Contenido

La experimentación puede ser un trabajo de campo o de laboratorio. El modelo de método usado para la simulación sería teórico, conceptual o sistémico.

Después de confirmar la hipótesis podemos ya diseñar un teorema. Finalmente si este es admitido puede convertirse en una teoría o en una ley.

Theoretical model

The theoretical model must contain the elements required for the simulation. An example with laboratory work is a computer statistics program that generates random numbers and contains the statistics of the mean and its different versions: quadratic-arithmetic-geometric-harmonic. In addition, it must be able to determine the normality in terms of probability of the generated series. The working hypothesis is that the mean and its versions also determine the normality of the series. It is experimental laboratory work. If the hypothesis is true we can establish a theorem, theory or law.

It is the main model of an entire scientific investigation, thanks to it we can define or conclude the hypothesis, predictions, etc.

Conceptual model

The conceptual model aims to establish, through a questionnaire and with field work, the importance of discrimination or rejection in a community and to do so through a questionnaire in the form of a simulation with an attitude scale. After seeing if the population is representative or adequate, now the simulation is the application of the questionnaire and the model is the questionnaire to confirm or reject the hypothesis of whether there is discrimination in the population and towards which group of people and on what issues. A large part of the simulations are of this type with conceptual models.

Systemic model

The systemic model is built using system dynamics as a methodology. The social system is simulated in one of its total representations. Systems analysis is a total representation. A development plan in the transportation segment with a human ecology model, for example. The emphasis on general systems theory is appropriate in this type of simulations. This method, which is for a complex system, is extremely abstract, and is not limited to the description of the system, but must include in the simulation the inputs and outputs of energy and the processes of homeostasis, autopoiesis and feedback.[4]​.

Both the statistics program, the attitude scale and the total system are perfect simulations of reality and model all the elements in their respective working hypotheses. They are also a microclimate and the environment or scenario in simulation/experimentation processes. Other properties that simulations must contain is that they be repeatable indefinitely. That they avoid the learning effect that encourages the interviewer to fill out the questionnaires himself and that can be avoided with some control, that they are flexible or improvable and that it is not invasive or changing the population of successive samples.

It is an attempt to model real-life situations through a computer program, which requires studying to see how the system works. Either by changing variables, perhaps predictions made about the behavior of the system.

Computer simulation has become a useful part of modeling many natural systems in physics, chemistry and biology, and human systems such as economics and social sciences (computational sociology),[3] as well as directing to gain penetration (depth) their behavior will change each simulation depending on the set of initial parameters assumed by the environment. Computer simulations are often considered humans outside of a simulation loop.

Traditionally, the formal modeling of systems has been through a mathematical model, which attempts to find analytical solutions to problems that allow the prediction of the behavior of a system from a set of parameters and initial conditions. Computer simulation is frequently used as an accessory to, or replacement for, modeling systems for which simple closed-form analytical solutions are not possible. There are many different types of computer simulation, the common characteristic that they all share is the attempt to generate a sample of representative scenarios for a model in which a complete enumeration of all possible states would be prohibitive or impossible. Several software packages exist for computer modeling, such as Vensim"), Stella or Powerim, and thus the simulation is done without great effort (for example: Monte Carlo simulation and stochastic modeling such as Risk Simulator).

It is increasingly common to hear about simulations of many classes designated as "synthetic environments." This label has been adopted by expanding the definition of "simulation", which encompasses virtually any computerized representation.[5]​.

In computing, simulation has even greater specialized meaning: Alan Turing used the term "simulation" to refer to what happens when a digital computer runs a state table (runs a program) that describes the state transitions, inputs and outputs of a machine.

In programming, a simulator is often used to run a program that has to run on certain types of computer problems or in a rigorous test controller environment. For example, simulators are frequently used to debug a microprogram (microcode) or sometimes commercial application programs. Since computer operation is simulated, all information about computer operation is directly available to the programmer, and speed and execution can vary at will.

Simulators can be used to interpret security engineering or VLSI logic design testing, before they are built. In theoretical computer science the term "simulation" represents a relationship between state transition systems. This is used in the study of operational semantics.

In the area of ​​science they are of great help since students relate abstract concepts with real ones (the collision of molecules) and it also helps in the sense of resources since you only have to have a couple of computers and not with all the equipment of an entire laboratory.

Simulation is used in the training or preparation of both civil and military personnel; This happens when it is prohibitively expensive or simply too dangerous to allow a trainee to use real equipment in the real world. In the latter situation they will learn valuable lessons in a safe virtual environment. The convenience is to allow for errors during training for a safety critical system.

Simulated training typically comes in three categories:.

This type of simulation is somewhat similar to training or preparation. They focus on specific tasks. In the past, videos were used by teachers to educate students, teaching them to observe, solve problems and play a role; However, it has been displaced by simulation, since it includes animated narrative vignettes, which can be videos of hypothetical cartoons and stories based on reality, involving the class in teaching and learning. It is also used to evaluate learning, problem-solving children's abilities and dispositions, and teachers' service.

Simulation in education allows the learner to reach knowledge through exploratory work, inference, learning by discovery and the development of skills involved in the investigation of a phenomenon of a physical or social nature, developing certain actions, skills and habits of the topic or specialty and problem solving.

Simulation in education consists of placing a student in a context that imitates some aspect of reality and establishing in that environment situations, problematic or reproductive, similar to those that could occur in reality. Thus, the person who performs the simulations to learn about some aspect, whether about their knowledge, skills or attitudes;[6]​ is prepared for when they happen in their life. For example: carry out a simulation on how to act in conflicts in the classroom, simulations on first aid, etc.

Experiments based on techniques such as NMR spectroscopy provide detailed data on the behavior of matter. However, to interpret these experiments and to obtain greater resolution in space and time, we have to resort to theoretical models. Analytical resolution of these models is impossible for most systems of practical interest. Therefore, it is necessary to resort to the numerical resolution of these models in the form of simulations. A simulation seeks to recreate the elements that are considered important in the reproduction of an empirically observed phenomenon. Important examples are molecular dynamics and computational chemistry, both widely used to study protein folding in biophysics, and the mechanical properties of artificial polymers in materials science.

This type of simulation is increasingly developing and is being increasingly deployed to teach therapeutic and diagnostic procedures, as well as concepts and decision making to personnel in the medical professions. Simulators have been developed for training in a range of basic procedures such as blood transfusion, laparoscopic surgery, trauma care, pulmonary and cardiac auscultation and others.

Contenido

La experimentación puede ser un trabajo de campo o de laboratorio. El modelo de método usado para la simulación sería teórico, conceptual o sistémico.

Después de confirmar la hipótesis podemos ya diseñar un teorema. Finalmente si este es admitido puede convertirse en una teoría o en una ley.

Theoretical model

The theoretical model must contain the elements required for the simulation. An example with laboratory work is a computer statistics program that generates random numbers and contains the statistics of the mean and its different versions: quadratic-arithmetic-geometric-harmonic. In addition, it must be able to determine the normality in terms of probability of the generated series. The working hypothesis is that the mean and its versions also determine the normality of the series. It is experimental laboratory work. If the hypothesis is true we can establish a theorem, theory or law.

It is the main model of an entire scientific investigation, thanks to it we can define or conclude the hypothesis, predictions, etc.

Conceptual model

The conceptual model aims to establish, through a questionnaire and with field work, the importance of discrimination or rejection in a community and to do so through a questionnaire in the form of a simulation with an attitude scale. After seeing if the population is representative or adequate, now the simulation is the application of the questionnaire and the model is the questionnaire to confirm or reject the hypothesis of whether there is discrimination in the population and towards which group of people and on what issues. A large part of the simulations are of this type with conceptual models.

Systemic model

The systemic model is built using system dynamics as a methodology. The social system is simulated in one of its total representations. Systems analysis is a total representation. A development plan in the transportation segment with a human ecology model, for example. The emphasis on general systems theory is appropriate in this type of simulations. This method, which is for a complex system, is extremely abstract, and is not limited to the description of the system, but must include in the simulation the inputs and outputs of energy and the processes of homeostasis, autopoiesis and feedback.[4]​.

Both the statistics program, the attitude scale and the total system are perfect simulations of reality and model all the elements in their respective working hypotheses. They are also a microclimate and the environment or scenario in simulation/experimentation processes. Other properties that simulations must contain is that they be repeatable indefinitely. That they avoid the learning effect that encourages the interviewer to fill out the questionnaires himself and that can be avoided with some control, that they are flexible or improvable and that it is not invasive or changing the population of successive samples.

It is an attempt to model real-life situations through a computer program, which requires studying to see how the system works. Either by changing variables, perhaps predictions made about the behavior of the system.

Computer simulation has become a useful part of modeling many natural systems in physics, chemistry and biology, and human systems such as economics and social sciences (computational sociology),[3] as well as directing to gain penetration (depth) their behavior will change each simulation depending on the set of initial parameters assumed by the environment. Computer simulations are often considered humans outside of a simulation loop.

Traditionally, the formal modeling of systems has been through a mathematical model, which attempts to find analytical solutions to problems that allow the prediction of the behavior of a system from a set of parameters and initial conditions. Computer simulation is frequently used as an accessory to, or replacement for, modeling systems for which simple closed-form analytical solutions are not possible. There are many different types of computer simulation, the common characteristic that they all share is the attempt to generate a sample of representative scenarios for a model in which a complete enumeration of all possible states would be prohibitive or impossible. Several software packages exist for computer modeling, such as Vensim"), Stella or Powerim, and thus the simulation is done without great effort (for example: Monte Carlo simulation and stochastic modeling such as Risk Simulator).

It is increasingly common to hear about simulations of many classes designated as "synthetic environments." This label has been adopted by expanding the definition of "simulation", which encompasses virtually any computerized representation.[5]​.

In computing, simulation has even greater specialized meaning: Alan Turing used the term "simulation" to refer to what happens when a digital computer runs a state table (runs a program) that describes the state transitions, inputs and outputs of a machine.

In programming, a simulator is often used to run a program that has to run on certain types of computer problems or in a rigorous test controller environment. For example, simulators are frequently used to debug a microprogram (microcode) or sometimes commercial application programs. Since computer operation is simulated, all information about computer operation is directly available to the programmer, and speed and execution can vary at will.

Simulators can be used to interpret security engineering or VLSI logic design testing, before they are built. In theoretical computer science the term "simulation" represents a relationship between state transition systems. This is used in the study of operational semantics.

In the area of ​​science they are of great help since students relate abstract concepts with real ones (the collision of molecules) and it also helps in the sense of resources since you only have to have a couple of computers and not with all the equipment of an entire laboratory.

Simulation is used in the training or preparation of both civil and military personnel; This happens when it is prohibitively expensive or simply too dangerous to allow a trainee to use real equipment in the real world. In the latter situation they will learn valuable lessons in a safe virtual environment. The convenience is to allow for errors during training for a safety critical system.

Simulated training typically comes in three categories:.

This type of simulation is somewhat similar to training or preparation. They focus on specific tasks. In the past, videos were used by teachers to educate students, teaching them to observe, solve problems and play a role; However, it has been displaced by simulation, since it includes animated narrative vignettes, which can be videos of hypothetical cartoons and stories based on reality, involving the class in teaching and learning. It is also used to evaluate learning, problem-solving children's abilities and dispositions, and teachers' service.

Simulation in education allows the learner to reach knowledge through exploratory work, inference, learning by discovery and the development of skills involved in the investigation of a phenomenon of a physical or social nature, developing certain actions, skills and habits of the topic or specialty and problem solving.

Simulation in education consists of placing a student in a context that imitates some aspect of reality and establishing in that environment situations, problematic or reproductive, similar to those that could occur in reality. Thus, the person who performs the simulations to learn about some aspect, whether about their knowledge, skills or attitudes;[6]​ is prepared for when they happen in their life. For example: carry out a simulation on how to act in conflicts in the classroom, simulations on first aid, etc.

Experiments based on techniques such as NMR spectroscopy provide detailed data on the behavior of matter. However, to interpret these experiments and to obtain greater resolution in space and time, we have to resort to theoretical models. Analytical resolution of these models is impossible for most systems of practical interest. Therefore, it is necessary to resort to the numerical resolution of these models in the form of simulations. A simulation seeks to recreate the elements that are considered important in the reproduction of an empirically observed phenomenon. Important examples are molecular dynamics and computational chemistry, both widely used to study protein folding in biophysics, and the mechanical properties of artificial polymers in materials science.

This type of simulation is increasingly developing and is being increasingly deployed to teach therapeutic and diagnostic procedures, as well as concepts and decision making to personnel in the medical professions. Simulators have been developed for training in a range of basic procedures such as blood transfusion, laparoscopic surgery, trauma care, pulmonary and cardiac auscultation and others.