Voice Assistants with Artificial Intelligence for Improving Academic English

2021 ◽  
Author(s):  
Vladimir Tregubov
Keyword(s):  
Artificial Intelligence ◽  
Comparative Analysis ◽  
Voice Recognition ◽  
Educational Process ◽  
Academic English ◽  
Academic Vocabulary ◽  
Active Mode ◽  
Specialized Software

The article describes applications of using voice recognition technology based on artificial intelligence to the educational process. The author presents a comparative analysis of existing examples artificial intelligence in the educational process. Artificial intelligence uses in specialized software it makes educational process more convenient for both the students and the teachers. There is a description of an application “Academic phrase bank" developed by author. The application consists of two specialising actions for Google assistant. The application allows to increase academic vocabulary, train of creating grammatically correct academic expressions, and memorize templates of academic phrases. In active mode, this application helps to create correct phrases of academic English and improve the abilities of understanding English speech.

scholarly journals Using Voice Recognition in E-Learning System to Reduce Educational Inequality During Covid-19

2021 ◽  
Vol 11 (04) ◽  
pp. 01-16
Author(s):  
Vladimir Tregubov
Keyword(s):  
Artificial Intelligence ◽  
Educational Inequality ◽  
Voice Recognition ◽  
Traditional Education ◽  
Educational Process ◽  
Learning System ◽  
Educational Institutions ◽  
Inequality In Education ◽  
E Learning ◽  
Online Format

During the COVID -19 pandemic, educational institutions around the world faced problems that have to do with the frustration of students for whom traditional education has been replaced by the online format. Students are experiencing technical difficulties in the digitalization of education. International monitoring of education systems has shown that quite a few countries were ready to move to distance learning, both for technical and economic reasons. The covid pandemic has caused an increase in educational inequality. Elearning systems were expected to reduce inequality in education, but empirical research has shown that learning in this format not only does not reduce, but can increase inequality, increasing the gap in educational outcomes between students with different socioeconomic status. The article describes applications of using voice recognition technology based on artificial intelligence which, by our opinion, may reduce educational inequality during covid-19. We presented a comparative analysis of existing examples artificial intelligence in the educational process. Artificial intelligence uses in specialized software it makes educational process more convenient for both the students and the teachers. There is a description of an application “Academic phrase bank" developed by author. The application consists of two specialising actions for Google assistant. The application allows to increase academic vocabulary, train of creating grammatically correct academic expressions, and memorize templates of academic phrases. In active mode, this application helps to create correct phrases of academic English and improve the abilities of understanding English speech.

MULTI-HOP WIRELESS NETWORKS AUTOMATED SIMULATION

2017 ◽  
Vol 13 (3) ◽  
pp. 68-78
Author(s):  
A. A. Pavlov ◽  
I. O. Datyev ◽  
M. G. Shishaev
Keyword(s):  
Wireless Networks ◽  
Comparative Analysis ◽  
Simulation Model ◽  
Conceptual Model ◽  
Software Package ◽  
Software Tools ◽  
Specialized Software ◽  
Automated Simulation ◽  
Network Simulators ◽  
Modern Experience

Simulation is the main way for testing technologies in the field of multi-hop wireless networks (MWN). Creating a simulation model MWN - a time-consuming task associated with the use of specialized software tools, called network simulators. In this paper, the modern experience of modeling MWN and the main problems are formulated. One of the main problem is the comparative analysis' impossibility of the experiments results conducted by various researchers. This is due to the reasons associated with the models used for testing, the planning an imitation experiment and the principal differences in the network simulators. To solve this problem, authors propose a generalized conceptual model of MWN simulation and a specialized software package that automates the execution of experiment series in a heterogeneous modeling environment.

Robot Teaching, Pedagogy, and Policy

2020 ◽  
pp. 787-803
Author(s):  
Elana Zeide
Keyword(s):  
Artificial Intelligence ◽  
Analytical Methods ◽  
Personalized Learning ◽  
Educational Process ◽  
Learning Systems ◽  
Policy Decisions ◽  
Public Discussion ◽  
Teaching Pedagogy ◽  
Do So

This chapter looks at the use of artificial intelligence (AI) in education, which immediately conjures the fantasy of robot teachers, as well as fears that robot teachers will replace their human counterparts. However, AI tools impact much more than instructional choices. Personalized learning systems take on a whole host of other educational roles as well, fundamentally reconfiguring education in the process. They not only perform the functions of robot teachers but also make pedagogical and policy decisions typically left to teachers and policymakers. Their design, affordances, analytical methods, and visualization dashboards construct a technological, computational, and statistical infrastructure that literally codifies what students learn, how they are assessed, and what standards they must meet. However, school procurement and implementation of these systems are rarely part of public discussion. If they are to remain relevant to the educational process itself, as opposed to just its packaging and context, schools and their stakeholders must be more proactive in demanding information from technology providers and setting internal protocols to ensure effective and consistent implementation. Those who choose to outsource instructional functions should do so with sufficient transparency mechanisms in place to ensure professional oversight guided by well-informed debate.

scholarly journals Taking into account Chinese students’ cognitive and psychological characteristics while teaching Russian grammar

2020 ◽  
Vol 9 (1) ◽  
pp. 283-288
Author(s):  
Yu Sun
Keyword(s):  
Comparative Analysis ◽  
Learning Strategies ◽  
Learning Process ◽  
Chinese Students ◽  
Educational Process ◽  
Russian Language ◽  
Psychological Characteristics ◽  
Oral Speech ◽  
The Russian Language ◽  
Specific Learning

This paper aims to discuss the problem of nationally oriented teaching of Russian grammar to Chinese students. The author analyzes the works that are devoted to the study of Chinese students cognitive and psychological characteristics. The analysis revealed specific learning strategies that Chinese students use when learning a foreign language. When training a mono-ethnic group, the national-oriented approach is considered optimal. To implement this approach, a comparative analysis of systems of contacting languages is necessary to determine the zones of interlanguage and intralanguage interferences. The most important factor in the effectiveness of the educational process is the adequacy of the teachers ideas about students from different regions. The author concludes that in order to maintain motivation for mastering the Russian language and optimize the learning process as a whole when developing curricula and class books for Chinese students, it is necessary to strive to make the learning process not only effective, but also as comfortable as possible for students. Taking into account Chinese students cognitive and psychological characteristics will not only contribute to the development of strong grammar skills, but will also ensure the development of oral speech skills in Russian. The paper provides recommendations for intensifying the process of teaching Russian grammar to Chinese students. The following research methods were used: a comparative analysis, an analysis and a synthesis.

scholarly journals Integration Trend of Digitalization of Teachers' Labor in the Practice of Russian Universities

2021 ◽  
Vol 93 ◽  
pp. 01014
Author(s):  
Maria Zakharova ◽  
Maksim Voronin
Keyword(s):  
Comparative Analysis ◽  
Educational Experience ◽  
Educational Process ◽  
Quality Of Education ◽  
Open University ◽  
Digital Environment ◽  
Educational Content ◽  
Russian Universities

The article examines the features of the organization of the educational process in the context of digitalization, analyzes the integration tendency of teachers' work in the practice of Russian universities, provides a comparative analysis of the practice of the Open University. This paper analyzes the educational experience that has developed in the process of emergency delivery of educational content to students during a pandemic. The models of mixed, purely distance and duplicate education are analyzed. The article substantiates the idea that there is a need for the formation of criteria for the quality of education online, and, therefore, the criteria for the quality of the organization of the educational process, including the work of teachers, are changing. This paper outlines some steps that are being taken by Russian universities in the field of researching trends related to improving the digital environment as a whole, regardless of the pandemic and other factors.

scholarly journals The Effect of Digital Economy and Artificial Intelligence on The Participants of The School Educational Process

2020 ◽  
Vol 8 (SPE2) ◽  
Author(s):  
Mikhail V. Vinichenko ◽  
◽  
Marina V. Rybakova ◽  
Marina V. Vinogradova ◽  
Maksim A. Malyshev ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Digital Economy ◽  
Educational Process

scholarly journals Software Platform for Designing and Running Artificial Intelligence Competitions with a Visualization Subsystem

2019 ◽  
Author(s):  
Дмитрий Александрович Коростелев ◽  
Dmitriy Aleksandrovich Korostelev ◽  
Алексей Радченко ◽  
Aleksey Radchenko ◽  
Никита Сильченко ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Intelligent Agents ◽  
Intelligent Systems ◽  
Software Platform ◽  
Main Approach ◽  
Specialized Software ◽  
Operational Testing ◽  
New Ideas ◽  
Systems Simulation

The paper describes the solution to the problem of testing the efficiency of new ideas and algorithms for intelligent systems. Simulation of interaction of the corresponding intelligent agents in a competitive form implementing different algorithms is proposed to use as the main approach to the solution. To support this simulation, a specialized software platform is used. The paper describes the platform developed for running competitions in artificial intelligence and its subsystems: a server, a client and visualization. Operational testing of the developed system is also described which helps to evaluate the efficiency of various algorithms of artificial intelligence in relation to the simulation like "Naval Battle".

MENTORING AS A FORM OF TEACHING ACTIVITY IN THE NEW DIGITAL EDUCATIONAL ENVIRONMENT

2021 ◽  
Vol 3 (102) ◽  
pp. 199-210
Author(s):  
ANNA V. POPOVA
Keyword(s):  
Comparative Analysis ◽  
Scientific Literature ◽  
Educational Environment ◽  
Educational Process ◽  
Training Process ◽  
Teaching Activity ◽  
Significant Difference

The article reveals the essential features of mentoring as a special type of pedagogical activity based on the concept of constructivism applying comparative analysis of individual legal acts in the field of education, as well as a thorough study of the Russian and foreign scientific literature. The author determines essential characteristics of this activity in the training process and the peculiarities of the mentor and mentee relationships. The article shows a significant difference between mentoring and coaching in the Russian educational process.

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