model, and Must Be Imagistically Aligned Conclusion Plausible Reasoning and Stages of Investigation Parallels and Differences Between Qualitative and Mathematical Modeling Thought Experiments and Imagistic Simulation in Plausible Reasoning Nature of Thought Experiments Fundamental Paradox of Thought Experiments and Two Definitions Nersessian Focus of This Chapter What are Some Major Functions of and Benefits from Untested Thought Experiments? Primary Function Secondary Functions Can Schema-based Imagistic Simulation be Involved in Untested Thought Experiments with These Different Functions, and if so, What is Its Role? Summary Clement_FM.indd xix 5/24/2008 9:39:37 AM

20 xx Detailed Table of Contents 15.2 Addressing the Thought Experiment Paradox: How Can an Untested Thought Experiment Generate Findings with Conviction? Introduction Sources of Conviction: Perceptual Motor Schemas Sources of Conviction: Spatial Reasoning, Symmetry, and Compound Simulation Summary Imagery Enhancement Phenomena Support the Proposed Answer to the Paradox Limitations on Simulation Ability Imagery Enhancement Focused on Enhancing the Application of a Schema in a Simulation Analysis of Transcripts Sources of Conviction in Imagery Enhancement Implications of These Extreme Case Examples for a Theory of Thought Experiments Imagery Enhancement Focused on Enhancing Spatial Reasoning or Symmetry or Compound Simulations Enhancing Spatial Reasoning Via Image Size and Orientation Symmetry Enhancement Compound (or Linearity ) Enhancement The Effectiveness of Enhancement Can Be Explained Using the Present Theory of Conviction in Thought Experiments How are Thought Experiments Used Within More Complex Reasoning Modes? Four Important Types of Plausible Reasoning Evaluative Gedanken Experiments as the Most Impressive Kind of Thought Experiment Multiple Types of Reasoning Processes that can Utilize Thought Experiments Run Via Imagistic Simulations Are Imagistic Simulations Operating in the Mathematical Part of the Solution? How Thought Experiments Contribute to Model Evaluation Evaluation Strategies Summary Combining Reasoning Processes into a Model Construction Process Chapter Summary Addressing the Fundamental Paradox of Thought Experiments: Sources of Conviction Clement_FM.indd xx 5/24/2008 9:39:37 AM

21 Detailed Table of Contents xxi 16 A Punctuated Evolution Model of Investigation and Model Construction Processes Abductive Processes for Generating and Modifying Models Defining Abduction Construction Occured via Generative Abduction Rather than Induction or Deduction Generative Abduction: Basic Model Qualitative Investigation Processes Introduction to Three-part Model of Investigation Processes GEM Cycles The Explanatory Depth and Precision of Description Dimensions The Three Cycles in the Outlined Investigation Process can Generate the Five Major Observed Modes of Investigation in the Protocol Separate Explanation and Description Processes Computational Model of Todd Griffith Evaluation Functions can Guide Control Comparison to Griffith Study Explaining Insight: Unpredictable Spontaneous Accessing of Subprocesses Generality Levels of Explanation and Precision Limitations of Model Presented Mathematical Modeling Processes Cycle III: Mathematical Modeling Untested Thought Experiments at Higher Levels of Precision than Qualitative Modeling Mathematics and Explanation Abduction II: How Evaluation Processes Complement Generative Abduction Multiple Sources of Ideas and Constraints for the Generative Abduction Process Model Evaluation can Provide Inputs to the Next Abduction Cycle Role of Transformations in Model Modification Distinctions Between Constructive Transformations, Running a Schema in an Imagistic Simulation, and Basic Spatial Reasoning Operators Coherence and Competition Between Models Seeking an Optimal Level of Divergence The Problem of Accessing Relevant Prior Knowledge: An Ill-Structured Problem Clement_FM.indd xxi 5/24/2008 9:39:37 AM

22 xxii Detailed Table of Contents Need for an Effective Middle Road with Respect to Creative Divergence Analogies and Extreme Cases Appear to be a Fruitful Source of Divergence Dangers of Divergence: The Need for Optimal Divergence Some Methods for Reducing Einstellung Effects Via Contained Divergence Mechanisms for Modulating Divergence Summary for Section on Divergence Chapter Summary Diagrammatic Summary Multiple Cycles and Goals in the Overall Investigation Process Four Subprocesses at the Core of Complex Model Construction: Generative Abduction, Model Evaluation, Schema Alignment, and Mathematization Imagistic Processes in Analogical Reasoning: Transformations and Dual Simulations Two Precedents from the Literature Structural Mapping and Evaluation Wertheimer s Parallelogram Conserving Transformations Transformations are not Equivalent to Mapping Symbolic Relations Are Conserving Transformations Just Memorized Rules? Conserving Transformations in Science Wheel Problem Spring Problem Newton s Canon Dual Simulation Do Dual Simulations Differ from Transformations? Dual Simulation for the Square and Circular Coils Overlay Simulation Examples of Overlay Simulation Connection to Model Construction: Overlay Simulations and Model Projections May Involve Similar Processes Model Projection Clement_FM.indd xxii 5/24/2008 9:39:37 AM

23 Detailed Table of Contents xxiii Imagistic Alignment Analogies Dual Simulation vs. Compound Simulation in Modeling Summary and Discussion of Types of Evaluation Processes: Contrasting Mechanisms for Determining Similarity Mechanisms for Dual Simulation (Including Overlay Simulation) Mechanisms for Conserving Transformations Bridging is a Higher-order Strategy Compared to Others Combination of Evaluation Methods Contrast to Structural Mapping of Images Conclusion on Evaluation: Four Main Analogy Evaluation Methods, Not One Use of Imagistic Transformations During the Generation of Partitions, Analogies, Extreme Cases, and Explanatory Models Conclusion How Grounding in Runnable Schemas Contributes to Producing Flexible Scientific Models in Experts and Students Introduction: Does Intuitive Anchoring Lead to Any Real Advantages? Review of Findings on Imagistic Simulation and Runnable Schemas Transfer of Runnability Hypothesis Models Can Inherit the Capacity for Simulation from Anchors What, Exactly is Transferred? Example of Transfer of Imagery and Runnability in Instruction Cognitive Benefits of Anchoring and Runnability for Models Traditional Benefits of Building on Prior Knowledge Benefits of Transferring Runnability from a Schema to an Explanatory Model Recursive Runnability of Models As Thought Experiments Explain Many of These Benefits Transfer of Conviction How Runnable Models Contribute Desirable Properties to Scientific Theories Scientific Theories and the Role of Runnability Conclusion Initial Support for the Runnability Hypothesis Clement_FM.indd xxiii 5/24/2008 9:39:37 AM

24 xxiv Detailed Table of Contents Section VI Conclusions Summary of Findings on Plausible Reasoning and Learning in Experts I: Basic Findings Brief Overview of Theoretical Findings Model Construction in Experts Model Construction in Students Summary Table of Expert Subprocesses Analogy Findings, Part One The Presence and Importance of Analogy in Expert Thinking: Significant Analogies Literal Similarity and the Problem of What Counts as an Analogy Analogy Subprocesses Initial New Distinctions and Findings on Analogy Model Construction Findings, Part One and Initial Connections to General Issues in History/Philosophy of Science Extraordinary vs. Natural Reasoning Extraordinary Thinking? Eureka vs. Accretion Question A Case Study of Scientific Insight Initial Exploration of Mechanisms of Hypothesis Generation Section Summary Imagistic Simulation Findings, Part One Imagery Indicators as Observational Concepts Mechanisms for Imagistic Simulation Terminology for Imagistic Simulations Imagery During Simulation Behavior Image-generating Perceptual Motor Schemas as Embodied Knowledge Sources of New Knowledge in Imagistic Simulations How Perceptual Motor Schemas are Useful in Scientific Thinking Intuitive Anchors Role of Perceptual/Motor Schemas in the Construction of Model Assemblies Connection to Experiments and Situated Action Section Summary Summary of Findings on Plausible Reasoning and Learning in Experts II: Advanced Topics Analogy Findings, Part Two Clement_FM.indd xxiv 5/24/2008 9:39:37 AM

25 Detailed Table of Contents xxv Comparison to Classical Views of Analogical Reasoning Analogies and Imagery Analogies and Model Construction Imagistic Simulation Findings Part Two: Thought Experiments and Their Uses in Plausible Reasoning Overview Summary of Findings on Thought Experiments Broader and Narrower Categories of Thought Experiments Can Thought Experiments Allow One to Get the Physics for Free? Section Conclusion Model Construction Findings Part Two: An Evolutionary Model of Investigation Processes Top Level of Scientific Investigation Process Process I: Description Cycle Process II: Explanatory Model Construction Process III: Mathematical Modeling The Important Role of Imagery in the Expert Investigations Limitations of the Imagery and Simulation Systems Evidence for Imagery Involvement in a Wide Range of Reasoning Processes Evidence for the Importance to Subjects of Imagistic Simulation Possible Advantages of Imagistic Representations as Knowledge Structures Possible Advantages of Imagistic Representations for Creative Reasoning Transfer of Runnability Leads to Outcomes of Flexible Model Application and Generativity Example of Flexible Model Application Role of Runnable Intuitions in Conceptual Understanding and Recursive Runnability Comparison to Lakoff and Nunez s Embodied Mathematics Payoffs from Transfer of Runnability: Comments on Methodology Small Samples Links Between Data and Theory Clement_FM.indd xxv 5/24/2008 9:39:37 AM

26 xxvi Detailed Table of Contents 21 Creativity in Experts, Nonformal Reasoning, and Educational Applications Summary of the Overall Framework View from Multiple Diagrams Central Role of Imagery Highlighted Findings Larger Integrating Processes Position on Concrete vs. Abstract Thinking How Experts Used Creativity Effectively Do Expert Discovery Processes in Science Always Have an Empirical Focus? How a Coalition of Weak, Nonformal Methods are Able to Overcome the Dilemma of Fostering both Creativity and Validity Overlap Between the Context of Discovery and Context of Evaluation Section Conclusion Educational Applications: Needed Additions to the Classical Theory of Conceptual Change in Education Uses and Criticisms of Kuhn Criticisms of Classical Conceptual Change Theory Need for an Expanded Theory of Conceptual Change for Education Expert Novice Similarities in Nonformal Reasoning and Learning Similarities Concerning Resistance to Change Similarities in the Use of Intuition and Imagery Use of Analogies by Students Model Construction by Students Summary: Expert Novice Comparisons Implications for Instructional Strategies and Theory Strategies Suggested by Initial Studies of Analogy and Model Construction in Part One of the Book Strategies Suggested by Findings on Imagistic Knowledge Representations in Part Two of the Book Educational Implications of Imagistic Learning Processes in Part Two of the Book Conclusion Educational Applications Are Creative Processes in Experts a Natural Extension of Everyday Thinking? Expert Novice Comparisons for Knowledge Structures: Science as an Extension of Intuition? Expert Novice Differences in Reasoning Expert Novice Similarities in Reasoning Clement_FM.indd xxvi 5/24/2008 9:39:37 AM

27 Detailed Table of Contents xxvii Some Expert Processes are Neither Extraordinary Nor Ordinary A Spectrum from Ordinary Thinking to Unusually Effective Creative Thinking to Extraordinary Thinking Summary: How Creative Expert Reasoning is not Ordinary Implications for Instruction: Utilizing Natural Reasoning Processes Assessing the Potential for a Model of Creative Theory Construction in Science Expertise and Domain Specificity Can Creative Behavior Be Explained? Conclusion Creative Thinking The Model Construction Process Portrayed Here in Contrast with Oversimplified Models Questions About Scientific Thinking References Name Index Subject Index Clement_FM.indd xxvii 5/24/2008 9:39:37 AM