This book describes interactive learning environments (ILEs) and their underlying concepts. It explains how ILEs can be used to improve the decision-making process and how these improvements can be empirically verified. The objective of this book is to enhance our understanding of and to gain insights into the process by which human facilitated ILEs are effectively designed and used in improving users' decision making in complex, dynamic tasks. This book is divided into four major parts. Part I serves as an introduction to the importance and complexity of decision making in dynamic tasks. Part II provides background material, drawing upon relevant literature, for the development of an integrated process model on the effectiveness of human facilitated ILEs in improving decision making in dynamic tasks. Part III focuses on the design, development, and application of FishBankILE in laboratory experiments to gather empirical evidence for the validity of the process model. Finally, part IV presents a comprehensive analysis of the gathered data to illustrate the lessons to be learned.

Better Decision Making in Complex, Dynamic Tasks will be useful for managers and practitioners, researchers, and students of dynamic decision making.

Praise for Better Decision Making in Complex, Dynamic Tasks:

"...rich in content, full with unique insights, and a self-sufficient volume on the design, development and application of system dynamics based simulations that are implemented as interactive learning environments (ILEs). Practitioners and researchers interested in seeking evidence for the efficacy of ILEs' use in decision-making will find this book a must read."

Prof. Carmine Bianchi, Scientific Coordinator of CED4-System Dynamics Group, University of Palermo, Italy

Klappentext

Computer simulation-based education and training is a multi-billion dollar industry. With the increased complexity of organizational decision making, projected demand for computer simulation-based decisional aids is on the rise. The objective of this book is to enhance systematically our understanding of and gain insights into the general process by which human facilitated ILEs are effectively designed and used in improving users' decision making in dynamic tasks. This book is divided into four major parts. Part I serves as an introduction to the subject of "decision making in dynamic tasks", its importance and its complexity. Part II provides background material, drawing upon the relevant literature, for the development of an integrated process model on the effectiveness of human facilitated ILEs in improving decision making in dynamic tasks. Part III focuses on the design, development and application of Fish Bank ILE, in laboratory experiments, to gather empirical evidence for the validity of the process model. Finally, part IV presents a comprehensive analysis of the gathered data to provide a powerful basis for understating important phenomena of training with human facilitated simulation-based learning environments, thereby, help to drive critical lessons to be learned. This book provides the reader with both a comprehensive understanding of the phenomena encountered in decision making with human facilitated ILEs and a unique way of studying the effects of these phenomena on people's ability to make better decision in complex, dynamic tasks. This book is intended to be of use to managers and practitioners, researchers and students of dynamic decision making. The background material of Part II provides a solid base to understand and organize the existing experimental research literature and approaches.

Inhalt

Preface.- PART ONE: INTRODUCTION TO DECISION MAKING IN COMPELX, DYNAMIC TASKS.- 1. Dynamic Decision Making and Learning: An Introduction.- 1.0 Introduction.- 1.1 Dynamic Decision Making and Interactive Learning Environments.- 1.2 Human Facilitated and Learning.- 1.3 Unique Approach of This Book.- 1.4 Critical Research Questions Explored.- 1.5 Organization of the Book.- PART TWO: DEVELOPMENT OF A PROCESS MODEL FOR BETETR DECISION MAKING.- 2. Empirical Evidence on Dynamic Decision Making and ILEs.- 2.0 Introduction.- 2.1 Important Background Concepts.- 2.2 A Framework for Experimental Review.- 2.3 Characteristics of Existing Research on DDM and Learning in ILEs.- 2.4 On the Influence of Learner Factors.- 2.5 Evidence on Dynamic Task Factors.- 2.6 Studies on Decision-Making-Environment Factors.- 2.7 Role of Human Facilitation.- 2.8 Summary of Empirical Evidence on DDM and ILEs.- 3. Towards a Road to Success: The Development of the Integrated Process Model.- 3.0 Introduction.- 3.1 The Process Model for Better Decision Making.- 3.2. Human Facilitation and Cognitive Apprenticeship Approach.- 3.3. Summary of the Integrated Process Model Development Activities.- 4. Seeking the Truth: Human-Facilitated ILEs and Hypotheses Development.- 4.0 Introduction.- 4.1 An Account of our Research Approach.- 4.2 Improving Decision Making with Human Facilitation.- 4.3 Main Hypotheses on the Effectiveness of Human-Facilitated ILEs.- 4.5 Summary of Hypotheses Development Activities.- PART THREE: SETTING THE STAGE FOR DECION MAKING AND LEARNING.- 5. Overexploitation of Renewables Abound: Modeling Fisheries Management.- 5.0 Introduction.- 5.1 The Dynamic Decision Task: Fisheries Management.- 5.2 Why to Use System Dynamics Modeling in the Development of ILEs?.- 5.3 The System Dynamics Simulation Model of Fisheries Management Task.- 5.4. Summary of the Development of the System Dynamics Simulation Model.- 6. How to Develop the Managerial Practice Field, FishBakILE? HCI Design and Learning Principles in Service of DDM.- 6.0 Introduction.- 6.1 HCI Design and Learning Principles in the Development of FishBankILE.- 6.2. The Developed Simulated Decision Environment.- 6.3. Development of Transfer Learning Task.- 6.4 Summary of HCI Design and Learning Principles-based FishBankILE.- 7. On the Mechanics of Laboratory Experiments: The Experimental Design and Procedures.- 7.0 Introduction.- 7.1 Why to Use the Laboratory-based Experimental Approach?.- 7.2 What Gets Measured Gets Done: Measuring Performance in.- 7.3 The Experimental Treatment Procedures.- 7.4 Human Facilitation Manipulations.- 7.5 Who are the Decision Makers?.- 7.6 On the Role of a Facilitator for FishBankILE.- 7.7 Summary of the Mechanics of Laboratory Experiments.- PART FOUR: ON BETTER DECIONS MAKING IN DYNAMIC TASKS.- 8. Improving Performance in Fisheries Management Task.- 8.0 Introduction.- 8.1. Developing Transfer Learning Skills.- 8.2. Improving Task Performance.- 8.3. Adapting Better Decision Strategy.- 8.4. Building Task Knowledge.- 8.5. Effects of Prior Task Knowledge and Demographics.- 8.6. Summary of Decision Making and Learning in Fisheries Management Task.- 9. Developing Transfer Learning Skills: The 1-Layer Process Model.- 9.1 Introduction.- 9.1 Effects of Task Knowledge and Task Performance on Transfer Learning.- 9.2 How Did They Develop Transfer Learning Skills?.- 9.3 A Summary on the Validation of the 1-Layer Process Model.- 10. Decision Strategy and Performance in Dynamic Tasks: The 2-Layer Process Model.- 10.0 Introduction.- 10.1 Direct Effects of Decision Strategy on Transfer Learning.- 10.2 Indirect Effects of Decision Strategy on Transfer learning.- 10.3 In Search of Decision Strategies for Better Decision Making.- 10.4 A Summary on the Validation of the 2-Layer Process Model.- 11. Pulling It Together: A Validated Process Model for DDM and Learning.- 11.0 Introduction.- 11.1 Role of Prior Knowledge in the Process Model.- 11.2 Overall Effects of Prior Knowledge.- 11.3 Do Dyads Do Better in Dynamic Tasks?.- 11.4 A Summary of the 3-Layer Process Model with LM Treatment.- 11.5 How Does Facilitation Matter? Pathways to DDM and Learning.- 11.6 Human-Facilitated ILEs in Service of DM and Learning in Dynamic Tasks.- 12. The Greater Whole: Human-Facilitated ILEs and Better Decision-Making: Critical Lessons Lear…