Franco Landriscina

Simulation and Learning

A Model-Centered Approach

• Broschiertes Buch

Produktbeschreibung

The main idea of this book is that to comprehend the instructional potential of simulation and to design effective simulation-based learning environments, one has to consider both what happens inside the computer and inside the students' minds. The framework adopted to do this is model-centered learning, in which simulation is seen as particularly effective when learning requires a restructuring of the individual mental models of the students, as in conceptual change. Mental models are by themeselves simulations, and thus simulation models can extend our biological capacity to carry out simulative reasoning. For this reason, recent approaches in cognitive science like embodied cognition and the extended mind hypothesis are also considered in the book.. A conceptual model called the "epistemic simulation cycle" is proposed as a blueprint for the comprehension of the cognitive activies involved in simulation-based learning and for instructional design.

Produktdetails

• Verlag: Springer / Springer New York / Springer, Berlin
• Artikelnr. des Verlages: 978-1-4899-9965-8
• 2013
• Seitenzahl: 256
• Erscheinungstermin: 8. April 2015
• Englisch
• Abmessung: 235mm x 155mm x 15mm
• Gewicht: 394g
• ISBN-13: 9781489999658
• ISBN-10: 1489999655
• Artikelnr.: 42578102

Inhaltsangabe

- The Simulation Paradox: If Simulations are Good for Learning, where are they?, The Epistemic Status of Simulation, Simulation Myths and Fads. -An Introduction to Simulation for Learning: What is Simulation for Learning, The Need for a Generalist Approach, Differences between Simulation and Games, Simulation and Cognition. - Models Everywhere: A Concept at the Crossroads of Different Disciplines, Types of Models, The Representational Issue, Functions of Models, Model-Based Learning. -The Epistemic Cycle: A Model of Modeling, The Reality-System Loop, The System-Model Loop, The Model-Simulation Loop. -Simulation Modeling: Simulation Paradigms, Continuous Models, Agent-Based Modeling, System Dynamics. -Simulation-Based Learning: Learning with Simulations, Simulative Reasoning, The Role of Mental Simulation, Simulation and Cognitive Partnering. -Simulation-based Instruction: From Computational Models to Instructional Units, Simulation and Cognitive Load, An Instructional Design Perspective, Simulation and Science Education, Modeling Skills, Simulation Literacy.- Conclusions.