The Influential Role of Robot in Second Language Classes Based on Artificial Intelligence

Thinh, Nguyen Truong; Hai, Nguyen Dao Xuan; Tho, Tuong Phuoc

doi:10.18178/ijmerr.9.9.1306-1311

Cited by 2 publications

(6 citation statements)

References 2 publications

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“…In terms of listening skills, AI-based technology can select appropriate listening material from a large corpus in keeping with students' needs and abilities in English. In the field of oral training, the AI-based robots are able to speak, put questions and respond to students' questions (Thinh et al, 2020). In the field of translation, AI machine translation is constantly improving with the various kinds of software that are widely used (Dai, 2022).…”

Section: Ai Applications In Eltmentioning

confidence: 99%

“…Huang et al, 2021). Moreover, face analysis using face recognition technology can help in checking student attendance and accurately identifying the current class size, which helps reduce teachers' tasks and enables them to manage class more effectively (Thinh et al, 2020). Image recognition technology can considerably reduce the workload of teachers by scanning and marking exams and obtaining text content from digital text images for instance.…”

Section: Ai Applications In Eltmentioning

confidence: 99%

“…Humanoid robots are professional robots designed to mimic human movements and interactions (Sowmiya et al, 2022). According to Thinh et al (2020), using robots as instructors could have advantages for students, including "repeatability; flexibility; digitization; humanoid appearance; body movement/motion; interaction; anthropomorphism; sensing capability, intelligence and automatic speech recognition; language understanding and dialogue management; emotional Expression" (p.…”

Section: Ai Applications In Eltmentioning

confidence: 99%

“…Based on the data reported in the Appendix, various AI approaches have been incorporated into ELT. For example, machine learning has been used to program a robot that talks to students and produces different sentence forms (Thinh et al, 2020), recognizes the optimal feature set of pedagogical factors distinguishing high-achievers from low-achievers in reading (Xiao & Hu, 2019), "analyze[s] the key competences assessment of English teaching disciplines and build[s] an evaluation model" (T. Zhao & Cai, 2021, p. 1), builds an intelligent online English education classroom management system (Y. Wang, 2021), and assesses students' knowledge of grammar (Srikanthan et al, 2020).…”

Section: State Of Current Research On Ai In Eltmentioning

confidence: 99%

“…Zhu, 2018). Besides, natural language processing is used to make robots smarter, with the ability to talk and ask and answer questions of students (Thinh et al, 2020). Moreover, studies reviewed indicate that data mining is utilized to create a thorough assessment of the learners' English test scores and nominates recommendations for reference teaching (Wu, 2021), to "analyze the association rules of question types to find some unknown information in an ordered data" (Shen, 2021).…”

Section: State Of Current Research On Ai In Eltmentioning

confidence: 99%

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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

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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.

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Section: Ai Applications In Eltmentioning

confidence: 99%

Section: Ai Applications In Eltmentioning

confidence: 99%

Section: Ai Applications In Eltmentioning

confidence: 99%

Section: State Of Current Research On Ai In Eltmentioning

confidence: 99%

Section: State Of Current Research On Ai In Eltmentioning

confidence: 99%

See 3 more Smart Citations

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

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Social robots in a translanguaging pedagogy: A review to identify opportunities for robot-assisted (language) learning

Berghe

2022

Front. Robot. AI

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This mini review discusses the use of social robots in a translanguaging pedagogy: the use of robots to enable students to use their full linguistic repertoire within schools, so any language that they speak at home or in another aspect of their lives. Current research on robot-assisted second-language learning is reviewed with the aim of finding out whether students’ languages have been employed strategically to support learning of another language. A total of 83 articles has been analyzed on the use of first and second languages in student-robot interactions. Most interactions were either exclusively in the second language, or exclusively in the first language, with only target words in the second language. Few studies strategically mixed the two languages to bootstrap learning, and only one study used the first language of students with migrant backgrounds to learn the second language. The review concludes with recommendations for future use of social robots in a translanguaging pedagogy.

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The Influential Role of Robot in Second Language Classes Based on Artificial Intelligence

Cited by 2 publications

References 2 publications

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

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

Social robots in a translanguaging pedagogy: A review to identify opportunities for robot-assisted (language) learning

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