Teaching students computer modeling using interactive environments. Modern problems of science and education Teaching computer modeling article
POSSIBILITIES OF APPLICATION OF COMPUTER SIMULATION IN THE PROCESS OF SELF-ACTUALIZATION OF A COMPUTER SCIENCE TEACHER IN THE MODERN EDUCATIONAL SPACE
© 2016 E. I. Travkin
cand. ped. Sciences, Associate Professor of the Department of Computer Technologies and Informatization of Education e-mail: e [email protected] en
Kursk State University
The article presents the possibilities of using computer modeling as one of the methods for implementing self-actualization of a computer science teacher at all levels of the higher education system, the characteristics of computer modeling as an effective method of cognition in an information educational environment. In work special place devoted to the description of the principles of training computer simulation and stages of computer modeling, the implementation of which contributes to the self-actualization of computer science teachers.
Key words: computer simulation method, model, professional self-actualization of an informatics teacher, multilevel system of higher education, professional training.
One of the most important trends in modern vocational education is informatization, which allows you to bring the educational process to a new qualitative level and reveal the potential of teaching staff in a new way in modern sociocultural conditions. The modern rapidly changing and rapidly developing information environment makes great demands for the self-actualization of a modern computer science teacher.
Government program Russian Federation"Information Society (2011-2020)" and the National Doctrine of Education of the Russian Federation until 2025 emphasize the need for significant changes regarding possible methods for modernizing the existing educational process in various fields based on the use of information technologies.
One of the most effective methods training in modern conditions of modernization educational system is the use of computer simulation method. Computer modeling is a fairly universal research method in various subject areas. modern science. Computer modeling is understood as a research method based on the construction and study of a computer model of an object or process [Pikalov 2010]. The main specific feature of computer simulation is the possibility of its use for a holistic study of the object under study.
When creating and studying a computer model, the process of displaying and reproducing an analogue or substitute object of a real-life or projected system and process takes place, not only the structure, elements, properties are revealed, but also the relationships and relationships between elements and external environment. Computer modeling, representing a kind of modeling, allows you to describe the system or process under study only with a certain degree of approximation to reality, taking into account existing relationships and
patterns between the main components of the original object. The end result of computer simulation is to obtain quantitative and qualitative characteristics necessary for the analysis of the systems or processes under study, decision-making on their optimization and modernization, predicting behavior in various conditions.
Modeling can be defined as one of the main methods of cognition, which is a form of reflection of reality and consists in clarifying or reproducing certain properties of real objects, objects and phenomena using other objects, processes, phenomena, or using an abstract description in the form of an image, plan, maps, sets of equations, algorithms and programs [Biryukov, Gasteev, Geller 1974].
A future computer science teacher should be able to realize his personal and professional potential in relation to meaningful and theoretical aspects professional activity. The adequacy of modern pedagogical methods ensures the productivity of self-actualization. Wide opportunities in solving problems of self-actualization are provided by the method of computer simulation.
Self-actualization is a factor that ensures the competitiveness of a modern computer science teacher, expanding his personal and professional potential in the face of constantly changing complex tasks in the modern educational space.
Self-actualization is the main topical problem of higher education. "Self-actualization" (from the Latin asShaNB - real, real) is considered as a person's desire for the fullest possible identification and development of their personal capabilities [Karpenko 1985].
Professional self-actualization determines the effectiveness of the formation and development of a future computer science teacher in the process of solving ever more complex tasks at various levels modern education: in specialized classes (information technology), on average vocational education, in the system of teaching undergraduate and graduate students, in the system of additional professional education.
The organization of the learning process based on computer simulation, aimed at self-actualization of a computer science teacher, is based on a system of didactic principles that are reflected in the works of classical and modern authors - I.P. Podlasogo, Yu.K. Babansky, L.V. Zankova, V.A. Slastenina, etc. All didactic principles represent a single system and are aimed at achieving educational, cognitive, developmental tasks, the solution of which contributes to the comprehensive self-actualization of an informatics teacher at various stages of his formation and development. A system of defining principles for the implementation of computer modeling in the process of self-actualization of a future teacher of informatics, which reflect the main patterns of the educational process, has been revealed. It seems appropriate to highlight the following principles in the process of self-actualization of the future teacher:
1) the principle of scientific character, which provides for the use in the educational process of the latest achievements in the field of computer modeling for the organization of research and scientific research activities of students;
2) the principle of accessibility, which implies the adequacy of the studied material to the age and individual characteristics of students and the level of their theoretical and practical training;
3) the principle of visibility, which ensures the construction of a computer model in a visual form that most adequately reveals the essential connections and relationships of the systems or processes under study;
4) the principle of systematicity, which involves consideration various kinds competencies, acquired knowledge and formed skills and abilities in the system of building all training courses and the entire content of training as systems that are included in each other and in common system information culture, and requiring rational division educational material on semantic fragments and gradual mastery of them with constant reference to the whole;
5) the principle of succession, which consists in planning the content that develops in an ascending line, where each new knowledge relies on the previous one and follows from it;
6) the principle of connection between theory and practice, which implies that the knowledge acquired by students interacts with life, is applied in practice, used to study, cognize and transform the surrounding processes and phenomena; awareness of the importance of acquired knowledge contributes to an increase in interest in learning, which has a positive effect on motivation and efficiency learning activities;
7) the principle of activity, which provides for a clear understanding of the studied educational material. In order to organize the active assimilation of knowledge by students and the development of independence of mental actions during the educational process, it is necessary to put forward a cognitive task, the solution of which allows motivating creative search and mental activity;
8) the principle of flexibility of computer models, understood as their correspondence to a real object and their consistency with other models that form a system of knowledge in a given subject area and in the content of education in general, as well as the possibility of prompt modernization of the computer model under study in the course of experimental work;
9) the principle of integrativity, which provides for the possibility of integrating the developed models in various conditions of the educational space; this principle also provides for the integration of various disciplines, fields and areas of activity in order to solve specific pedagogical tasks;
10) the principle of openness, which provides the possibility of permanent modification of the created computer model, depending on the needs and conditions of training.
Organization of the educational process based on the use of computer
modeling aimed at self-actualization of a computer science teacher,
should follow the following steps [Kelton, Lowe 2004]:
Task formulation;
Collection of data (information) and definition of the conceptual model;
Determination of the adequacy of the conceptual model;
Formalization or creation of a mathematical model;
Creation of a computer model;
Checking the computer model;
Experiment planning;
Performing experiments with a computer model;
Analysis and interpretation of output data;
Use of results.
The identified stages are performed iteratively, that is, there is a return to
previous stages and their re-execution in order to clarify some
parameters of the developed model. The presented sequence of stages reflects the general approach to conducting computer simulation on the objects under study and allows you to follow the methodology of computer simulation when organizing the learning process.
It is important to emphasize that the stages of computer simulation almost completely correspond to the stages of exploratory learning. In its expanded form, exploratory learning assumes that the student:
Identifies and poses a problem to be solved;
Offers possible solutions;
Checks these possible solutions;
Based on the data, draws conclusions in accordance with the results;
Applies inferences to new data; makes generalizations.
According to the supporters of research education, the educational process should ideally model the process of scientific research, the search for new knowledge [Klarin 1998]. The correspondence of the stages, as well as the methodology of computer modeling and research training, makes it possible to actively introduce this method into the learning process as a way to develop the research abilities of students, which contributes to the self-actualization of future teachers of computer science.
As a result of computer simulation, students create a computer model. A computer model is understood as [Lychkina 2000]:
□ a conditional image of an object or some system, described with the help of interconnected computer tables, flowcharts, diagrams, graphs, drawings, animation fragments, hypertexts, etc. and showing the structure and relationships between the elements of the object - a structural-functional model;
□ a separate program, a set of programs, a software package that allows, using a sequence of calculations and a graphical display of their results, to reproduce (simulate) the processes of the object's functioning under the influence of various (including random) factors on it - simulation models. In the work of I.Yu. Pikalov determines that the use of simulation modeling for the analysis of complex systems is based on the development of statistical test methods (Monte Carlo method), which allow modeling random factors using computer technology, which leads to faster calculations and experiments with complex systems [Pikalov 2014].
The concept of a model lends itself to the method of using computer simulation in educational process that broad spectrum intersubject communications, the formation of which is one of the main tasks of self-actualization of an informatics teacher. The very activity of building a model - modeling - is a generalized type of activity that characterizes computer science [Kasprazhak 2004]. In addition, the concepts and modeling method are studied on models of various subject areas revealing their commonality. Accounting for intersubject communications is a necessary condition successful learning. The development of thinking and outlook of students depends on how this connection is carried out. In addition, the correct implementation of interdisciplinary connections contributes to the formation of a scientific worldview, helps students to discover the relationship between objects and phenomena in the world around them, and creates a holistic view of the studied phenomena and processes of the real world [Volodin 2005].
The organization of the educational process on the basis of interdisciplinary connections contributes to the involvement of students in the subject-practical activity, which involves the active acquisition of knowledge, their creative use, the development of cognitive
activity and independence, the formation of a scientific worldview. The formation of interdisciplinary connections based on modeling is determined by the use of a number of methods for obtaining knowledge and skills (analysis, synthesis, induction, deduction, etc.).
In turn, A.V. Yastrebov in his dissertation research [Yastrebov 2003] notes that “ highest goal education is the training of a specialist who is able to independently formulate problems in the field of professional activity and solve them...”, “... higher education should educate a specialist with the self-awareness of a researcher, regardless of whether it is a scientist in the narrow sense of the word, a scientist-engineer or a scientist-teacher.
The process of creating computer models has a huge developmental potential and contributes to a more efficient flow of the process of self-actualization at all stages of the formation and development of a professional in the field of teaching computer science. Possession of the basics of computer modeling is a channel for the implementation of developmental education, which allows you to bring the teacher to a new qualitative level and achieve not only the heights of professional competence, but personal development.
Bibliographic list
Biryukov B.V., Gasteev Yu.A., Geller E.S. Modeling. M.: BSE, 1974.
Volodin A.A. Computer simulation modeling in the study of the basics of digital technology by future technology teachers: dis. ... cand. ped. Sciences: 13.00.02. M., 2005
Kelton W., Lowe A. Simulation modeling. CS classic. 3rd ed. St. Petersburg: Peter; Kyiv: BHV Publishing Group, 2004. 847 p.: ill.
Klarin M.V. Innovations in world pedagogy: Learning based on research, games, discussions, analysis of foreign experience. M., Riga: Pedagogical Center "Experiment", SPC "Experiment", 1998. 180 p.: ill.
Brief psychological dictionary / comp. L.A. Karpenko; under total ed. A.V. Petrovsky, M.G. Yaroshevsky. M.: Politizdat, 1985. 431 p.
Lychkina N.N. Modern trends in simulation modeling // Bulletin of the University. Series "Information management systems". M.: GUU, 2000. No. 2.
Pikalov I.Yu. The study of computer modeling in the course "Information and communication technologies in science and production" // Science and modernity. 2010. No. 6-1. pp. 307-312.
Pikalov I.Yu. Application of simulation modeling and expert systems in economic analysis // Auditorium. Electronic scientific journal of Kursk State University. 2014. No. 4 (4). pp. 93-95. URL: http://auditorium.kursksu.ru/pdf/004-017.pdf
Elective courses in professional education: Educational area"Informatics" / ed. ed. A.G. Kasprazhak, Ministry of Education of the Russian Federation -National Foundation staff training. M.: Vita-Press, 2004. 112 p.
Yastrebov A.V. Modeling scientific research as a means of optimizing student learning pedagogical university: dis. doc. ped. Sciences: 13.00.08. M., 2003.
Lewy A. Planning the school curriculum. Paris, 1977.
R. P. Romansky
Technical University, Sofia, Bulgaria
Introduction
For development computer technology and improvement of the architectural organization of computer systems (CS) is necessary continuous learning and self-improvement of computer professionals and students. This training should combine forms of traditional learning with opportunities for self-study, distance learning, hands-on project development and research experiments. essential role when studying in the field computer science performs the application modern methods study of the architectural organization and analysis of the system performance of the COP. In this sense, the use of modeling methods in the process of studying the basic structures of various CSs and the organization of computer processes makes it possible to develop a suitable mathematical description of the object under study and create software for performing computer experiments[Romansky, 2001, Arons, 2000]. Analysis experimental results simulation [Bruyul, 2002] makes it possible to evaluate the main characteristics of the system and the performance of the studied CS.
The use of modeling in the process of studying the CS allows us to explore the features of the architecture and the organization of computation and control. This can be done on the basis of a model experiment, the organization of which involves designing a computer model as a sequence of three components (conceptual model, mathematical model, software model) and implementing this model in a suitable operating environment. In this paper, we consider the possibility of using different methods for studying CSs in the process of studying them, and in particular, the application of modeling principles for studying ongoing processes, as well as analyzing the system performance of CSs. The main goal is to define a generalized computer modeling procedure as a sequence of interrelated steps and to present the main stages of the modeling research methodology. To do this, the next part presents the general formalization of computer processing of information and the features of computer computing as an object of study. The application of modeling principles in the process of studying CS is associated with the methodological organization of learning in the traditional, distance, or distributed sense.
Computer systems as an object of study and research methods
One of the main objectives of specialized training courses in the field of computer systems and performance research is to train future and current computer designers, developers of computer equipment and users of CS in the correct use of the technological capabilities of modeling and measuring the characteristics of systems. These possibilities are used both in the process of evaluating the effectiveness of new computer projects, and for conducting comparative analysis existing systems. In the learning process, the task is to clarify the sequence of research stages and the possibility of processing experimental results in order to obtain adequate estimates of performance indices. This task can be refined depending on the specific area. computer learning and features of the principles of the considered computer processing of information.
Rice. 1. Information support of computer processing.
In general, computer processing is concerned with the implementation of certain functions to transform input data into final solutions. This determines two levels of functional transformation of information (Fig. 1):
mathematical transformation of information - real data processing in the form of mathematical objects and is represented by a generalized function f:D®R, which depicts the elements of the data set D in the elements of the result set R;
computer implementation of processing - represents a specific implementation f*:X®Y of the mathematical function f depending on the computer and software equipment based on a suitable physical representation of real information objects.
As a result, we can write a generalized functional model of computer processing r = f(d)ºj 2 (f*[ 1(d)]), where the functions j 1 and j 2 are auxiliary for encoding and decoding information.
Considering the CS as an object of study, one must keep in mind that computer processing consists of processes, each of which can be represented as a structure I =
Rice. 2. Approximate profile of the computer process.
Support of different processes in the organization of computer processing forms the system load of the computer environment. For each moment (t =1,2,...) it can be represented by the vector V(t)=Vt=
When studying the CS, it is necessary to determine a set of basic system parameters that reflect the essence of computer processing, as well as to develop a methodology for studying the behavior of a system resource and ongoing processes. As the main system parameters (performance indices), one can study, for example, the workload of each element of the system resource, the total system load of the CS, the response time when solving a set of tasks in a multiprogram mode, the degree of stability (persistence) of equipment, the cost of computer processing, the efficiency of scheduling parallel or pseudo-parallel processes, etc.
A typical course of study in the field of analysis and research of CS performance should discuss the main theoretical and practical problems in the following areas:
the possibility of studying the performance of computer equipment and the efficiency of computer processes;
application of effective research methods (measurement, modeling);
technological features of measuring system parameters (benchmark, monitoring);
technological features and organization of modeling (analytical, simulation, etc.);
methods of analysis of experimental results.
All this is connected with the application of this research method and the choice of suitable tools. In this sense, in Fig. 3 shows an approximate classification of methods for studying CS and processes. Three main groups can be identified:
Software mixtures - represent mathematical dependencies for evaluating processor performance based on the application coefficients of individual operating classes. Allows you to evaluate the processor load by statistical analysis after the execution of typical programs.
Counting methods - allow you to obtain reliable information about the course of computer processes based on the direct registration of certain values of the available parameters of the COP. To do this, it is necessary to use or develop a suitable counting tool (monitor) and organize the execution of the counting experiment. It should be noted that modern operating systems have their own system monitors that can be used at the software or firmware level.
Modeling methods - are used in the case when there is no real object of the experiment. The study of the structure or ongoing processes in the CS is carried out on the basis of a computer model. It reflects the most important aspects of the behavior of structural and system parameters depending on the goal. To develop a model, it is necessary to choose the most appropriate modeling method, which allows to obtain maximum adequacy and reliability.
Rice. 3. Classification of research methods for CS and processes.
The traditional learning process involves the conduct of the main course of lectures in conjunction with a set of classroom exercises and / or laboratory practice. In the field of computer science, when studying the organization of a CS and the principles of managing computer processes (at a low and high level), as well as when analyzing system performance, it often becomes necessary to develop computer models while performing laboratory tasks in the classroom or when implementing projects independently. In order to successfully complete these practical work and to obtain the necessary practical skills, it is necessary to determine the sequence of stages and present the technological features of model development. This will allow students to acquire the necessary knowledge about the development of adequate and reliable computer models for the study, evaluation and comparative analysis of system performance of different computer architectures. As a result of this, a generalized procedure for conducting modeling is further proposed, as well as a methodological scheme for modeling the study of CS and processes.
The procedure of computer simulation in the study of CS and processes
Applying Simulation to Computer Science Education
R. P. Romansky
Technical University, Sofia, Bulgaria
Introduction
For the development of computer technology and the improvement of the architectural organization of computer systems (CS), continuous training and self-improvement of computer specialists and students is necessary. This training should combine forms of traditional learning with opportunities for self-study, distance learning, hands-on project development and research experiments. An essential role in teaching in the field of computer science is played by the use of modern methods for studying the architectural organization and analyzing the system performance of the CS. In this sense, the use of modeling methods in the process of studying the basic structures of various CSs and organizing computer processes makes it possible to develop a suitable mathematical description of the object under study and create software for performing computer experiments [Romansky, 2001, Arons, 2000]. An analysis of the experimental results of modeling [Bruyul, 2002] makes it possible to evaluate the main characteristics of the system and the performance of the studied CSs.
The use of modeling in the process of studying the CS allows us to explore the features of the architecture and the organization of computation and control. This can be done on the basis of a model experiment, the organization of which involves designing a computer model as a sequence of three components (conceptual model, mathematical model, software model) and implementing this model in a suitable operating environment. In this paper, we consider the possibility of using different methods for studying CSs in the process of studying them, and in particular, the application of modeling principles for studying ongoing processes, as well as analyzing the system performance of CSs. The main goal is to define a generalized computer modeling procedure as a sequence of interrelated steps and to present the main stages of the modeling research methodology. To do this, the next part presents the general formalization of computer processing of information and the features of computer computing as an object of study. The application of modeling principles in the process of studying CS is associated with the methodological organization of learning in the traditional, distance, or distributed sense.
Computer systems as an object of study and research methods
One of the main objectives of specialized training courses in the field of computer systems and performance research is to train future and current computer designers, developers of computer equipment and users of CS in the correct use of the technological capabilities of modeling and measuring the characteristics of systems. These possibilities are used both in the process of evaluating the effectiveness of new computer projects, and for conducting a comparative analysis of existing systems. In the learning process, the task is to clarify the sequence of research stages and the possibility of processing experimental results in order to obtain adequate estimates of performance indices. This task can be refined depending on the specific area of computer learning and the features of the principles of the considered computer processing of information.
Rice. 1. Information support of computer processing.
In general, computer processing is concerned with the implementation of certain functions to transform input data into final solutions. This determines two levels of functional transformation of information (Fig. 1):
mathematical transformation of information - real data processing in the form of mathematical objects and is represented by a generalized function f:D®R, which depicts the elements of the data set D in the elements of the result set R;
computer implementation of processing - represents a specific implementation f*:X®Y of the mathematical function f depending on the computer and software equipment based on a suitable physical representation of real information objects.
As a result, we can write a generalized functional model of computer processing r = f(d)ºj 2 (f*[ 1(d)]), where the functions j 1 and j 2 are auxiliary for encoding and decoding information.
Considering the CS as an object of study, it must be borne in mind that computer processing consists of processes, each of which can be represented as a structure I = , where: t is the initial moment of the process; A - defining attributes; T - process trace. The last component of the formal description determines the temporal sequence of events e j to address the given process to the elements of the system resource S=(S 1 , S 2 , …, S n ). The sequence of time steps and the load of the system resource make it possible to determine the profile of the calculation process (Fig. 2).
Rice. 2. Approximate profile of the computer process.
Support of different processes in the organization of computer processing forms the system load of the computer environment. For each moment (t =1,2,...) it can be represented by a vector V(t)=Vt= , whose elements express free (v j =0) or busy (v j =1) device S j єS (j=1 ,2,...,n).
When studying the CS, it is necessary to determine a set of basic system parameters that reflect the essence of computer processing, as well as to develop a methodology for studying the behavior of a system resource and ongoing processes. As the main system parameters (performance indices), one can study, for example, the workload of each element of the system resource, the total system load of the CS, the response time when solving a set of tasks in a multiprogram mode, the degree of stability (persistence) of equipment, the cost of computer processing, the efficiency of scheduling parallel or pseudo-parallel processes, etc.
A typical course of study in the field of analysis and research of CS performance should discuss the main theoretical and practical problems in the following areas:
the possibility of studying the performance of computer equipment and the efficiency of computer processes;
application of effective research methods (measurement, modeling);
technological features of measuring system parameters (benchmark, monitoring);
technological features and organization of modeling (analytical, simulation, etc.);
methods of analysis of experimental results.
All this is connected with the application of this research method and the choice of suitable tools. In this sense, in Fig. 3 shows an approximate classification of methods for studying CS and processes. Three main groups can be identified:
Software mixtures - represent mathematical dependencies for evaluating processor performance based on the application coefficients of individual operating classes. Allows you to evaluate the processor load by statistical analysis after the execution of typical programs.
Counting methods - allow you to obtain reliable information about the course of computer processes based on the direct registration of certain values of the available parameters of the COP. To do this, it is necessary to use or develop a suitable counting tool (monitor) and organize the execution of the counting experiment. It should be noted that modern operating systems have their own system monitors that can be used at the software or firmware level.
Modeling methods - are used in the case when there is no real object of the experiment. The study of the structure or ongoing processes in the CS is carried out on the basis of a computer model. It reflects the most important aspects of the behavior of structural and system parameters depending on the goal. To develop a model, it is necessary to choose the most appropriate modeling method, which allows to obtain maximum adequacy and reliability.
Rice. 3. Classification of research methods for CS and processes.
The traditional learning process involves the conduct of the main course of lectures in conjunction with a set of classroom exercises and / or laboratory practice. In the field of computer science, when studying the organization of a CS and the principles of managing computer processes (at a low and high level), as well as when analyzing system performance, it often becomes necessary to develop computer models while performing laboratory tasks in the classroom or when implementing projects independently. For the successful implementation of these practical works and to obtain the necessary practical skills, it is necessary to determine the sequence of stages and present the technological features of model development. This will allow students to acquire the necessary knowledge about the development of adequate and reliable computer models for the study, evaluation and comparative analysis of system performance of different computer architectures. As a result of this, a generalized procedure for conducting modeling is further proposed, as well as a methodological scheme for modeling the study of CS and processes.
The procedure of computer simulation in the study of CS and processes
The main task of computer simulation in the study of CS and processes is to obtain information about performance indices. Planning a model experiment in the learning process is carried out on the basis of the following steps:
collection of empirical data for specific values of basic system parameters;
structuring and processing of empirical information and development of a functional diagram of the model;
determination of a priori information and definitional areas of operating parameters for the development of a suitable mathematical model of the original object;
implementation of model experiments, accumulation of model information and its subsequent analysis.
The generalized formalized procedure of model research for the organization of model experiment is shown in fig. four.
Rice. 4. Model study procedure.
The initial goal is determined by the need to study a real object (system or process). The main steps of the procedure are as follows:
Determination of the basic concept of building a model by decomposing an object into subsystems and introducing an acceptable degree of idealization for some aspects of the behavior of system processes.
Mathematical formalization of the structure and relationships in the investigated object based on a suitable formal system.
Mathematical description of the functioning of a real system and development of a suitable functional model depending on the purpose of modeling.
Implementation of the mathematical model using the most suitable modeling method.
Description of the created mathematical model by means of a suitable software environment (specialized or universal).
Performing experiments based on the created model and subsequent processing and interpretation of model information to evaluate the parameters of the object of study.
The main methods of computer simulation are as follows:
Analytical methods - use mathematical tools to describe the components of a real system and ongoing processes. On the basis of the chosen mathematical approach, the mathematical model is usually built as a system of equations that makes it easy to program, but implementation requires high accuracy of the formulations and accepted working hypotheses, as well as significant verification.
Simulation (imitation) methods - the behavior of a real object is imitated by a software simulator, which, in its work, uses a real workload (emulation) or a software workload model (simulation). Such models allow the study of complex systems and obtaining reliable results, but they are executed in time, and this determines the main drawback of the method - a significant consumption of computer time.
Empirical methods are quantitative methods for registering, accumulating and analyzing information on the functioning of a real object, on the basis of which it is possible to build statistical model for his research. Typically, linear or non-linear equations are used to represent the relationship of selected parameters (for example, from a set of primary factors) and to calculate statistical characteristics.
The main task of computer simulation is to create an adequate model, with the help of which it is possible to accurately represent the structure of the system under study and the ongoing processes. The development of a computer model includes three successive levels - a conceptual model (an ideological concept of structuring a model), a mathematical model (an image of a conceptual model by means of a mathematical formal system) and a program model (a software implementation of a mathematical model with a suitable language environment). At each level of computer simulation, it is necessary to check the adequacy of the model in order to ensure the reliability of the final model and the accuracy of the results of model experiments. The specificity of the individual stages of the modeling procedure determines the applied approaches and means of assessing the adequacy. These features have found a place in the developed methodology of computer modeling, which is presented below.
Model Research Methodology
In the process of computer modeling, regardless of the method used, it is possible to determine the generalized matodological scheme of the model study (Fig. 5). The proposed formalized methodological sequence provides for several main phases, presented below. Basically, it represents an iterative procedure for obtaining the necessary reliability of the developed computer model based on the formulation of the initial model hypothesis and its sequential modification. This approach is successful in the study of complex systems, as well as in the absence of sufficient a priori information for the object under study.
Stage "Formulation"
At the first stage of model development, it is necessary to accurately and clearly define the object of modeling, the conditions and hypotheses of the study, as well as the criteria for evaluating model effectiveness. This will allow developing a conceptual model and defining it in abstract terms and concepts. Usually, the abstract description defines the initial principles of model building (basic approximations, definitional ranges of variables, performance criteria, and types of expected results). At this stage, the following sub-stages can be defined:
Definition and analysis of the task. Includes a clearly defined essence of the research task and planning the necessary activities. Based on the analysis of the problem, the volume of expected actions and the need for task decomposition are determined.
Specifying the type of initial information. This information makes it possible to obtain the correct output results of the simulation, and therefore it is necessary to provide the necessary level of reliability of the estimates.
Introduction of assumptions and hypotheses. This is necessary when there is not enough information to implement the model. Assumptions replace missing data or missing data completely. Hypotheses are of the type possible outcomes or to the environment for the implementation of the processes under study. During the modeling process, these hypotheses and assumptions can be accepted, rejected, or modified.
Definition of the main content of the model. On the basis of the applied modeling method, the feature of the real object, the task and the means of its solution are reported. The results of this sub-stage include the formulation of the basic concept of the model, a formalized description of real processes, and the choice of an appropriate approximation.
Determination of model parameters and selection of efficiency criteria. At this sub-stage, primary and secondary factors, input actions and expected output responses of the model are determined, which is especially important to achieve the required accuracy of the mathematical description. Refinement of efficiency criteria is associated with the definition of functional dependencies for assessing the response of the system when changing model parameters.
Abstract description of the model. The conceptual model general formulation phase completes the construction of the abstract model in a suitable environment of abstract terms - for example, in the form of a block diagram, as a flow diagram (Data Flow Diagram), in the form graphic scheme(State Transition Network), etc. This abstract representation makes it easy to build a mathematical model.
Rice. 5. Methodological scheme of the model study.
Stage "Design"
The design of a computer model is associated with the development of a mathematical model and its software description.
The mathematical model is a representation of the structure of the object under study and the ongoing processes in a suitable mathematical form Y=Ф(X, S, A, T), where: X is the set of external influences; S - set of system parameters; A - reflects functional behavior (functioning algorithms); T - running time. Thus, the behavior (reaction) of the object Y models a set of functional influences Ф, representing analytical dependencies (deterministic or probabilistic). In this sense, a mathematical model is a description of an abstract model by means of a chosen mathematical system, evaluating accepted hypotheses and approximations, initial conditions, and defined research parameters. When developing a mathematical model, it is possible to apply known mathematical formulas, dependencies or mathematical laws (for example, probability distributions), as well as combine and supplement them. The most common theoretical mathematical systems for the purpose of modeling provide an opportunity to present a mathematical model in a graphical form - Petri nets, Markov chains, queuing systems, etc. Based on the criteria determined at the previous stage, the created mathematical model must be evaluated in order to achieve the required degree of reliability and adequacy, and then you can approve or reject it.
A software model is an implementation of a mathematical description in a program language - for this, appropriate technical and technological means are selected. In the process of software implementation, a logical structural-functional scheme of the model is developed on the basis of a mathematical model. To build this circuit, you can use traditional block diagrams, or graphical tools that are represented by a specialized simulation environment - such as in GPSS (General Purpose Simulation System) . The software implementation of the model is the task of software development and, in this sense, is subject to the principles of programming technology.
Stage "Clarification"
The actions of this stage are intended for the complete validation of the designed model and approval of its adequacy. An assessment of the current adequacy at the previous stages is essential for their effectiveness. In this sense, the process of model refinement should be considered as a set of distributed actions at all previous stages of computer simulation. AT general plan, the refinement stage can be represented as an iterative procedure (Fig. 6), which allows sequential modification of the initial version of the model being developed.
Rice. 6. Iterative procedure for model refinement.
The main purpose of checking the model reliability is to determine the level of accuracy of correspondence when representing the processes of a real object and the mechanism for registering model results. In general terms, a computer model represents a collection of individual components, and in this sense it is especially important to properly plan adequacy tests.
Stage "Execution"
This is the stage of implementation of the created model (solution by a numerical method or execution in time). The main goal is to obtain maximum information for the minimum amount of machine time. There are two sub-stages:
Planning a model experiment - determining the value of controlled factors and the rules for registering observed factors when executing the model. The choice of a specific experimental design depends on the goal of the study while optimizing the execution time. To obtain an effective plan, it is usually used statistical methods(full design, one-factor design, randomized design, etc.), which allow removing the combined influence of the observed factors and estimating the allowable experimental error.
Implementation of the experiment - preparation of input data, computer implementation of the experimental plan and storage of experimental results. The implementation of the experiment can be performed as follows: control simulation (to test the performance and sensitivity of the model and estimate the model time); working simulation (actual implementation of the developed experimental plan).
Stage "Analysis and interpretation of model results"
When implementing the plan of a model experiment, information (simulation results) is accumulated, which must be analyzed in order to obtain an assessment and conclusions about the behavior of the object under study. This determines two aspects - the choice of methods for the analysis of experimental information and the use of suitable methods for interpreting the obtained estimates. The latter is especially important for the formation of correct conclusions of the study. In the sense of the first aspect, statistical methods are usually used - descriptive analyzes (calculation of boundary values of parameters, mathematical expectation, variance and root-mean-square error; determination of stratification for a selected factor; calculation of a histogram, etc.); correlation analysis (determining the level of factorial relationship); regression analysis(study of a causal relationship in a group of factors); analysis of variance (to establish the relative influence of certain factors on the basis of experimental results).
The results of the analysis of model data can be presented in numerical or tabular form, using graphical dependencies, diagrams, histograms, etc. To select the appropriate graphical tools, the analysis method used is essential, as well as the subjective skills of the experimenter to present the results of the experiment.
Conclusion
The main goal of organizing each simulation experiment is the implementation of effective simulation. It is associated with machine time - a significant amount of processing in the model increases the cost of modeling and reduces efficiency. Rapid validation of the model and achievement of convergence are essential for the effectiveness of the study. For each real system, it is often necessary to create many different models that differ in the way of decomposition and level of detail, modeling method, software implementation tools, etc. In the process of choosing the best option, only the assessment of accuracy and adequacy is insufficient. From the set of convergent models, it is necessary to choose the most efficient option that spends the minimum time on implementation.
The applied language of software implementation, as well as the completeness of the formal system of abstract representation of the conceptual model, the simplicity of the terms of description, the development of an optimal plan, etc., are essential for achieving sufficient efficiency of the model. for analytical modeling. To implement simulation models, it is good practice to use specialized language environments.
Bibliography
[Bruyul 2002] Bruyul A. SPSS: the art of information processing. Analysis of statistical data. St. Petersburg: DiaSoft, 2002, - 608 p.
[Romansky, 2001] Romansky R. Mathematical Modeling and Study of Stochastic Time Characteristics of Computer Data Processing Processes // Information Technologies. - Moscow, Russia, 2001, No 2, - S. 51 - 55.
Arons H., van Asperen E. Computer assistance for model definition // Proceedings of the 32nd Winter Simulation Conference. - Florida, USA, December 2000. - P. 399-408.
Benveniste A., Fabre E., Haar St. Markov nets: probabilistic models for distributed and concurrent systems // IEEE Transactions on Automatic Control. November 2003, vol. 48, No 11. - P. 1936-1950.
Butler J.E., Brockman J. B. A Web-based learning tool that simulates a simple computer architecture // ACM SIGCSE Bulletin. June 2001, vol. 33, no. 2. - P. 47-50.
Crosbie R. E. A model curriculum in modeling and simulation: Do we need it? Can we do it? // Proceedings of the 32nd Winter Simulation Conference. December 2000.-P. 1666-1668.
Fabre E., Pigourier V. Monitoring distributed systems with distributed algorithms // Proceedings of the 41st IEEE Conference on Decision and Control. - vol. 1. 10-13 December 2002 - P. 411-416.
Ibbett R.N. WWW Visualization of Computer Architecture Simulations // Procedings of the 7th Annual Conf. on Innovation and Technology in Computer Science Education. June 2002. - P. 247.
Lilja D.J. Comparing Instructional Delivery Methods for Teaching Computer Systems Performance Analysis // IEEE Trans. on Education. February 2001, vol. 44, No 1, - P. 35-40.
Music G., Zupancic B., Matko D. Petri net based modeling and supervisory control design in Matlab // Proceedings of the IEEE Conference EUROCON 2003 "Computers as a Tool". - vol. 1. 22-24 Sept. 2003. - Slovenia. - P. 362-366.
Pandey S., Ramamritham K., Chakrabarti S. Monitoring the dynamic Web to respond to continuous queries // Proceedings of the 12th International Conference on World Wide Web. - Hungary, May 2003, - P. 659-668.
Pockec P., Mardini W. Modeling with queues: an empirical study // Proceedings of the Canadian Conference on Electrical and Computer Engineering. - vol. 1. 13-16 May 2001. - P. 685-689.
Romansky R. et all. An Organization of Informational Network InfoNet for Distributed e-Learning // Proceedings of the 3rd International Conference on Computer Systems and Technologies (e-Learning). 20-21 June 2002. Sofia, Bulgaria. - P. IV.4-1 - IV.4-6.
Sargent R.G. Verification and validation of simulation models // Proceedings of the 2003 Winter Simulation Conference. - vol. 1. 7-10 December 2003. - P. 27-48.
Stahl, I. GPSS: 40 years of development // Proceedings of the 33rd Winter Simulation Conference. December 2001. - P. 577-585.
Ye D, Xiaofer Xu, Yuliu Chen. Integrated modeling methodology for virtual enterprises // Proceedings of the 10th Conference on Computers, Communications, Control and Power Engineering. - vol. 3. October 2002. - P. 1603-1606.
1The article deals with the organization of educational research using computer simulation methods. Analyzed General characteristics educational research as a teaching method adequate in general to the informatization of education. The features of computer modeling as a method of scientific research are described. A generalized structure of educational research is constructed using computer modeling methods, based on the stages of educational research and general scheme model building. The features of setting a goal, formulating a hypothesis, developing a system of tasks, and conducting an experiment are specified. The general logic of educational research using computer modeling methods is revealed in the form of stages of forming theoretical ideas about the object of study and determining essential properties, determining a list of parameters for a formal description of the model, choosing tool computer simulation, model building and experiment. At the end of the article, examples of setting up educational research implemented using computer simulation methods are given.
educational project
study study
computer modelling
1. Korolev A.L. Computer modelling. M.: BINOM. Knowledge Laboratory, 2010. - 230 p.
2. Korotkov A.M. Theoretical and methodological system of preparing students for learning in a computer environment: dissertation…. Dr. ped. Sciences. - Volgograd, 2004. - 341 p.
3. Leontovich A.V. On the basic concepts of the concept of development of research and project activities students // Research work of schoolchildren. - 2003. - No. 4. - S. 18–24.
4. Letsko V.A. Didactic conditions for using a computer as a means of teaching future teachers to solve search problems: dis. ... cand. ped. Sciences. - Volgograd, 1995. - 158 p.
5. New pedagogical and information technologies in the education system: Proc. allowance for students. ped. universities and systems of higher education. qualified ped. personnel / E.S. Polat, M.Yu. Bukharkina, M.V. Moiseeva, A.E. Petrov / Ed. E.S. Polat. - M.: Publishing Center "Academy", 1999. - 224 p.
6. Petrov A.V. Methodological and methodological foundations personality-developing computer education: Monograph. Volgograd: Change, 2001. 266 p.
7. Samarskii A.A., Mikhailov A.P. Mathematical modeling: Ideas. Methods. Examples. - Ed. 2nd, rev. - M.: Fizmatlit, 2001. - 320 p.
8. Sergeev A.N. Computer technologies as a means of personal development in the learning process: new opportunities // Proceedings of the Volgograd State Pedagogical University. Series " pedagogical sciences": Science Magazine. - 2005. - No. 1 (10). - S. 80–85.
9. Sovetov B.Ya., Yakovlev S.A. Systems Modeling: Proc. for universities - Ed. 3rd, revised. and additional - M.: Higher. school, 2001. - 343 p.
Information technologies are widely used in the educational process. In 1985, a computer science course was included in the structure of school and university education, within which much attention was paid to the formation of algorithmic thinking and computer programming. At the same time, the development of software tools was carried out. educational purpose across a range of academic disciplines. The computer and training programs were considered as a new learning tool that provides the formation of knowledge and skills of students, taking into account the possibilities of individualization and differentiation, control, development of stable skills for performing certain operations. In the future, ideas about the possibilities and ways of using information technology in education have expanded and changed somewhat. The computer began to be understood as an element of a broader, holistic didactic computer environment, and the leading idea of informatization of education was the understanding that new information technologies should ensure, first of all, the development and implementation of new pedagogical technologies that meet today's needs.
Thus, at present, we can say that achieving the goals of informatization of education is impossible only through the use of informatization tools, the use of a computer as a means of working with information in previously established learning models. Along with the advent of technical means, teaching methods must also change, adequate to the social demand for a change in education. In many ways, these methods are associated with project-based learning technologies that involve active position student.
As indicated in the works of E.S. Polat, the project activity of students is a joint educational, cognitive, creative or gaming activity, has common goal, agreed methods, methods of activity, aimed at achieving overall result activities. An indispensable condition for project activity is the presence of pre-developed ideas about the final product of the activity, the stages of design and implementation. E.S. Polat notes that the project always begins with the formulation of a problem (task) that is significant in terms of research and creativity, requiring integrated knowledge, research search for its solution.
The educational project, thus, becomes a method of organizing educational research, a motivational basis for its implementation. Research naturally becomes an integral part of the educational project, since in order to achieve the goals of the project it requires the acquisition of new knowledge, which is understandable and obvious to students.
Analyzing the features of the research activities of students, A.V. Leontovich points out that the purpose of educational research is the acquisition by students of the functional skill of research activity as a universal way of mastering reality, the development of the ability for a research type of thinking, the activation of the student's personal position in the educational process based on the acquisition of subjectively new knowledge. At the same time, the effective organization and implementation of educational research directly depends on the design of the study. Educational research assumes the presence of the main stages characteristic of research in the scientific field: 1) problem statement; 2) study of theory related to the chosen topic; 3) putting forward hypotheses; 4) selection of research methods and practical mastery of them; 5) collection of own material, its analysis and generalization; 6) formulation of conclusions.
Taking the described A.V. Leontovich stages of research, we consider it necessary to pay attention to the fact that all modern research(both in the educational process and in "big" science) are implemented using information technology. At a minimum, this applies to the stages of studying information sources, collecting, storing and processing own data, and formalizing the results of the study. At the same time, there is reason to assert that the possibilities of information technology are realized to the greatest extent in situations where research activities involves the use of methods based on modeling the studied objects and phenomena in a computer environment.
What is the feature research work carried out using computer simulation methods? Modeling as the construction and study of models of real objects and phenomena is the most important research method. The main feature of such studies is that modeling is a method of indirect cognition, in which the original object under study is in some correspondence with another model object, and the model is capable of replacing the original in one way or another at some stages of the cognitive process. The modeling process assumes the presence of: 1) the object of study; 2) a researcher who is assigned a specific task; 3) a model created to obtain information about the object and necessary to solve the problem.
A. L. Korolev distinguishes the following main stages in the general model construction scheme.
- Based on the existing problem, a research task is formulated, which includes a description of the modeling object.
- The simulation object is analyzed: it is established what elements the object consists of, how they interact with each other. The properties of the object that are relevant for solving the problem are set. The factors that determine these properties are identified.
- The actual creation of the model is performed, while choosing the type of model and the method of its construction.
- The issue of interpreting the simulation results (if necessary) is being resolved, i.e. about how the results of the experiment with the model will be transferred to the real object.
- Experiments are carried out with the model, its adequacy is checked (the degree of correspondence between the model and the object in terms of the modeled properties).
- The model is corrected or reworked (in case of insufficient adequacy).
- The model is used to solve the problem .
With the advent of computer technology, modeling has received a new and very powerful resource for its implementation, since traditional analytical methods for building models have been supplemented by the capabilities of computer calculations. In this case, calculations are performed automatically, in accordance with a given algorithm, and do not require human intervention.
A.A. Samarsky proposed to break the process of computer modeling into three stages: "model - algorithm - program". This methodology has been developed in the form of a computational experiment technology for conducting theoretical research. The basis of the computational experiment is mathematical modeling and the use of computer technology.
Development of A.A. Samarsky is also seen in the aspect of using software for preparing models - algorithms can be developed not only in the form of computer programs for known programming systems, but also step-by-step instructions for various mathematical packages, as well as specialized computer modeling tools. The use of special computer simulation packages allows you to quickly build models, conduct experiments with them, analyze and visualize simulation results. The implementation of models does not require the use of any programming system, which can significantly reduce the complexity of developing models and time spent on development.
Conducting an educational study using computer modeling methods, therefore, involves the construction and study of a model of the object under study. Relying on overall structure educational research described by A.V. Leontovich, as well as on the model construction scheme proposed by A.L. Korolev, we can describe the generalized structure of educational research implemented using computer simulation methods.
The implementation of educational research using computer modeling methods begins with the definition of the problem (topic) of the study. Based on the analysis of the problem, a description of the object of study is carried out, the goal, hypothesis and tasks are formulated.
The purpose of educational research conducted using computer modeling methods can be defined as the study of the object of study in the aspect of its understanding (to understand how a particular object or process works, what are its structure, basic properties, laws of development and interaction with the outside world), management (to learn manage an object or process, determine the best ways to manage it under given goals and criteria) or forecast (predict the direct and indirect consequences of an impact on an object or process in given ways).
A hypothesis is formulated as an assumption about the object of study, the verification of which can be carried out in the course of an experiment with a computer model.
The tasks of educational research using computer modeling methods will include:
1) the formation of theoretical ideas about the object of study (the structure and properties of the object), the definition of essential properties for studying the object according to the goals of modeling;
2) determination of the list of parameters that allow describing the model in the formal language of mathematics (the list of quantities on which the behavior or structure of the modeled object depends and the parameters that must be obtained as a result of modeling in accordance with the goals set);
3) selection of computer modeling tools (programming systems, spreadsheet processors, computer mathematics packages, special packages for modeling processes of various types) according to the method of solving a mathematical model (numerical, statistical or simulation modeling);
4) building a model and conducting an experiment to test or refute the hypothesis.
In the course of the experiment, the adequacy of the model to a real object is checked, experimental data are collected and analyzed, the properties of the object are studied, its optimal parameters and operating modes are found, and the model is refined if necessary. Based on the results of the experiment, conclusions are formulated about the validity of the hypothesis put forward, the conditions and limits of applicability of the results obtained.
To illustrate the structure of educational research described above, implemented using computer simulation methods, we will give examples of setting up educational research implemented under our guidance by students from the Faculty of Mathematics, Informatics and Physics of the Volgograd State Socio-Pedagogical University.
1. Topic: "The movement of a body thrown at an angle to the horizon." Problem situation: it is known that without taking into account the resistance environment a body thrown at an angle to the horizon moves along a parabola trajectory. Obviously, in the presence of resistance, the flight range of the body will change. But will the character change? trajectories body movements?
The object of study is the trajectory of a material body thrown at an angle to the horizon. The purpose of the study: to reveal the nature of the influence of the resistance of the environment on the trajectory of the movement of a material body. As a research hypothesis, an assumption can be put forward that the trajectory of movement depends on the resistance of the medium.
Research tasks: revealing the parameters that determine the trajectory of the movement of a material body; building a mathematical model; implementation of numerical simulation by compiling a program for the Turbo Delphi programming system; visualization of simulation results (construction of a motion trajectory in a rectangular coordinate system); carrying out a numerical experiment for a number of values of the drag coefficients; analysis of the obtained results and formulation of conclusions.
As a result of the study, it was revealed that the range and trajectory of a body thrown at an angle to the horizon depend on its mass, initial speed, throwing angle, and environmental resistance. A change in the values of the medium resistance coefficients affects the type of the trajectory of motion: without taking into account the resistance of the medium, the trajectory is described by a parabola, and taking into account the resistance of the medium, it is a curve that differs from a parabola. These results allowed us to conclude that the hypothesis put forward is legitimate, not only the flight range of the body, but also the trajectory of its movement depends on the resistance of the medium.
2. Topic: "Dynamics of population development". Problem: some ecological system there are populations of two species of individuals that consume a common resource and are in competition for its use. Is sustainable coexistence of populations possible, or will one of the populations necessarily crowd out the other?
The dynamics of population development is considered as an object of study. The purpose of the study: based on the logistic model of interspecific competition, to study the effect of interspecific competition on the development of populations. Hypothesis - the coexistence of two populations is possible if interspecific competition of populations is weaker than intraspecific competition.
In the course of the study, the following tasks are solved: implementation of a logistic model of interspecific competition of two populations with continuous reproduction using the universal modeling system MVS (Model Vision Studium); providing visualization of simulation results (in the form of graphs of the desired functions); conducting an experiment to determine possible options for the development of two competing populations.
As a result of the experiments, it was found that if interspecific competition is weaker than intraspecific, then the coexistence of two populations is possible; complete displacement of one of them occurs if the influence of one of the populations is stronger than the competition within the other population. The results obtained allowed us to conclude that the proposed hypothesis was confirmed.
Thus, the methodology of conducting research using computer modeling methods allows a new approach to the organization and conduct of educational research, to describe the project-research method of teaching at the level pedagogical technology. Building computer models and conducting computational experiments enable students to act as a researcher, gaining experience in analyzing problems, setting research goals, formulating hypotheses and tasks. Research itself appears as a process of confirming or refuting a hypothesis with the help of sound methods used in "big" science. This nature of the educational activity of students contributes not only to the development of new knowledge and skills in the field of computer science and other disciplines, but also to the acquisition of experience in planning and implementing their own research, substantiating the results obtained during the study.
Reviewers:
Germashev I.V., Doctor of Technical Sciences, Professor of the Department of Informatics and Informatization of Education, Volgograd State Socio-Pedagogical University, Volgograd;
Sergeev A.N., Doctor of Pediatric Sciences, Professor of the Department of Informatics and Informatization of Education, Volgograd State Social and Pedagogical University, Volgograd.
Bibliographic link
Markovich O.S. COMPUTER SIMULATION IN EDUCATIONAL RESEARCH: DEVELOPMENT OF NEW LEARNING METHODS USING INFORMATION TECHNOLOGIES // Contemporary Issues science and education. - 2015. - No. 5.;URL: http://science-education.ru/ru/article/view?id=21724 (date of access: 01.02.2020). We bring to your attention the journals published by the publishing house "Academy of Natural History"
Practical classes are one of the most important components of biomedical education. Experiments in vivo and in vitro are widely used to help students acquire practical experimental skills, but no less important task is to consolidate and comprehend the factual material obtained in lectures, seminars, and from textbooks. Although the use of laboratory animals for this purpose has become a tradition, this approach has its drawbacks. Let's try to list some of them:
Setting up an experiment is quite complicated and sometimes requires a significant investment of time.
It follows from the previous paragraph that only a limited number of drugs can be tested for a given period of time.
The experiment may be resource intensive and economic considerations may prevail in the design of the study.
Animal experiment is always associated with moral and ethical restrictions, the topic of which is also discussed in this essay.
Computer modeling applied in medical education can be divided into the following categories:
- computer text simulators create a verbal description of a situation in which the user selects one of several predefined responses. Based on the response received, the computer generates the following situation. Being based only on textual information, such simulators are relatively easy to program and require little computer resources. However, nowadays these criteria are becoming less relevant and today text simulators are used relatively rarely.
- computer graphics simulators recreate a graphic representation of the situation on the display, often to explain the pharmacokinetic and pharmacodynamic processes associated with taking the drug. Usually only the “mouse” is used as an interface device. Although such simulations contribute to the understanding and assimilation of the material, they usually do not develop practical skills in students. The main purpose of using them is to explain some abstract concepts in an accessible and inexpensive way. Such simulators are particularly suitable for simulating physiological and pharmacological processes.
Sniffy-TheVirtualRat
As one example of modeling a laboratory animal, one can cite the well-known program Sniffy - The Virtual Rat, which allows you to simulate the behavior of a real rat, but without all the disadvantages of using a real animal. The program allows students to reproduce classical experiments on the study of the physiology of learning (the development of conditioned reflexes, etc.). It is possible to implement your own experimental plan, use various stimulating factors, etc. We can note the well-thought-out user interface and superbly executed computer graphics, which very closely simulate the movements of a real rat.
Lab Rat Simulation in Action - Sniffy The Virtual Rat
Rat cvs (Cardiovascular System)
The Rat CVS program simulates an experiment on the effects of various drugs on the rat cardiovascular system. The program allows you to register changes in systemic arterial pressure, pressure created in the left ventricle, venous pressure, strength and frequency of heart contraction. Simulation of a spinal rat is also possible. It is possible for the experimenter to inject various drugs in the required doses (digoxin, atenolol, isoprenaline, losartan, etc.), stimulate nervous system(vagus nerve, etc.). All this is accompanied by real-time visualization of changes in the parameters of the cardiovascular system.
The program can be used both for teaching students and for control - you can “inject” unknown drugs into a rat in order to determine them by the student. Rat CVS is developed by John Dempster, University of Strathclyde.
Rat CVS - injection of adrenaline at a dose of 10 mcg / kg