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EnglishIn current language, the term model indicates a specimen that is deemed worthy of being imitated, reproduced or exhibited. In scientific language, the model is a conceptual representation of a real phenomenon with an explanatory function. A model is used to analyse phenomena for the purpose of description or prediction: to understand the cause-effect relationships at the base of the phenomena to describe the functioning mechanisms, to modify them functionally for a purpose and to implement trend forecasts. The simulation can take place in various ways, thus giving rise to: i) conceptual models (the basis of any model), ii) physical models on a scale (direct simulation), iii) mathematical models (indirect simulation), iv) animal models. A scientific simulation model is, therefore, an archive of hypotheses (which limit their validity), of experimental data and of theories. Developing a scientific model of simulation involves using symbols to represent the phenomenal reality that is the object of interest; representation can have different degrees of fidelity, use different methods and simulation tools and pursue different purposes. The scientific model is a tool that serves to represent, according to the interpretative assumptions of the phenomenal reality of a certain discipline, a given phenomenon of interest. A scientific model reflects the opinions and knowledge of the model maker on the phenomenon under study: for this and other reasons (mainly related to the choice of the type of representation and the simplifying hypotheses adopted), different models are possible for the same system in the studio. As a result, a scientific model is always a simplified representation of the phenomenon of interest, functional to a specific objective. The model is therefore the indispensable tool for a scientific work in function of the accumulation of knowledge for doing. From the practices developed thanks to the formulation of effective models, further and more refined conceptualizations of the phenomena can be developed, in the sign of the progress of science (heuristic function of the models).
| Titolo: | Il concetto di modello e il suo uso nelle scienze. | |
| Autori Riconosciuti: | ||
| Autori: | Enrico Prenesti | |
| Data di pubblicazione: | 2020 | |
| Abstract: | In current language, the term model indicates a specimen that is deemed worthy of being imitated, reproduced or exhibited. In scientific language, the model is a conceptual representation of a real phenomenon with an explanatory function. A model is used to analyse phenomena for the purpose of description or prediction: to understand the cause-effect relationships at the base of the phenomena to describe the functioning mechanisms, to modify them functionally for a purpose and to implement trend forecasts. The simulation can take place in various ways, thus giving rise to: i) conceptual models (the basis of any model), ii) physical models on a scale (direct simulation), iii) mathematical models (indirect simulation), iv) animal models. A scientific simulation model is, therefore, an archive of hypotheses (which limit their validity), of experimental data and of theories. Developing a scientific model of simulation involves using symbols to represent the phenomenal reality that is the object of interest; representation can have different degrees of fidelity, use different methods and simulation tools and pursue different purposes. The scientific model is a tool that serves to represent, according to the interpretative assumptions of the phenomenal reality of a certain discipline, a given phenomenon of interest. A scientific model reflects the opinions and knowledge of the model maker on the phenomenon under study: for this and other reasons (mainly related to the choice of the type of representation and the simplifying hypotheses adopted), different models are possible for the same system in the studio. As a result, a scientific model is always a simplified representation of the phenomenon of interest, functional to a specific objective. The model is therefore the indispensable tool for a scientific work in function of the accumulation of knowledge for doing. From the practices developed thanks to the formulation of effective models, further and more refined conceptualizations of the phenomena can be developed, in the sign of the progress of science (heuristic function of the models). | |
| Volume: | 6 | |
| Pagina iniziale: | 149 | |
| Pagina finale: | 161 | |
| Nome del convegno: | Scuola Permanente per l’Aggiornamento degli Insegnanti di Scienze Sperimentali “I modelli nelle Scienze”. | |
| Luogo del convegno: | Agrigento | |
| Anno del convegno: | 22-27 luglio 2019 | |
| URL: | http://math.unipa.it/~grim/quaderno_2020_numspec_6.htm | |
| Rivista: | QUADERNI DI RICERCA IN DIDATTICA | |
| Appare nelle tipologie: | 04B-Conference paper in rivista |
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| File | Descrizione | Tipologia | Licenza | |
|---|---|---|---|---|
| QRD_2020_NumSpec_6.pdf | PDF EDITORIALE | Open Access Visualizza/Apri |
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