Expert and learning systems. Expert systems in training Database management systems and expert systems

  • 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 research 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.

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Conclusion of the dissertation on the topic “Theory and methodology of training and education (by areas and levels of education)”, Gryzlov, Sergey Viktorovich

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, 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-training 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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Expert systems in education. Four development problems

And it’s not the uniform that’s valued in potatoes,

and the internal content

Expert systems (ES) are based on the use of elements of artificial intelligence and are used in automated educational systems to improve the quality of teaching by automating the learning process and increasing efficiency by freeing the teacher from routine work.

The main disadvantage of existing electronic educational tools is the use of undeveloped primitive forms of interactive communication with the user. The transition from a primitive dialogue, such as a “menu”, to a dialogue in “natural” language, to a dialogue “from voice” requires the use of expert systems.

Today there is no clear definition of the term “expert system”. The most general definition: an ES is an artificial system that can effectively replace a human expert in a given subject area. Automated information systems that are focused on solving problems in a specific subject area with sufficient quality can be called expert.

ES are intended to make available the combinations of knowledge, experience, skills and intuition of qualified specialists. ES in combination with a complex of educational information, in contrast to existing automated training courses, are a fundamentally new direction for increasing the didactic effectiveness of software and methodological complexes that implement control and management of the learning process. This difference lies in the possibility of intellectual support for students of different levels of preparedness. This possibility is due to the presence of a knowledge base.

Types of tasks where it is advisable to use ES:

management of the learning process, taking into account the individual preparedness of the student, his individual characteristics;

diagnostics and prediction of the quality of assimilation of subject information and the formation of changes in the sequence of presentation of educational material;

maintaining the student’s professional level in a given subject area;

Abstract on the topic:

"Creating a report as a database object. Expert and learning systems"


Contents

Creating a report as a database object

Report structure in Design mode

Methods for creating a report

Create a report


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/Note command from the View menu. Microsoft Access simultaneously adds and removes report title and comment areas.

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

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.

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.


(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 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 an expert system operating in real time 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 yavl. 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.

Expert system for training is a software system that implements the learning function based on expert knowledge.

EOS capabilities:
  • Network presentation of training courses

  • Learner models

  • Generation of security questions and data for analysis of answers to them

  • Possibility of increasing knowledge bases, skills and abilities


Expert system tasks:
  • provide the student with clear criteria for achieving educational goals (control system),

  • help him build an optimal individual training schedule.

  • save the results of previous consultations.


  • Expert system for solving problems in the subject area being studied

  • Expert system for diagnosing student errors

  • Expert system for planning the exercise management process


1. Teaching

1. Teaching . Creating an environment for knowledge acquisition.

2. Education. Performing the functions of a teacher in presenting the material, monitoring its assimilation and diagnosing errors

3. Monitoring and diagnostics . Providing test questions, evaluating answers and identifying errors.

4. Training . Creating an environment that allows you to acquire and consolidate the required skills and abilities.



Expert Shell

Expert Shell designed to organize training in the “computer-student” mode. Training as part of the Chopin information and educational environment takes place according to an individual curriculum and at an individual pace. The expert shell in the environment plays the role of an adviser who, based on the student’s real achievements recorded in the database of testing and training results, builds a training plan and makes decisions about the student achieving a certain level of knowledge about the subject area. VIPES – hybrid shell


VIPES is designed to work online. This shell is multi-user. This system uses a graphical user interface. Subject specialists and teachers are able to independently create and edit knowledge bases for the VIPES shell.

  • Test Shell

  • Data Analysis Console

  • Multi-user ES shell with a visual interface

  • Training and testing database

  • File system for test and training course data

  • Learning Shell

  • Service module



Testing of initial data

Testing of initial data includes verification of factual information that serves as the basis for the examination.

Logical testing of the knowledge base consists in detecting logical errors in the production system that do not depend on the subject area; missing and overlapping rules; inconsistent and terminal clauses (inconsistent conditions).

Concept testing is carried out to check the general structure of the system and take into account all aspects of the problem being solved.


1. Simplicity of solving the initial problem of building a system.

2. Possibility of adding to the testing system during use.

3. A fairly simple scheme for practical use.

4. Attractiveness for the user due to the time and effort spent on testing knowledge.


offering several answer options indirectly encourages the user to analyze various solutions and explore the task in more depth.

Reviewing expert system.

One of the ways to solve the problem of intensifying the educational process is to use the latest information technologies in the training and internship of young specialists.

To solve this problem, a project has been developed to create a reviewing expert system that performs the functions of an expert - consultant and teacher at the same time.




An expert system is a program that is designed to simulate human intelligence, experience, and the process of cognition.

With an expert system based on a peer-review approach, the user provides more data as well as his or her own solution or course of action.

The system evaluates the user's plan and provides critical analysis.

The critique includes alternatives, explanations, justifications, warnings, and additional information to consider.


The reviewing expert system implements two types of abilities:
  • The system can function like a conventional expert system

  • The system can analyze any of the possible plans proposed by the user in the context of a scenario of possible actions, and produce a practical critical analysis.



1. The user enters information regarding the current action and submits his operating plan or set of actions.

2. the entered data is analyzed

3. the user gets the required result.

4. If the user has set the action plan as unknown, the reviewing expert system will function as a regular expert system and will produce the plan recommended by the expert.


All expert systems perform different functions, but they pursue one single goal - to compare a given task with the available information in the database and perform the function that the given expert system performs.

  • What is an expert-learning system?

  • What are the 3 aspects of expert system testing?