The method of student's query analysis while intelligent computer tutoring in SQL

Recently, IT specialties have become one of the most demanded specialties in the world labor market. Simultaneously the traditional teaching in conditions of mass production, even with a professional teacher, has a significant drawback – the fundamental impossibility of adapting to each student. Since the 60s of the twentieth century, researchers worldwide have been developing various computer-tutoring tools that have, less or more, adaptive functions. Nevertheless, the task of the perfect computer tutor development is still far from being solved. The article's research subject is the process of student requests analyzing during intelligent computer tutoring in SQL. The main goal is to develop a method for analyzing the student's SQL queries. The purposes: to form a general scheme and features of the method for analyzing student’s SQL queries based on the principles of technical diagnostics and methods of lexical, syntactic analysis of computer programs; to develop methods for parse tree construction; to create methods for comparing reference and real SQL queries according to their similarity rate; to demonstrate the function ability of the developed methods on specific examples. The methods used computer programs the automatic testing method, the computer programs lexical and syntactic analysis methods, the computer programs parsing trees construction methods, the objects diagnosing method based on comparison with a reference, the strings analysis methods, the method of q-grams. The following results were obtained: the student’s SQL queries analysis method was formed based on a system approach including automatic testing on real data, building query-parsing trees, comparison with a reference, and comprehensive determination of the queries similarity rate. The scientific novelty is the improvement of the method for the student's SQL query analysis during intelligent computer training in SQL query composition.

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PRINCIPAL PROBLEMS OF NATURAL LANGUAGE PROCESSING SYSTEMS

Studia Philologica ◽

10.28925/2311-2425.2018.11.5 ◽

2018 ◽

pp. 35-38

Author(s):

O. Hyryn

Keyword(s):

Natural Language Processing ◽

Natural Language ◽

Language Processing ◽

Syntactic Analysis ◽

Syntactic Ambiguity ◽

Grammatical Structure ◽

English Sentence ◽

Analysis Methods ◽

The Way

The article deals with natural language processing, namely that of an English sentence. The article describes the problems, which might arise during the process and which are connected with graphic, semantic, and syntactic ambiguity. The article provides the description of how the problems had been solved before the automatic syntactic analysis was applied and the way, such analysis methods could be helpful in developing new analysis algorithms. The analysis focuses on the issues, blocking the basis for the natural language processing — parsing — the process of sentence analysis according to their structure, content and meaning, which aims to analyze the grammatical structure of the sentence, the division of sentences into constituent components and defining links between them.

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The engineering skills training process modeling using dynamic bayesian nets

RADIOELECTRONIC AND COMPUTER SYSTEMS ◽

10.32620/reks.2021.2.08 ◽

2021 ◽

pp. 87-96

Author(s):

Andrey Chukhray ◽

Olena Havrylenko

Keyword(s):

Bayesian Networks ◽

Bayesian Network ◽

Learning Process ◽

Probabilistic Inference ◽

Dynamic Bayesian Network ◽

Computer Training ◽

Skills Training ◽

Dynamic Bayesian Networks ◽

Competence Level ◽

Intelligent Computer

The subject of research in the article is the process of intelligent computer training in engineering skills. The aim is to model the process of teaching engineering skills in intelligent computer training programs through dynamic Bayesian networks. Objectives: To propose an approach to modeling the process of teaching engineering skills. To assess the student competence level by considering the algorithms development skills in engineering tasks and the algorithms implementation ability. To create a dynamic Bayesian network structure for the learning process. To select values for conditional probability tables. To solve the problems of filtering, forecasting, and retrospective analysis. To simulate the developed dynamic Bayesian network using a special Genie 2.0-environment. The methods used are probability theory and inference methods in Bayesian networks. The following results are obtained: the development of a dynamic Bayesian network for the educational process based on the solution of engineering problems is presented. Mathematical calculations for probabilistic inference problems such as filtering, forecasting, and smoothing are considered. The solution of the filtering problem makes it possible to assess the current level of the student's competence after obtaining the latest probabilities of the development of the algorithm and its numerical calculations of the task. The probability distribution of the learning process model is predicted. The number of additional iterations required to achieve the required competence level was estimated. The retrospective analysis allows getting a smoothed assessment of the competence level, which was obtained after the task's previous instance completion and after the computation of new additional probabilities characterizing the two checkpoints implementation. The solution of the described probabilistic inference problems makes it possible to provide correct information about the learning process for intelligent computer training systems. It helps to get proper feedback and to track the student's competence level. The developed technique of the kernel of probabilistic inference can be used as the decision-making model basis for an automated training process. The scientific novelty lies in the fact that dynamic Bayesian networks are applied to a new class of problems related to the simulation of engineering skills training in the process of performing algorithmic tasks.

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LEGAL REGULATION OF THE USE OF ARTIFICIAL INTELLIGENCE IN NOTARY AND CIVIL PROCESSES AS AN ELEMENT PROTECTION AND PROTECTION OF THE RIGHTS OF RESIDENTS (RESIDENTS) OF THE TEMPORARILY OCCUPIED TERRITORIES OF UKRAINE

Juridical science ◽

10.32844/2222-5374-2020-103-1.54 ◽

2020 ◽

pp. 447-456

Author(s):

Г. В. Луцька

Keyword(s):

Artificial Intelligence ◽

Social Relations ◽

Computer Programs ◽

Legal Regulation ◽

Civil Procedure ◽

Civil Process ◽

Procedure Code ◽

Occupied Territories ◽

Intelligent Computer ◽

Autonomous Republic

The article considers the problem of application of artificial intelligence in the law of Ukraine in general and in the notarial and civil process in particular. The legal consequences of the legal regime of temporary occupation of some territories of Ukraine are indicated and the ways to eliminate obstacles in the protection and defense of the rights of citizens of Ukraine in these territories are determined. The legal construction of «artificial intelligence» is studied and its types are offered. The conclusion about the expediency of using intelligent computer programs, intelligent information technologies as types of artificial intelligence in notarial and executive processes is substantiated. It is proposed to consider the use of artificial intelligence in notarial and civil proceedings for citizens of Ukraine living in the Autonomous Republic of Crimea or in the occupied territories of Donetsk and Luhansk regions, within the limits, in the manner and in the manner prescribed by law of Ukraine. It is proved that the introduction of artificial intelligence through the mechanism of protection and defense of human and civil rights and freedoms in the civil process must be adapted to social relations that arise and exist, not violate the constitutional rights and freedoms of man and citizen in Ukraine and have a legal basis. Based on the scientific and practical analysis of the Civil Procedure Code of Ukraine, it is proposed for citizens of Ukraine living in the Autonomous Republic of Crimea or in the occupied territories of Donetsk and Luhansk regions to establish that lawsuits, separate and injunctive proceedings are entirely online. The procedure (procedure) and features of such proceedings with the use of various types of artificial intelligence (such as chatbots and other information intelligence technologies) should be defined in the Civil Procedure Code of Ukraine. It is noted that the introduction of the above mechanism to protect and defend the rights of citizens living in the Autonomous Republic of Crimea or in the occupied territories of Donetsk and Luhansk regions through intelligent computer programs will require proper maintenance and support of such programs to prevent leakage of information, leakage of personal data, etc. The conclusion is substantiated that e-litigation and remote notarial proceedings will increase the effectiveness of notarial and judicial forms of protection and protection of rights and make these state forms of protection more flexible, able to anticipate the peculiarities of procedural actions involving residents of the temporarily occupied territories.

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A Consistent Set of Oxidation Number Rules for Intelligent Computer Tutoring

Journal of Chemical Education ◽

10.1021/ed079p465 ◽

2002 ◽

Vol 79 (4) ◽

pp. 465 ◽

Cited By ~ 3

Author(s):

Dale A. Holder ◽

Benny G. Johnson ◽

Paul J. Karol

Keyword(s):

Oxidation Number ◽

Computer Tutoring ◽

Intelligent Computer

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A Study on the Awareness of Artificial Intelligence Among Youth and Its Impact on Employment

International Journal of Advanced Research in Science, Communication and Technology ◽

10.48175/ijarsct-1168 ◽

2021 ◽

pp. 461-465

Author(s):

Ms. Aswathy K A ◽

Dr. Rosalind Gonzaga ◽

Ms. Josna Susan Francis

Keyword(s):

Artificial Intelligence ◽

At Risk ◽

Secondary Analysis ◽

Negative Attitude ◽

Computer Programs ◽

Skilled Labor ◽

Intelligent Machines ◽

Employment Sector ◽

Near Future ◽

Intelligent Computer

Artificial Intelligence (A.I.) is the Engineering and Science of making Intelligent Machines and Intelligent Computer Programs. It develops Intelligence in Machines and enables them to think like Humans. The study was conducted to find out level of awareness about artificial intelligence among youth and its impact on employment. From the study it was found that artificial intelligence is career threatening and the youth shows a negative attitude towards it. As a result of development of artificial intelligence the employment sector now demands more technological skills from the employees. It was found that majority of the respondents are of the opinion that artificial intelligence will replace the human workers in the near future. It is evident from the secondary analysis that low skilled jobs are at risk due to artificial intelligence, because the replacement is more in low skilled jobs as compared to high skilled jobs. It can be conclude that , demand of skilled jobs is on the rise and there might be a temporary shortage of skilled labor but if the current pace of development in education and retraining continues it will be resolved soon.

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