The Use of Machine Translation System for Component Development of Adaptive Computer System for Individual Testing of Students’ Knowledge

Fedosov, A. Yu.; Eliseeva, Dina; Karnaukhova, Anastasia

doi:10.1007/978-3-030-37858-5_40

Cited by 4 publications

(2 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In the first case, there are large databases of tagged data, and in the second, just data. Therefore, in recent years, researchers have been trying to reinforce learning -the model can interact with the provided environment, and thereby learn (Fedosov A., Eliseeva D., Karnaukhova A., 2019).…”

Section: Discussionmentioning

confidence: 99%

The Evolution of Artificial Intelligence and the Possibility of its Application in Cyber Games

Eliseeva

Fedosov

Agaltsova

et al. 2020

View full text Add to dashboard Cite

Artificial intelligence, as a separate field of research, is currently experiencing a boom - new methods of machine learning and hardware are emerging and improving, and the results achieved change the life of society. Machine translation, handwriting recognition, speech recognition are changing our reality. The work of creating unmanned vehicles, voice assistants and other devices using these technologies is in an active process. The article examines the historical context of the artificial intelligence development, it evaluates the possibilities of its introduction into cyber games, as a safe and effective platform for testing new methods of machine learning. The promotion of such projects can increase the reputation of development companies, ensure increased user confidence in other products and, with a competent marketing strategy, cause a significant public resonance among video game fans, providing the developer with economic profit.

show abstract

Section: Discussionmentioning

confidence: 99%

The Evolution of Artificial Intelligence and the Possibility of its Application in Cyber Games

Eliseeva

Fedosov

Agaltsova

et al. 2020

View full text Add to dashboard Cite

show abstract

“…The emergence of machine translation in the realm of AI has made great strides in expediting the teaching of English (Yong, 2020). Although machine translation is still not perfectly accurate (H. ), Fedosov et al (2019 posit that it can be employed whilst working with training materials when teaching a foreign language. Machine translation can also serve as a tool to motivate learners to learn English and to alleviate their learning fears (Tsai & Liao, 2021).…”

Section: Ai Applications In Eltmentioning

confidence: 99%

A Systematic Review of Research on the Use of Artificial Intelligence in English Language Teaching and Learning (2015-2021): What are the Current Effects?

Sharadgah

Sa’di

2022

JITE:Research

View full text Add to dashboard Cite

Aim/Purpose: This study carried out a systematic review of the literature on artificial intelligence (AI) in English language teaching (ELT). The objective was to delineate the current research progress in the field and to further understand the challenges. Background: The study analyzed articles published between 2015 and 2021. Methodology: The qualitative research method was employed. Five steps were taken to steer the review. 200 articles were scrutinized; 64 were retained. Contribution: Prior research on AI in ELT has not investigated how the literature is progressing or what areas of AI are being covered. Without a holistic picture, some important research findings could be missed. Understanding how studies on AI in ELT are designed and implemented will contribute to a greater understanding of the existing state of research. Findings: Findings show that there is a promising future for AI in ELT. AI in ELT yielded positive results in terms of optimizing the English language skills, translation, assessment, recognition, attitude, satisfaction, etc. It was also found out that more and more articles on the topic are being published; the mixed research method is the most commonly used, higher education level is the most sampled, students as participants are the most sampled, and most studies developed novel AI-based systems. Various AI approaches have been identified in the reviewed studies, including machine learning, neural network, support vector machine, genetic algorithms, deep learning, decision tree, expert system, natural language processing, data mining, cloud computing, and edge computing. However, AI in ELT is still in its infancy, where little research has been conducted and gaps in the literature are still present, especially in terms of inherent issues related to body language, gestures, expressions, emotions, translation, lack of elaborate description of teaching material used for learning driven by AI, uncertainties and vagueness with regards to what can be considered under the realm of AI, and most authors being outside of the ELT discipline. Recommendations for Practitioners: This literature review is likely to provide practitioners with an overview of the current adopted technology, research method, instruments and/or tools, educational level, language skill, and the effects reported by the AI-based studies for designing effective systems for the use of AI in their ELT classrooms. Recommendation for Researchers: Researchers need to conduct research on AI in ELT along with a detailed in-depth description of the methodology, research design, and the proposed systems used to achieve AI in ELT. Furthermore, it is recommended that researchers explore the efficiency of AI-based systems used in previous research and ensure their relevance and functionality. They are also required to provide in-depth analysis of the challenges inherent to systems that have been highlighted in the literature, which will maximize the potentials of these AI-based technologies. Impact on Society: The findings of this paper can provide visualization of research findings that could particularly benefit researchers, educators, and AI specialists who are involved in the study of the applications of AI in ELT. Future Research: Future AI research needs to seriously include more detailed descriptions of the method in further research.

show abstract

Comparative Analysis of Products for Testing Software

Fedosov

Eliseeva

Ходакова

et al. 2020

Software Engineering Perspectives in Intelligent Systems

View full text Add to dashboard Cite

The Use of Machine Translation System for Component Development of Adaptive Computer System for Individual Testing of Students’ Knowledge

Cited by 4 publications

References 8 publications

The Evolution of Artificial Intelligence and the Possibility of its Application in Cyber Games

The Evolution of Artificial Intelligence and the Possibility of its Application in Cyber Games

A Systematic Review of Research on the Use of Artificial Intelligence in English Language Teaching and Learning (2015-2021): What are the Current Effects?

Comparative Analysis of Products for Testing Software

Contact Info

Product

Resources

About