The Use of Models in Science

2013 ◽  
pp. 39-52
Keyword(s):  
Models In Science ◽  
Use Of Models

The Use of Models in Science and Science Teaching

1980 ◽  
Vol 2 (1) ◽  
pp. 3-13 ◽  
Author(s):  
J. K. Gilbert ◽  
R. J. Osborne
Keyword(s):  
Science Teaching ◽  
Models In Science ◽  
Use Of Models

The Use Of Models in Science

2018 ◽  
pp. 1-4
Author(s):  
Edward K. Yeargers
Keyword(s):  
Models In Science ◽  
Use Of Models

scholarly journals Logical Relativism Through Logical Contexts

2021 ◽  
Vol 17 (2) ◽  
Author(s):  
Jonas R. Becker Arenhart
Keyword(s):  
Scientific Practice ◽  
Similar Argument ◽  
Models In Science ◽  
Intuitionistic Mathematics ◽  
Use Of Models

We advance an approach to logical contexts that grounds the claim that logic is a local matter: distinct contexts require distinct logics. The approach results from a concern about context individuation, and holds that a logic may be constitutive of a context or domain of application. We add a naturalistic component: distinct domains are more than mere technical curiosities; as intuitionistic mathematics testifies, some of the distinct forms of inference in different domains are actively pursued as legitimate fields of research in current mathematics, so, unless one is willing to revise the current scientific practice, generalism must go. The approach is advanced by discussing some tenets of a similar argument advanced by Shapiro, in the context of logic as models approach. In order to make our view more appealing, we reformulate a version of logic as models approach following naturalistic lines, and bring logic closer to the use of models in science.

scholarly journals Modeller i kjemiundervisning - et eksempel på hvordan de kan bidra til læring og feillæring

2021 ◽  
Vol 17 (2) ◽  
pp. 181-205
Author(s):  
Heidi Iren Saure ◽  
Nils-Erik Bomark ◽  
Monica Lian Svendsen
Keyword(s):  
Science Education ◽  
Paper Chromatography ◽  
Main Theme ◽  
Abstract Concepts ◽  
Teaching Program ◽  
Analogical Model ◽  
Models In Science ◽  
Teacher Students ◽  
Online Learning Resources ◽  
Use Of Models

We discuss the use of analogical models in science education using examples from online learning resources.  We have conducted a teaching program for a group of 7th grade pupils and a group of science teacher students, and the main theme of this program is the use of models in chemistry. Specifically, we study the effect of an analogical model that is designed to promote understanding of the properties of molecules, related to a paper chromatography experiment. Our research indicates that analogical models can be a useful tool to convey understanding of abstract concepts and non-visible phenomena, but they hold serious pitfalls that can lead to misunderstandings amongst students if not used in a proper manner. These findings are in line with other studies. Our data indicate that respondents` knowledge about molecular properties may have increased after participating in this teaching program. However, both groups of respondents consistently used wrong properties to explain the paper chromatography experiment. Conversation transcripts and respondents` models indicate that these misconceptions are enhanced by the analogical model they were given to work with during the teaching program. Based on our findings, we give some advice for how to best present analogies in the classroom.

Computing Possible Futures

2019 ◽  
Author(s):  
William B. Rouse
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Computational Modeling ◽  
Mental Model ◽  
Data Analytics ◽  
Computational Models ◽  
Senior Managers ◽  
Interactive Visualizations ◽  
Use Of Models ◽  
Better Than

This book discusses the use of models and interactive visualizations to explore designs of systems and policies in determining whether such designs would be effective. Executives and senior managers are very interested in what “data analytics” can do for them and, quite recently, what the prospects are for artificial intelligence and machine learning. They want to understand and then invest wisely. They are reasonably skeptical, having experienced overselling and under-delivery. They ask about reasonable and realistic expectations. Their concern is with the futurity of decisions they are currently entertaining. They cannot fully address this concern empirically. Thus, they need some way to make predictions. The problem is that one rarely can predict exactly what will happen, only what might happen. To overcome this limitation, executives can be provided predictions of possible futures and the conditions under which each scenario is likely to emerge. Models can help them to understand these possible futures. Most executives find such candor refreshing, perhaps even liberating. Their job becomes one of imagining and designing a portfolio of possible futures, assisted by interactive computational models. Understanding and managing uncertainty is central to their job. Indeed, doing this better than competitors is a hallmark of success. This book is intended to help them understand what fundamentally needs to be done, why it needs to be done, and how to do it. The hope is that readers will discuss this book and develop a “shared mental model” of computational modeling in the process, which will greatly enhance their chances of success.

An empirical evaluation of the use of models to improve the understanding of safety compliance needs

2020 ◽  
Vol 126 ◽  
pp. 106351
Author(s):  
Jose Luis de la Vara ◽  
Beatriz Marín ◽  
Clara Ayora ◽  
Giovanni Giachetti
Keyword(s):  
Empirical Evaluation ◽  
Safety Compliance ◽  
Use Of Models
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