- Specialty of the Higher Attestation Commission of the Russian Federation13.00.02
- Number of pages 192
INTRODUCTION
CHAPTER 1. COMPUTER TRAINING SYSTEMS IN
PROCESS OF EDUCATION
1.1. Brief overview of the implementation of computer teaching technologies.
1.2. Expert systems: their fundamental properties and applications.
1.3. Application of expert systems in the learning process. Expert learning systems.
1.4. Conducting and analyzing the main results of the ascertaining experiment.
1.5. Prospects for the use of expert systems in the educational process.
CONCLUSIONS ON THE FIRST CHAPTER
CHAPTER 2. THEORETICAL ISSUES OF CONSTRUCTION
EXPERT TRAINING SYSTEMS
2.1. EOS architecture.
2.2. Representation of knowledge in EOS.
2.3. Learner model.
2.4. Classification of EOS. 89 CONCLUSIONS ON CHAPTER TWO
CHAPTER 3. TRAINING SYSTEM BUILT BY SOFTWARE
THE PRINCIPLE OF OPERATION OF EXPERT TRAINING SYSTEMS ORIENTED AT SOLVING PROBLEMS ABOUT THE MOTION OF A BODY ON AN INCLINE
NOAH PLANE
3.1. Software tools that teach solving physical problems.
3.2. Construction and operation of a training system built on the principle of operation of expert-training systems, focused on solving problems about the movement of a body on an inclined plane.
3.3. Problems solved using the developed expert-training system.
CONCLUSIONS ON CHAPTER THREE
CHAPTER 4. EXPERIMENTAL CHECKING THE METHODS OF TEACHING STUDENTS USING DEVELOPED SOFTWARE TOOLS
4.1. Conducting and analyzing the main results of the search experiment.
4.2. Conducting and analyzing the main results of a teaching and control pedagogical experiment.
CONCLUSIONS ON CHAPTER FOUR
Recommended list of dissertations
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Introduction of the dissertation (part of the abstract) on the topic “Computer training systems built on the principle of operation of expert-training systems: Development and application in teaching solving physical problems. tasks"
Traditionally, the learning process in general and the process of teaching physics in particular are considered as two-way, including the activities of the teacher and students. The active use of computers in the educational process makes it a full third partner in the learning process. Computers provide virtually unlimited opportunities for the development of independent creative thinking of students, their intelligence, as well as independent creative activity of students and teachers.
Active work to find new forms and methods of teaching began in the 60s. Under the leadership of Academician A.I. Berg organized and carried out work on the problems of programmed training, the introduction of technical teaching aids and teaching machines. Programmed training was the first step towards enhancing learning activities. In-depth research on the theory and practice of programmed learning was carried out by V.P. Bespalko, G.A. Bordovsky, B.S. Gershunsky, V.A. Izvozchikov, E.I. Mashbits, D.I. Penner, A.I. Raev, V.G. Razumovsky, N.F. Talyzina and others.
The issues of effective use of computers in the educational process and research on the development of effective methods and means of computer training remain relevant today. Relevant work in this area is being carried out in our country and abroad. However, a unified view on the use of computer technology in the field of education has not yet been formed.
The initial period of using computers in the learning process is characterized as a period of intensive development of the ideas of programmed training and the development of automated teaching systems. Developers of automated training systems proceeded from the assumption that the learning process can be carried out through a well-organized sequence of frames of training and control information. The first experiments on the use of computers in the educational process were embodied in the form of educational programs with a deterministic learning scenario. This class of educational programs has the following disadvantages: low level of adaptation to the individual characteristics of the student; reducing the task of diagnosing a student’s knowledge to the task of determining whether his answers belong to one of the classes of standard answers; large labor costs for preparing educational material.
An alternative approach to the process of computerization of learning is the creation of so-called learning environments. The learning environment embraces the concept of learning through discovery. The fundamental difference between this approach and the one discussed above is that in this case the student is treated as some kind of autonomous system capable of having its own goals. This class of educational programs is characterized by the following features: the learning environment provides the student with educational materials and other resources necessary to achieve the educational goal set for him by the teacher or by himself; lack of control of the student’s actions by the system. The main purpose of the learning environment is to create a favorable, “friendly” environment or “world”, through which the student “travels” acquires knowledge.
Research in the field of psychology of thinking, advances in the field of artificial intelligence and programming technologies have expanded the scope of the computer in the educational process and made it possible to test in practice new concepts for the intellectualization of computer learning.
The sharp increase in the volume of information in the educational process places new demands on the cybernetic approach to teaching, and, consequently, on pedagogical software. They should help to effectively solve the main problem - managing the learning process using feedback based on a detailed diagnosis of students’ knowledge, identifying the reasons for their errors, while simultaneously explaining the computer-proposed solution to the learning problem. The noted features are most effectively implemented, first of all, by training systems built on the principle of operation of expert-training systems, which determines the relevance of the theoretical and practical study of this problem.
The introduction of expert systems into the educational process is a natural logical continuation of the computerization of education, its qualitatively new stage, laying the foundations for the informatization of education. This process became possible thanks to in-depth research conducted on the issues of computerization of education by scientists and teachers. Considering that the use of expert systems to solve problems in physics has yielded positive results, research on the development and application of expert systems is relevant not only in scientific but also in pedagogical activities, including teaching physics.
The use of training programs built on the principle of operation of expert-training systems in the learning process will give a new qualitative leap in education. Their introduction into teaching practice will make it possible to: change the style of teaching, turning it from informational and explanatory to cognitive, educational and research; reduce the time required to acquire the necessary knowledge.
The object of the study is the process of teaching physics.
The subject of the study is the process of learning to solve problems in physics using a teaching system built on the principle of operation of expert-learning systems, and the formation of a general way of solving problems in students.
The purpose of the work was to develop and create a teaching system built on the principle of operation of expert learning systems, focused on solving physical problems of a certain class, and to study the possibility of developing a general solution method for students when learning to solve problems in physics using data from specially developed pedagogical software tools .
The research hypothesis is as follows: the introduction into the learning process of teaching systems built on the principle of operation of expert teaching systems will lead to more effective learning by students of the general method of solving problems in physics, which will improve their academic performance, deepen their knowledge of physics and will contribute to improving quality of knowledge in the subject being studied.
Based on the formulated hypothesis, to achieve the goal of the study, the following tasks were set and solved:
Analysis of modern methods and means of developing educational programs. Focusing on those that correspond to the goals of the work;
Research into the possibilities of using a computer to implement the development of a common way of solving problems in students;
Development of the structure and principles of constructing a training system, built on the principle of operation of expert-training systems, focused on solving physical problems of a certain class;
Testing the proposed research hypothesis, assessing the effectiveness of the developed methodology, developed pedagogical software during the pedagogical experiment.
To solve the problems, the following research methods were used:
Theoretical analysis of the problem based on the study of pedagogical, methodological and psychological literature;
Questionnaires and surveys of pupils, students, teachers of schools and universities;
Studying the process of learning to solve problems and the developed methodology during visiting and conducting physics classes, observing students, talking with teachers, conducting and analyzing tests, testing students;
Planning, preparing, conducting a pedagogical experiment and analyzing its results.
The scientific novelty of the research consists of:
Development of a training system built on the principle of operation of expert-training systems, focused on solving a certain class of problems in physics;
Theoretical and practical substantiation of the possibility of developing in students a general way of solving problems when using developed pedagogical software tools (a teaching system built on the principle of operation of expert-learning systems) in the learning process;
Development of the fundamentals of a methodology for using a training system, built on the principle of operation of expert-training systems, when teaching the solution of physical problems.
The theoretical significance of the study lies in the development of an approach to teaching solving problems in physics, which consists in implementing control of students’ activities when solving problems using specially developed pedagogical software (a teaching system built on the principle of operation of expert learning systems).
The practical significance of the research lies in the creation of software and methodological support for physics classes (a teaching system built on the principle of operation of expert teaching systems), determining its role and place in the educational process and developing the fundamentals of a methodology for using these pedagogical software tools when conducting classes on solving physics tasks using a computer.
The following is submitted for defense:
Justification of the possibility of using the developed training system, built on the principle of operation of expert-training systems, in the process of learning to solve problems in physics;
Development of an approach to managing students’ activities through specially developed pedagogical software (a teaching system built on the principle of expert learning systems) when teaching solving problems in physics;
Fundamentals of the methodology for using a teaching system, built on the principle of operation of expert-learning systems, when conducting classes on solving problems in the process of teaching physics.
Testing and implementation of research results. The main results of the study were reported, discussed and approved at meetings of the Department of Methods of Teaching Physics at Moscow State University (1994-1997), at a conference of young scientists (Mordovia State University, 1996-1997), at conferences at Moscow State University (April, 1996).
The main provisions of the dissertation are reflected in the following publications:
1. Gryzlov S.V. Expert learning systems (literature review) // Teaching physics in higher education. M., 1996. No. 4. - P. 3-12.
2. Gryzlov S.V. Application of expert-learning systems in the process of teaching physics // Teaching physics in higher education. M., 1996. No. 5.-S. 21-23.
3. Gryzlov S.V., Korolev A.P., Soloviev D.Yu. Expert-training system focused on solving a set of problems about the movement of a body on an inclined plane // Improving the educational process based on new information technologies. Saransk: Mordovian State. ped. Institute, 1996. - pp. 45-47.
4. Gryzlov S.V., Kamenetsky S.E. Promising directions for the use of computer technology in the educational process of universities and schools // Science and school. 1997. No. 2.-S. 35-36.
Structure and scope of the dissertation. The dissertation consists of an introduction, four chapters, a conclusion, a list of references and an appendix. The total volume is 192 pages of typewritten text, including 25 figures, 8 tables. The list of references includes 125 titles.
Similar dissertations in the specialty “Theory and Methods of Teaching and Education (by areas and levels of education)”, 13.00.02 code HAC
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CONCLUSIONS ON CHAPTER FOUR
1. Based on the analysis of possible directions for using a computer in teaching, the shortcomings of existing pedagogical software tools have been identified, the need for the creation and use in the educational process of software training tools built on the principle of operation of expert-learning systems has been substantiated.
2. A methodology has been developed for conducting classes using developed software (a training system built on the principle of operation of expert-training systems).
3. During the search experiment, the content was determined and the structure of the developed pedagogical software tools was adjusted.
4. Conducting a search experiment made it possible to develop the final version of the methodology for conducting classes using the developed teaching system, aimed at developing in students a general way of solving problems.
5. The conducted comparative analysis of the results of the control pedagogical experiment indicates the significant influence of our proposed methodology for conducting classes on solving physical problems using developed pedagogical software on the formation of a general method of solving problems in students.
Thus, the validity of the hypothesis put forward about the greater effectiveness of our proposed methodology for conducting classes on solving physical problems using developed pedagogical software tools has been proven in comparison with the traditional one.
CONCLUSION
1. Pedagogical, methodological and psychological literature and dissertation research on methods of using a computer in the learning process have been studied and analyzed. On this basis, it has been revealed that the most effective pedagogical software tools are educational programs built on the principle of operation of expert learning systems.
2. Expert learning systems focused on developing a common method of solving in students are the most effective means of teaching problem solving.
3. The prospects for using expert-learning systems in the educational process are determined, and directions for using expert systems in the learning process are proposed.
4. The structure of the training system, built on the principle of operation of expert-learning systems, focused on developing a common way of solving problems in students, is proposed and justified.
5. A training system has been developed, built on the principle of operation of expert-training systems, focused on solving a set of problems about the movement of a body on an inclined plane. Control of students' activities in the course of solving a problem with the help of a developed teaching system is implemented through: a) computer modeling, which makes it possible to identify the essential properties and relationships of the objects discussed in the problem; b) heuristic tools that provide students with the opportunity to plan their actions; c) step-by-step control of the student’s actions by the learning system and presentation, at the student’s request, of a reference solution to the problem, developing the ability to evaluate one’s actions, and select criteria for this evaluation.
6. The methodology for conducting classes on solving problems using developed pedagogical software tools, their role and place in the educational process have been determined. The main provisions of this methodology are as follows: a) students’ independent choice of tasks to master the general method of solving problems of a certain class; b) the use of developed pedagogical software (a training system built on the principle of operation of expert-training systems) to form a general way of solving problems; c) a combination of independent problem solving by each student with a collective discussion of the solution plan; d) identifying an algorithm for solving problems of this class based on a generalization of already solved problems.
7. The results of the conducted pedagogical experiment showed that the formation of a general way of solving problems among students in experimental groups, where training was carried out using developed pedagogical software (a teaching system built on the principle of operation of expert-learning systems), is significantly higher than in control groups , where training was carried out using the most common types of computer programs (simulating and training), which confirms the reliability of the hypothesis put forward.
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Abstract on the topic:
Contents
Creating a report as a database object
Methods for creating a report
Create a report
Expert and learning systems
Creating a report as a database object
A report is a formatted representation of data that is displayed on screen, printed, or in a file. They allow you to extract the necessary information from the database and present it in a form that is easy to understand, and also provide ample opportunities for summarizing and analyzing data.
When printing tables and queries, information is displayed practically in the form in which it is stored. There is often a need to present data in the form of reports that have a traditional look and are easy to read. A detailed report includes all the information from a table or query, but contains headers and is broken into pages with headers and footers.
Report structure in Design mode
Microsoft Access displays data from a query or table in a report, adding text elements to make it easier to read.
These elements include:
Title. This section is printed only at the top of the first page of the report. Used to output data, such as report title text, a date, or a statement of document text, that should be printed once at the beginning of the report. To add or remove a report title area, select the Report Title/Note command from the View menu.
Page header. Used to display data such as column headings, dates, or page numbers printed at the top of each report page. To add or remove a header, select Header and Footer from the View menu. Microsoft Access adds a header and footer at the same time. To hide one of the headers and footers, you need to set its Height property to 0.
The data area located between the header and footer of a page. Contains the main text of the report. This section displays the data printed for each of the records in the table or query on which the report is based. To place controls in the data area, use a list of fields and a toolbar. To hide the data area, you need to set the section's Height property to 0.
Footer. This section appears at the bottom of every page. Used to display data such as totals, dates, or page numbers printed at the bottom of each report page.
Note. Used to output data, such as conclusion text, grand totals, or a caption, that should be printed once at the end of the report. Although the report Note section is at the bottom of the report in Design view, it is printed above the page footer on the last page of the report. To add or remove a report notes area, select the Report Title/Report Notes command from the View menu. Microsoft Access simultaneously adds and removes the title and comment areas of a report.
Methods for creating a report
You can create reports in Microsoft Access in a variety of ways:
Constructor
Report Wizard
Auto report: to column
Auto report: tape
Chart Wizard
Postal labels
The wizard allows you to create reports by grouping records and is the simplest way to create reports. It puts the selected fields into the report and offers six report styles. After completing the Wizard, the resulting report can be modified in Design mode. Using the Auto Report feature, you can quickly create reports and then make some changes to them.
To create an Auto Report, you must perform the following steps:
In the database window, click the Reports tab and then click the Create button. The New Report dialog box appears.
Select the Autoreport: column or Autoreport: strip item in the list.
In the data source field, click the arrow and select Table or Query as the data source.
Click on the OK button.
The Auto Report Wizard creates an auto report in a column or strip (user's choice) and opens it in Preview mode, which allows you to see what the report will look like when printed.
Changing the report display scale
To change the display scale, use the pointer - a magnifying glass. To see the entire page, you must click anywhere on the report. The report page will be displayed on a reduced scale.
Click on the report again to return to a larger view. In the enlarged report view, the point you clicked on will be in the center of the screen. To scroll through report pages, use the navigation buttons at the bottom of the window.
Print a report
To print a report, do the following:
On the File menu, click on the Print command.
In the Print area, click the Pages option.
To print only the first page of the report, enter 1 in the From field and 1 in the To field.
Click on the OK button.
Before printing a report, it is advisable to view it in Preview mode, to access which you need to select Preview from the View menu.
If you print with a blank page at the end of your report, make sure that the Height setting for report notes is set to 0. If you print with blank pages in between, make sure that the sum of the form or report width and the left and right margin widths does not exceed the width of the sheet of paper specified in the Page Setup dialog box (File menu).
When designing report layouts, use the following formula: report width + left margin + right margin<= ширина бумаги.
In order to adjust the size of the report, you must use the following techniques:
change the report width value;
Reduce margin width or change page orientation.
Create a report
1. Launch Microsoft Access. Open the database (for example, the educational database "Dean's Office").
2. Create an AutoReport: Tape, using a table as a data source (for example, Students). The report opens in Preview mode, which allows you to see what the report will look like when printed.
3. Switch to Design mode and edit and format the report. To switch from Preview mode to Design mode, you must click Close on the Access application window toolbar. The report will appear on the screen in Design mode.
Editing:
1) remove the student code fields in the header and data area;
2) move all fields in the header and data area to the left.
3) Change the text in the page title
In the Report Title section, select Students.
Place the mouse pointer to the right of the word Students so that the pointer changes to a vertical bar (the input cursor) and click at that position.
Enter NTU "KhPI" and press Enter.
4) Move the Caption. In the Footer, select the =Now() field and drag it to the Report Header under the name Students. The date will appear below the title.
5) On the Report Designer toolbar, click the Preview button to preview the report.
Formatting:
1) Select the heading Students of NTU "KhPI"
2) Change the typeface, font style and color, as well as the background fill color.
3) On the Report Designer toolbar, click the Preview button to preview the report.
Style change:
To change the style, do the following:
On the Report Designer toolbar, click the AutoFormat button to open the AutoFormat dialog box.
In the Report - AutoFormat Object Styles list, click Strict and then click OK. The report will be formatted in the Strict style.
Switches to Preview mode. The report will be displayed in the style you selected. From now on, all reports created using the AutoReport function will have the Strict style until you specify a different style in the AutoFormat window.
Expert and learning systems
Expert systems are one of the main applications of artificial intelligence. Artificial intelligence is one of the branches of computer science that deals with the problems of hardware and software modeling of those types of human activities that are considered intellectual.
The results of research on artificial intelligence are used in intelligent systems that are capable of solving creative problems belonging to a specific subject area, knowledge about which is stored in the memory (knowledge base) of the system. Artificial intelligence systems are focused on solving a large class of problems, which include the so-called partially structured or unstructured tasks (weakly formalizable or unformalizable tasks).
Information systems used to solve semi-structured problems are divided into two types:
Creating management reports (performing data processing: searching, sorting, filtering). Decisions are made based on the information contained in these reports.
Expert systems are one of the main applications of artificial intelligence. Artificial intelligence is one of the branches of computer science that deals with the problems of hardware and software modeling of those types of human activities that are considered intellectual.
The results of research on artificial intelligence are used in intelligent systems that are capable of solving creative problems belonging to a specific subject area, knowledge about which is stored in the memory (knowledge base) of the system. Artificial intelligence systems are focused on solving a large class of problems, which include the so-called partially structured or unstructured tasks (weakly formalizable or unformalizable tasks).
Information systems used to solve semi-structured problems are divided into two types:
Creating management reports (performing data processing: searching, sorting, filtering). Decisions are made based on the information contained in these reports.
Developing possible solution alternatives. Decision making comes down to choosing one of the proposed alternatives.
Information systems that develop solution alternatives can be model or expert:
Model information systems provide the user with models (mathematical, statistical, financial, etc.) that help ensure the development and evaluation of solution alternatives.
Expert information systems provide the development and assessment of possible alternatives by the user through the creation of systems based on knowledge obtained from specialist experts.
Expert systems are computer programs that accumulate the knowledge of specialists - experts in specific subject areas, which are designed to obtain acceptable solutions in the process of information processing. Expert systems transform the experience of experts in any particular field of knowledge into the form of heuristic rules and are intended for consultation of less qualified specialists.
It is known that knowledge exists in two forms: collective experience and personal experience. If a subject area is represented by collective experience (for example, higher mathematics), then this subject area does not need expert systems. If in a subject area most of the knowledge is the personal experience of high-level specialists and this knowledge is weakly structured, then such an area needs expert systems. Modern expert systems have found wide application in all spheres of the economy.
The knowledge base is the core of the expert system. The transition from data to knowledge is a consequence of the development of information systems. Databases are used to store data, and knowledge bases are used to store knowledge. Databases, as a rule, store large amounts of data with a relatively low cost, while knowledge bases store small but expensive information sets.
A knowledge base is a body of knowledge described using the selected form of its presentation. Filling the knowledge base is one of the most difficult tasks, which is associated with the selection of knowledge, its formalization and interpretation.
The expert system consists of:
knowledge base (as part of working memory and a rule base), designed for storing initial and intermediate facts in working memory (also called a database) and storing models and rules for manipulating models in the rule base
problem solver (interpreter), which provides the implementation of a sequence of rules for solving a specific problem based on facts and rules stored in databases and knowledge bases
explanation subsystem allows the user to get answers to the question: “Why did the system make this decision?”
a knowledge acquisition subsystem designed to both add new rules to the knowledge base and modify existing rules.
user interface, a set of programs that implement the user’s dialogue with the system at the stage of entering information and obtaining results.
Expert systems differ from traditional data processing systems in that they typically use symbolic representation, symbolic inference, and heuristic search for solutions. For solving weakly formalizable or non-formalizable problems, neural networks or neurocomputers are more promising.
The basis of neurocomputers is made up of neural networks - hierarchical organized parallel connections of adaptive elements - neurons, which ensure interaction with objects of the real world in the same way as the biological nervous system.
Great successes in the use of neural networks have been achieved in the creation of self-learning expert systems. The network is configured, i.e. train by passing all known solutions through it and achieving the required answers at the output. The setup consists of selecting the parameters of the neurons. Often they use a specialized training program that trains the network. After training, the system is ready for operation.
If in an expert system its creators pre-load knowledge in a certain form, then in neural networks it is unknown even to the developers how knowledge is formed in its structure in the process of learning and self-learning, i.e. the network is a “black box”.
Neurocomputers, as artificial intelligence systems, are very promising and can be endlessly improved in their development. Currently, artificial intelligence systems in the form of expert systems and neural networks are widely used in solving financial and economic problems.
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Expert training system
Introduction
Currently, due to the rapid development of Internet technologies, more and more new interactive services are appearing for Internet and Intranet -networks, such as distance learning. The distance learning system is a fairly popular form of education in the world in those countries that have a fairly high level of development of computer-based communication tools. The training of modern specialists requires the organization of the educational process using these new information technologies and using knowledge-based systems - expert systems (ES).
The use of ES for assessing the level of knowledge of students in testing systems determines an important block of computer programs - expert training systems (ETS).
Expert learning systems are computer programs that have the main components of an ES, but which have an additionally expanded explanation component. Such systems are based both on the knowledge of software experts and on the knowledge of teaching methodology experts. In addition, they have a component of adapting the presentation of educational material to the student, depending on his preparedness. And at a minimum, there are several learning strategies, the level of detail of which depends on the student’s activity in dialogue with the system.
The use of EOS as a testing tool to determine the quality of knowledge of a student is also of great importance in teaching. Since during such testing the student is not influenced by a subjective factor, that is, the test results do not depend on the personal characteristics of the examiner and the person being tested. And the use of uniform tests allows the teacher to objectively assess the level of preparation of students.
1. Relevance of the topic
In connection with the widespread use of computers, the role of computer training is increasing, the methodology of which increases the intellectual abilities of the student and the independence of decision-making. And such qualities are most in demand in a competitive economy and contribute to educationalprofessional growth. There are problems of creating effective teaching systems, as well as creating new forms and ways of presenting educational material, searching for new pedagogical techniques and means of teaching. One of the directions for increasing the effectiveness of training, assimilation of information and reducing the costs of the learning process itself is the development and use of automated expert training systems. At this time, there are many terms denoting an automated expert training system, which, in fact, are similar.
The most popular of them are distance learning systems, computer training systems and others. To explain the full meaning of the terms listed above, the following definition can be given.
An expert training system (ETS) is a complex of software, hardware, educational and methodological tools built on the basis of the knowledge of subject matter experts (qualified teachers, methodologists, psychologists), implementing and controllinglearning process. The purpose of such a system is that, on the one hand, it helps the teacher to teach and control the student, and on the other hand, the student learns independently.
2. Purpose and objectives of the study, planned results
The purpose of the study is to develop a computer expert teaching system that will help increase the amount of acquired knowledge and the efficiency of information perception, as well as reduce the time spent studying the subject, including the time spent by the teacher on presenting information and instilling practical skills in students.
Main objectives of the study:
- Development of an ontological model of EOS;
- Development of the EOS structure;
- Justification and selection of computer implementation tools;
- Introduction of active components into the EOS (games, interactive systems, direct access to communication, for example, via Skype with the manager);
Object of study: expert training system.
Subject of study: models, structures and functions of EOS.
Scientific novelty consists of a new approach to EOS design based on modeling the learner’s activities and the use of artificial intelligence methods.
As part of the master's thesis, it is planned to obtain relevant scientific results in the following areas:
- Modeling learning processes.
- Designing the EOS structure for Internet and Intranet.
Planned results of the work: a prototype of an expert training system that will improve the quality of training and reduce training time.
3. Review of scientific research.
Since the issues of researching expert teaching systems and increasing the effectiveness of training in this system are an important part of solving complex problems using expert systems. EOS have been widely studied by both foreign and domestic specialists.
3.1. Review of international sources
First training system Plato based on a powerful computer from the company " Control Data Corporation "was developed in the USA in the late 50s and developed over 20 years. The creation and use of training programs have become truly widespread since the early 80s, when personal computers appeared and became widespread. Since then, educational applications of computers have become one of their main applications, along with word processing and graphics, pushing mathematical calculations into the background.
ECSI was also founded in 1972 and has since established itself as a leading service provider to the education industry. The company specializes in developing products and services to enhance the learning experience for students and their parents. ECSI currently serves more than 1,300 schools, colleges and universities across the country, offering a wide range of fully customized, intuitive learning systems.
3.2. Review of national sources
Modern training systems include TrainingWare, eLearning Server 3000 v2.0, eLearningOffice 3000, IBM Workplace Collaborative Learning and HyperMethod 3.5 from HyperMethod, which is the largest Russian developer of ready-made solutions and software in the field of multimedia, expert training and e-commerce.
4. Expert training systems
An expert learning system (ETS) is a computer program built on the basis of the knowledge of subject matter experts (qualified teachers, methodologists, psychologists) that carries out and controls the learning process. The purpose of such a system is that, on the one hand, it helps the teacher to teach and control the student, and on the other hand, the student learns independently.
The main components of the EOS are:
- knowledge base;
- output machine;
- knowledge extraction module;
- training module;
- explanation system;
- testing module.
Picture 1- Functional model of the EOS structure
(animation: 8 frames, 5 repetition cycles, 118 kilobytes)
In this model, the upper part of the EOS is inherited from the ES, and the lower part represents blocks that ensure the process of training and testing.
A knowledge base is a depository of knowledge modules. The knowledge module of expert systems is a formalized, using some method of knowledge representation (production system, frames, semantic networks, 1st order predicate calculus) display of objects of the subject area, their relationships, actions on objects.
Working with the knowledge base involves the following stages:
- extracting knowledge from experts;
- formalization of knowledge;
- access, processing of knowledge modules.
During the learning process, expert knowledge can be transferred to the learner in the form of a piece of information (text, graphic, multimedia), as well as knowledge based on experience, which cannot be transferred directly to the learner, but is acquired by him in the course of independent activity].
To transfer expert knowledge, developed hypertext technology is widely used - from traditional help programs to modern tools for creating and supporting Web sites (for example, Dreamweaver MX).
Unlike ES, to build an EOS knowledge base, not only expert teachers are involved, but also knowledge about pedagogical techniques and teaching strategies and about the psychological characteristics of the individual is used. Therefore, knowledge modules are formed by many experts. And here it is necessary to take into account the consistency of expert opinions and fine-tune the knowledge base, taking into account the competence of experts. Of course, these difficulties can be circumvented if there is an expert who combines the knowledge of a specialist in the subject area, knowledge of teaching tactics and strategies, and masters psychological teaching techniques, that is, a highly qualified teacher.
The training component is a set of software modules that implement various output mechanisms to achieve the pedagogical goal in training. EOS, unlike other computer teaching aids, are interactive: they have a dialogue with the student, which is very attractive for the latter.
The construction of dialogue is based on the basic psychological principles of learning:
- user-friendly interface;
- exit the dialogue at any time;
- timely and motivated assistance.
Each question asked of the student must be carefully thought through, and if necessary, provide a more detailed question in order to better understand it.
As a result of the study It has been shown that many components of creating an EOS depend on the outcome of the training, therefore, to create an EOS knowledge base, you need a specialist who has excellent knowledge of the subject area and is also confident in learning techniques.
5. Client-server technology of expert training system for networks InternetAndIntranet
The client-server architecture consists of the following components:
a server that fulfills client requests; client, which provides a user interface that sends requests to the server and receives responses from it; network communication software that communicates between a client and a server. The use of client-server technology provides certain advantages when building an ES: the knowledge base is stored on the server and, therefore, the need to update it is done once;
the knowledge base can be accessible to other applications; and the advantage for expert learning systems (ETS) is that you can store content on a server and track learning statistics on it.
Client-server ES and EOS for Internet/Intranet networks make it possible to expand the possibilities of their use in distance education.
Computer training systems allow both the development of ES prototypes and can be used for tailored testing and training of students over a local network.
The main components of the EOS are the following: knowledge base editor; logical inference machines (direct, inverse, indirect inference, Bayes formula); explanation subsystem; dough analyzer; teacher module; training component.
The main task of expert learning systems is to provide the student with the opportunity to acquire knowledge, skills, and abilities in developing knowledge bases and creating prototypes of electronic systems independently, as well as for trained testing.
There are at least five important reasons that hinder the implementation of client-server (distributed) ES:
- The structural elements of the ES components are not isolated from each other.
- A database is not a database, for which there are powerful DBMSs (Oracle, InterBase, MySQL, and so on) that use SQL queries.
- Multi-user access to the knowledge base for editing is simply not acceptable.
- The logical conclusion and the specifics of creating a knowledge base (different ways of representing knowledge) do not contribute to the need to combine them into a single system. A number of description languages and Web services have been developed for Symantec Web, but there are still no proposals for implementing logical inference.
- Software tools for constructing ES and knowledge bases are exclusive and expensive.
You can, of course, place the ES on a Web server for downloading to the client machine via the download link and update it on the server, but this is not a client-server solution.
Similarly, one can argue about the use of a three-tier client-server architecture (Server - CORBA - Client), when the knowledge base is located on the application server and is presented in the form of business decision rules.
Also not suitable for the “thin client” technology (KB, logical inference, explanation system are located on the server, and the dialogue with the ES is supported both on the server and on the client) and “thick client” (KB, logical inference, explanation system are located on the client machine, and the dialog interface is supported by the client and server).
Please note that the ES knowledge base is intellectual property and cannot be made available for free use. And educational KBs should be placed on a Web server so that any interested user can analyze how the ES works and improve their knowledge of the subject area.
We should not forget about server loads during peak situations. No provider will give away a server just for the functioning of an ES, since the user’s reaction during consultation or explanation is not predictable. And these are important aspects of the functioning of the ES (consultations can last from minutes to several hours).
Developing an EOS for Internet/Intranet networks is a completely different matter.
EOS is a computer system built on the basis of the knowledge of subject matter experts (qualified teachers, methodologists, psychologists), which carries out and controls the learning process. The purpose of such a system is that, on the one hand, it helps the teacher teach and control students, and on the other hand, students learn independently.
The main components of the EOS are the following: knowledge base; output machine; training module; explanation system; learning testing module.
As a rule, the knowledge base contains:
Psychodiagnostic rules for identifying psychological types of students.
Didactic techniques for teaching. The rules represent the accumulated knowledge of teachers for assessing students' knowledge.
Learning rules change the sequence of presented content tasks. This sequence is a function of many variables: the psychological type of the student, the level of training, the current response of the student, the level of difficulty of the task, the amount of training completed.
In connection with what has been said about distributed ES, it is recommended to use “thick client” technology for training and testing, that is, when all the components of the ES are located on the client machine, and the results of training and testing are transferred to the server. And there is no need to fear that the results can be replaced, given the modern encryption capabilities of the protocol with a remote server. Why this particular technology? It is known that about 80% of all information perceived by a person - it's visual. Therefore, multimedia technologies (avi files) are a priority in training. If you place them and run them onserver - this is a huge load on the server and, as a result, traffic increases to enormous sizes.
conclusions
EOS, unlike other computer learning technologies, have the ability to implement the learning process according to an individual student model. Learning with the help of ES is focused on the acquisition of knowledge by the learner himself. Namely, such specialists are in demand in the modern labor market. EOS also has its advantages and disadvantages.
The main disadvantages associated with expert learning systems can be divided into psychological associated with the lack of “live” communication with the teacher, high requirements for self-organization and technical, which are caused by imperfections in content, technology and telecommunications infrastructure.
The advantages of expert training systems are:
- Geographical and temporal advantages.
- Personalization of the learning process. Opportunity to train various categories of people, including those with disabilities.
- Expanding the information being studied and increasing the intensity of learning.
- Optimization and automation of the knowledge transfer process.
The master's thesis is devoted to the current scientific problem of automating an expert teaching system. As part of the research, the following was carried out:
- Existing expert training systems are analyzed.
- A study was carried out on an automated expert training system.
- The Client-server technology of an expert training system for Internet and Intranet networks is considered.
In accordance with the statement of the problem, the further direction of research is the selection, development and adaptation of an expert training system, its software implementation and testing.
At the time of writing this abstract, the master's thesis has not yet been completed. Final completion: December 2013. The full text of the work and materials on the topic can be obtained from the author or his supervisor after the specified date.
List of sources
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8. Pusilovsky, P., Adaptive and Intelligent Technologies for Web-based Education. In C. Rollinger and C. Peylo (eds.), Special Issue on Intelligent Systems and Teleteaching, Konstliche Intelligenz, 4, 19 - 25.
9. Burdaev V.P. Client-server technology of an expert training system for Internet and Intranet networks. // Artificial intelligence.
11. Andreychikov A.V. Intelligent information systems. /A. V. Andreichikov, O. N. Andreichikova: Textbook. - M.: Finance and Statistics, 2004. - 424 p.
12. Atanov G. A. Training and artificial intelligence, or the foundations of modern higher school didactics. /G. A. Atanov, I. N. Pustynnikova. - Donetsk: DOU, 2002. - 504 p.
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(in medicine, the computer offers diagnostic options and gives advice) Expert systems- these are programs for computers that accumulate (i.e. collect, accumulate) the knowledge of specialists - experts in specific subject areas, which are designed to obtain acceptable solutions in the process of information processing. Expert systems transform the experience of experts in any specific field of knowledge into the form of heuristic rules and are intended for consultation of less qualified specialists.
The principles of operation of a knowledge-based expert system: the user transmits facts or other information to the expert system and receives expert advice or expert knowledge as a result.
The expert system consists of:
Knowledge base (as part of working memory and a rule base), designed for storing initial and intermediate facts in working memory (also called a database) and storing models and rules for manipulating models in the rule base
A problem solver (interpreter) that provides the implementation of a sequence of rules for solving a specific problem based on facts and rules stored in databases and knowledge bases
Explanation subsystems allow the user to get answers to the question: “Why did the system make this decision?”
A knowledge acquisition subsystem designed to both add new rules to the knowledge base and modify existing rules.
User interface, a set of programs that implement the user’s dialogue with the system at the stage of entering information and obtaining results.
In general expert systems are classified in three main areas: by type of computer, by connection with real time and by the type of problem being solved.
By computer type ES is classified into: super computer; Medium performance computer; character processors; personal computers.
In connection with real time classified into: Static; Quasi-dynamic;
· Dynamic.
By type of problem being solved classified into: Data interpretation; Diagnostics; Monitoring; Design; Forecasting; Planning; Control; Decision support; Education.
The expert’s knowledge relates to only one subject area, and this is the difference between methods based on the use of expert systems and general methods for solving problems. An expert's knowledge related to solving specific problems is called the expert's area of knowledge.
In the field of knowledge, an expert system conducts reasoning or draws logical conclusions on the same principle as a human expert would reason or arrive at a logical solution to a problem. This means that based on certain facts, a logical, justified conclusion is formed through reasoning, which follows from these facts.
Expert systems have many attractive features:
Increased availability. Any suitable computer hardware may be used to provide access to expert knowledge.
· Reduced costs. The cost of providing expert knowledge per individual user is significantly reduced.
· Reduced danger. Expert systems can be used in such environments that may turn out to be dangerous for humans.
· Constancy. Expertise never goes away. Unlike human experts, who may retire, quit their jobs, or die, the knowledge of an expert system will persist indefinitely.
· Opportunity to gain expertise from many sources. With the help of expert systems, the knowledge of many experts can be collected and brought to work on a task that is performed simultaneously and continuously, at any time of the day or night. The level of expert knowledge combined by combining the knowledge of several experts may exceed the level of knowledge of a single human expert.
· Increased reliability. The use of expert systems can increase the degree of confidence that the right decision has been made by providing another informed opinion to a human expert or mediator when resolving discordant opinions between several human experts. (Of course, this method of resolving discordant opinions cannot be used if the expert system is programmed by one of the experts involved in the clash of opinions.) The decision of the expert system must always agree with the decision of the expert; a mismatch can only be caused by an error made by the expert, which can only happen if the human expert is tired or stressed.
· Explanation. An expert system is able to explain in detail its reasoning that led to a certain conclusion. And the person may be too tired, not inclined to explain, or unable to do it all the time. The opportunity to receive an explanation increases confidence that the right decision was made.
· Fast response. Some applications may require fast or real-time response. Depending on the hardware and software used, an expert system can respond faster and be more ready to work than a human expert. Some extreme situations may require faster reactions than humans; in this case, the use of a real-time expert system becomes an acceptable option.
· Consistently correct, emotionless and complete answer under any circumstances. This property can be very important in real time and in extreme situations where a human expert may be unable to perform at maximum efficiency due to stress or fatigue.
· Possibility of use as an intelligent training program. An expert system can act as an intelligent teaching program, giving the student examples of programs to run and explaining what the system's reasoning is based on.
· Can be used as an intelligent database. Expert systems can be used to access databases using an intelligent access method.
25.Advantages of using ICT in education
Information phenomenon the most important mechanism of reform is formation. Systems, e.g. to higher quality, access. and effect. education.
Comp. technology is just hardware. Today we have another task - poppy. Effect. Use her, direction to decide strategically modernization goals Education – higher. its quality.
Advantages:
1. Information technology Means. expand the possibilities of presenting educational information. The use of color, graphics, sound, all modern. video equipment allows you to recreate the real situation of an activity..
2. The computer allows noun. increase motivation to learn.
3. ICTs involve students in learning. process, contributing to the widest disclosure of their abilities, the activation of mental activity.
4. Use ICT in the educational process increased. Possible setting educational tasks and managing the process of solving them. Computers make it possible to build and analyze models of various objects, situations, and phenomena.
5. ICTs make it possible to qualitatively change the control of activities. Study while providing flexibility in managing the learning process.
6. The computer contributes to the formation. students' reflection. The training program allows students to visually present the result of their actions, the specific stage in solving the problem, the cat. made a mistake and correct it.