Models and Modeling - Cognitive Tools for Scientific Enquiry

Contents

Contributors

Part I Theory Formation and Modeling in Science Education

1 Modeling and the Future of Science Learning

Introduction

The Nature of Models and Modeling

Models, Modeling, and the Nature of Science

Models and Modeling in Scientific Enquiry

Modeling as a Cognitive Tool

Modeling in the Teaching and Learning of Science

Future Work

References

2 A Study of Expert Theory Formation: The Role of Different Model Types and Domain Frameworks

Creating Models

A Protocol Study of Expert Theory Formation

Analysis of Three Protocols

Discussion

Conclusion

References

3 The Nature of Scientific Meta-Knowledge

Introduction

Perspectives on the Nature of Science

Meta-theoretic Knowledge

Different Types of Models

An Agent Model of Social Interaction (Community Model)

Purposes of Different Models

Creating Models

Characteristics of a Good Model

How Different Models Fit Together

Meta-questioning Knowledge

Different Types of Research Questions

Purposes for Research Questions

Criteria for Good Research Questions

Generating Research Questions

How Research Questions Fit Together

Meta-investigation Knowledge

Different Types of Investigations

Exploratory Inductive Investigations

Confirmatory Investigations

Examples of Investigations

Purposes of Different Investigations

Creating Investigations

Further Issues to Consider When Designing Investigations

Characteristics of a Good Investigation

How Different Investigations Fit Together

Meta-knowledge for Data Analysis

Different Data Analysis Methods

Study 1. Qualitative and Quantitative Exploratory Analyses Based on Interviews with Students About Their Views of Friendship

Study 2. A Quantitative, Confirmatory Analysis to Test Hypotheses About Strategies for Making Friends

Study 3. Qualitative and Quantitative Exploratory Analyses Based on Observation of the Development of Friendships Within a Book Group

Purposes of Data Analysis

Creating Analyses

Characteristics of a Good Data Analysis

How Different Analyses Fit Together

Discussion

Summary of the Meta-knowledge Framework

Teaching Scientific Meta-knowledge

Concluding Thoughts About the Utility of the Framework

References

4 From Modeling Schemata to the Profiling Schema: Modeling Across the Curricula for Profile Shaping Education

Modeling Theory in Science Education

Paradigmatic Perspective

Critical Thresholds

Modeling Schemata

Progressive Middle-Out Approach

Experiential Learning Cycles

Mediated Regulation

Profile Shaping Education

The Profiling Schema

Cognitive Taxonomy

Deployment

References

Part II Modeling and Student Learning in Science Education

5 Helping Students Construct Robust Conceptual Models

A Brief History of Modeling Instruction

The Modeling Classroom

Culture

Motivation

Student Thinking

The Modeling Experience

The Study

Findings

Modeling Activities

Whiteboarding

The Architecture of Modeling Discourse

Connecting Discourse with Whiteboarded Representations to Make Sense of Student Thinking

Whiteboard-Centered Activities

The Power of the Marker and the Power of the Eraser

The Role of the Teacher

Critical Factors in Discourse Management––The Board Meeting

Understanding the Conceptual Models Students Construct

Implications for Instruction

Suggestions for Teachers

Conclusion

References

6 The Molecular Workbench Software: An Innovative Dynamic Modeling Tool for Nanoscience Education

Introduction

The Importance of Dynamic Modeling

Why Use First Principles to Build Educational Simulations?

The Molecular Workbench Software

The Computational Engines

The Molecular Dynamics Engine

The Quantum Dynamics Engine

The Modeling and Authoring System

The Delivery System

The Assessment System

Results

Future Work

References

7 Lowering the Learning Threshold: Multi-Agent-Based Models and Learning Electricity

Introduction

Theoretical Overview: Electricity and the Micro–Macro Link

Misconceptions in Electricity as ''Slippage Between Levels''

The ''Emergent'' Approach: The Microscopic Theory of Conduction and Its Affordances

Potential Design Challenges from a Developmental Perspective

Lowering the Threshold for Learning: Designing NIELS to Leverage Naïve Intuition

NetLogo: A ''Glass-Box'' Platform for Learning and Modeling

The Original Model: Electric Current in a Wire

The Redesigned Model: Electron-Sink Model

The Study: Setting, Method, and Data

Differences Between the Models Used

Coding and Analysis

Registration

Causal Schema

Phenomenological Primitives

Findings

Mental Models of Students in the Electron-Sink Group (Fifth and Seventh Grade): Understanding Conservation of ''Filling-Time''

Amber (fifth grade)

David (and Sam) (seventh Grade)

Written Explanations of the ''Balancing Filling-Time'' Activity

From ''Filling-Time'' to Electric Current

Between-Group Quantitative Comparisons of Post-explanations of ''Balancing Current''

Discussion

References

NetLogo Models References

8 Engineering-Based Modelling Experiences in the Elementary and Middle Classroom

Introduction

Engineering, Science, Mathematics, and Technology Education

Engineering Education for Young Learners

A Models and Modelling Perspective for Engineering Education

An Engineering Model-Eliciting Activity

Principles for Designing Model-Eliciting Activities

The Model Construction Principle

The Personal Meaningfulness Principle

The Self-Assessment Principle

The Model Documentation Principle

The Model Generalization Principle

The Present Study

Participants and Procedures

Data Sources and Analyses

Results

Model A

Model B

Model C

Model D

Remaining Groups' Model Creations

Discussion and Concluding Points

Appendix: There Is a Trouble in Paradise: Severe Water Shortage Problem in Cyprus

The Problem

References

9 Engaging Elementary Students in Scientific Modeling: The MoDeLS Fifth-Grade Approach and Findings

The MoDeLS Approach to Scientific Models and Modeling

Conceptual Framework

Methodological Framework: A Learning Progression Framework for Students' Scientific Modeling

The Model-Centered Instructional Sequence and the Unit of Evaporation and Condensation for Elementary Students' Engagement in Scientific Modeling

The Authors' Work on Engaging Elementary Students in Scientific Modeling

The Instructional Sequence as a Pedagogical Tool

The Model-Centered Instructional Sequence (MIS)

The MIS-Embedded Unit of Evaporation and Condensation

Method

The Influence of the MIS on Students' Modeling

The Influence of Empirical Investigations in MIS: Students' Attention to Empirical Evidence

The Influence of the Computer Simulations in MIS: Students' Attention to Invisible Objects as an Explanatory Feature

The Influence of the Social Interactions in MIS: Students' Attention to Audience and Communicative Features of Models

Discussion and Concluding Remarks

References

Part III Modeling and Teachers' Knowledge

10 Relationships Between Elementary Teachers' Conceptions of Scientific Modeling and the Nature of Science

Introduction

Literature Review and Framework

Method

Participants

Intervention

Data Collection

Data Analysis

Results

Teachers' Conceptions of NOS Aspects

Teachers' Conceptions of Scientific Models and Relationships of Scientific Models and NOS Aspects

Implications

Recommendations

Appendix

References

11 Science Teachers' Knowledge About Learning and Teaching Models and Modeling in Public Understanding of Science

Introduction

Aim of the Study

Public Understanding of Science (PUSc)

Models and Modeling in Public Understanding of Science

Method and Procedure

Participants in the Study

The Repertory Grid Instrument

The Semi-structured Interview

Data Analyses

Rep Grid Data Analyses: Research Question 1

FOCUS Sorting and Hierarchical Clustering

COMPARE

Interview Data Analyses: Research Question 2

Knowledge About Instructional Strategies (1) and About Students' Understanding (2)

Knowledge About Ways to Asses Students' Understanding (3)

Knowledge About Goals and Objectives of the Topic in the Curriculum (4)

Results from the Data Analyses

Research Question 1: Rep Grid Results

Research Question 2: Interview Results

Type I of PCK: Focused on Model Content

Type II of PCK: Focused on Model Content, Model Creation, and Model Thinking

PCK Development

Conclusions

Type A: Science as a Body of Knowledge

Type B: Science as a Method of Generating and Validating Knowledge

Discussion and Implications

Possible Explanations of the Differences Between Type A and Type B

Implications

References

12 Teaching Pre-service Elementary Teachers to Teach Science with Computer Models

Introduction

Methods

Participants

The Computer-Modeling Tool

The Instructional Design Model

Assessment Task

Results and Discussion

Concluding Remarks

References

Name Index

Subject Index