LEARNING TASKS IN ARTIFICIAL INTELLIGENCE EDUCATION

2020 ◽  
Vol 11 (1) ◽  
pp. 233-240
Author(s):  
Veneta Tabakova-Komsalova ◽  
◽  
Todorka Glushkova ◽  
Maria Grancharova-Hristova ◽  
Irina Krasteva ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Ministry Of Education ◽  
Teaching Aids ◽  
Learning Tasks ◽  
Innovative Schools ◽  
Effectiveness Of Training ◽  
Intelligence Education ◽  
Logical Rules ◽  
Different Levels

Modern trends in the development of digital technologies are directly related to Artificial Intelligence and its application in all spheres of life. This determines the need to study this discipline not only in universities but also in schools. In the last few years, various schools in Bulgaria have introduced the study of elements of Artificial Intelligence as an innovation in specialized, professional and innovative schools, as well as in clubs of interest. The Ministry of Education and Science has approved a sample curriculum. Textbooks and teaching aids are being created. The report aims to present a classification of learning tasks in artificial intelligence training in different levels and forms of training. Some basic key examples will be considered, through which the basic concepts and rules in classical artificial intelligence are introduced, related to both the basic algorithms for solving problems through search and the presentation of knowledge through logical rules. The authors will share their experience in the study of Artificial Intelligence and will present some opportunities to increase the effectiveness of training.

scholarly journals APPLICATION OF COMPUTER-BASED TOOLS FOR MATHEMATICS TEACHING AT VARIOUS TYPES OF LESSONS IN GYMNASIUMS

10.23856/4216 ◽  
2021 ◽  
Vol 42 (5) ◽  
pp. 117-125
Author(s):  
Tetiana Tabler
Keyword(s):  
Learning Tools ◽  
Structural Elements ◽  
Computer Tool ◽  
Computer Tools ◽  
Teaching Aids ◽  
Computer Based ◽  
Computer Teaching ◽  
Different Levels ◽  
Active Interaction

The article analyzes the classification of types of lessons in didactics and, in particular, types of lessons in mathematics. Mathematics lessons are divided into five types: a lesson of presenting new knowledge; a lesson of consolidation of the studied material, in particular, a lesson of formation of skills and abilities; a lesson of repetition, systematization, and generalization of the studied; knowledge testing and assessment lesson and combined lesson. You can get a computer tool for each type of the lesson and, accordingly, for its purpose and its structural elements. Despite of the modern information space is sufficiently filled with a variety of computer tools, it is important for teachers to quickly determine which tool is right for a particular type of lesson. We propose to divide computer learning tools into three levels of interactivity: I level of interactivity – reactive interaction; II level of interactivity – active interaction; III level of interactivity – mutual interaction. The experience of teachers is analyzed and it is established at which structural stages of the lesson teachers use different computer tools, we offer a classification of computer teaching aids depending on the level of interactivity and type of lesson. The positive experience of the interactive catalog of computer tools developed and implemented by us in the lessons of mathematics confirmed our assumption that for each type of lesson a corresponding computer tool of different levels of interactivity is selected.

LEARNING IN SCHOOL OF LOGIC AND LOGICAL PROGRAMMING FOR PRESENTATION AND PROCESSING OF KNOWLEDGE

2020 ◽  
Vol 11 (1) ◽  
pp. 15-22
Author(s):  
Stanimir Stoyanov ◽  
◽  
Todorka Glushkova ◽  
Rumyana Papancheva ◽  
◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Extracurricular Activities ◽  
Main Idea ◽  
High School Education ◽  
Ministry Of Education ◽  
Teaching Resources ◽  
Logical Programming ◽  
General Meaning ◽  
Different Levels

New trends in the development of society in the digital age determine the growing role of artificial intelligence (AI). This determines the need for its formal and informal study in different levels and in different volumes in both classroom and extracurricular activities of bulgarian schools. On the basis of a curriculum approved by the Ministry of Education and Science, the development of appropriate teaching resources and aids began. In this report, the authors will present an approach to presenting knowledge with general meaning in artificial intelligence by applying logical inferences, rules and dependencies. The main topics of the curriculum and the way of their structuring will be presented. The main idea is, following the requirements of classical artificial intelligence, to consider different methods and approaches for presenting this theory in the context of high school education.

Development and Evaluation of Fuzzy Criteria for the Diagnosis of Rheumatoid Arthritis

1996 ◽  
Vol 35 (04/05) ◽  
pp. 334-342 ◽  
Author(s):  
K.-P. Adlassnig ◽  
G. Kolarz ◽  
H. Leitich
Keyword(s):  
Rheumatoid Arthritis ◽  
Reference Model ◽  
American Rheumatism Association ◽  
Uniform Definition ◽  
Sensitivity Rate ◽  
Fuzzy Techniques ◽  
Definition Of ◽  
Different Levels ◽  
Specificity Rate

Abstract:In 1987, the American Rheumatism Association issued a set of criteria for the classification of rheumatoid arthritis (RA) to provide a uniform definition of RA patients. Fuzzy set theory and fuzzy logic were used to transform this set of criteria into a diagnostic tool that offers diagnoses at different levels of confidence: a definite level, which was consistent with the original criteria definition, as well as several possible and superdefinite levels. Two fuzzy models and a reference model which provided results at a definite level only were applied to 292 clinical cases from a hospital for rheumatic diseases. At the definite level, all models yielded a sensitivity rate of 72.6% and a specificity rate of 87.0%. Sensitivity and specificity rates at the possible levels ranged from 73.3% to 85.6% and from 83.6% to 87.0%. At the superdefinite levels, sensitivity rates ranged from 39.0% to 63.7% and specificity rates from 90.4% to 95.2%. Fuzzy techniques were helpful to add flexibility to preexisting diagnostic criteria in order to obtain diagnoses at the desired level of confidence.

REALIZATION OF IDEAS OF ARTIFICIAL INTELLIGENCE FOR THE FINDING OF HIERARCHY OF MOTIVES OF TRAINING

2018 ◽  
pp. 12-19
Author(s):  
M. G. Koliada ◽  
T. I. Bugayova
Keyword(s):  
Artificial Intelligence ◽  
Hierarchical System ◽  
Productive Activity ◽  
Large Role ◽  
Educational Work ◽  
Intelligent Search ◽  
Dynamic Mechanisms ◽  
Innovative Method ◽  
Effectiveness Of Training ◽  
Probabilistic Nature

The hierarchy of learning motives plays an extremely important role for a management of productive activity of learners, their activity and purposefulness. In the process of educational work, such a motivational hierarchy is formed, where some motives are dynamic mechanisms of other motives that are very difficult to identify at the intuitive level, especially considering the influence of each of them. Therefore, to determine the most significant hierarchical sequence of motives, an innovative method was proposed which is based on the ideas of artificial intelligence. As an example, the search was implemented based on the so-called algorithm of imitation roasting, which is capable to take into account the probabilistic nature of motivational indicators. The article highlights the main leading educational motives of students, on the basis of which the “mechanism” of finding their optimal hierarchical system is shown, and one that simultaneously takes into account the multifactorial influence of their driving causes, taking into account their interconnection, interaction and dynamism. A step-by-step realization of construction of such a hierarchical system of main educational motives in combination with casual, minor motives which are difficult for expecting or providing in advance is shown. Given their unpredictability and probabilistic nature of occurrence, the proposed system of intelligent search allows you to select exactly those sequences of motives that provide the highest productivity and effectiveness of training. The value of the proposed algorithm of imitation roasting is that the accuracy of the result is sacrificed, but the number of iteration cycles decreases, which plays a large role in processing a significant number of motivational indicators.

MODERN INFORMATICS: FROM ROBOTICS TO ARTIFICIAL INTELLIGENCE

2018 ◽  
Vol 1 (8) ◽  
pp. 2-5 ◽  
Author(s):  
L. L. Bosova ◽  
N. N. Samylkina
Keyword(s):  
Artificial Intelligence ◽  
Different Levels

The article describes the work of Informatics Club in the framework of the project "Children University of MPSU". It is considered how it is possible to realize the development of complex questions of informatics in the framework of Club work with students of different levels of education.

scholarly journals Classification of artificial intelligence technologies to determine the civil liability

2021 ◽  
Vol 1794 (1) ◽  
pp. 012001
Author(s):  
A Alekseev ◽  
O Erakhtina ◽  
K Kondratyeva ◽  
T Nikitin
Keyword(s):  
Artificial Intelligence ◽  
Civil Liability
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