A systematic review on artificial intelligence dialogue systems for enhancing English as foreign language students’ interactional competence in the university
Систематический обзор систем диалога на основе искусственного интеллекта для повышения интерактивной компетенции студентов, изучающих английский язык как иностранный, в университете
2023-01-01
SCID: 54.1/3zcfse28
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AI dialogue systemsEnglish as a Foreign LanguagePRISMA systematic reviewinteractional competencetechnological integration
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Abstract (AI)
Previous studies demonstrate that the use of artificial intelligence (AI) dialogue systems for English as a Foreign Language (EFL) education has effectively improved university students' reading, writing, and listening abilities. However, there are limited systematic reviews focused on the evidence-based interactional competence of EFL university students. This study aims to examine the use of AI dialogue systems to enhance EFL university students' interactional competence. Through the PRISMA process, this study identified 28 articles published between January 2013 and August 2022 in journals and conferences from the most popular databases, including Google Scholar, ProQuest, IEEE, ScienceDirect, and Web of Science. The systematic review identified six dimensions and 25 sub-dimensions that influence the application of AI dialogue systems for EFL learning. The six dimensions include technological integration, task designs, students’ engagement, learning objectives, technological limitations, and the novelty effect. Gaps are identified that (1) components of debate and problem-solving skills in EF acquisition in university education seemed to be overlooked in the AI dialogue system design, and (2) the importance of embedding culture, humor and empathy functions were not taken into consideration in the AI dialogue system. This study finds that the development and implementation of an AI dialogue system in EFL is still in its infancy stage. Future research should emphasize meaning-based communication, intelligibility in language competency, debate, and problem-solving skills in university education.
Key Findings
1
AI dialogue system designs commonly neglect debate and problem-solving components relevant to university-level EFL education.
2
AI dialogue systems frequently omit cultural, humor, and empathy functions in their design for EFL learners.
3
Development and implementation of AI dialogue systems for EFL interactional competence remain in an infancy stage.
4
Future research should prioritize meaning-based communication, intelligibility in language competency, and incorporation of debate and problem-solving skills.
5
Systematic review of 28 articles (Jan 2013–Aug 2022) examined AI dialogue systems for enhancing EFL university students' interactional competence.
6
The review identified six influencing dimensions: technological integration, task designs, students’ engagement, learning objectives, technological limitations, and the novelty effect.
7
Within those six dimensions the study delineated 25 sub-dimensions that affect application of AI dialogue systems in EFL learning.
Research Object
Artificial intelligence (AI) dialogue systems used for English as a Foreign Language (EFL) instruction for university students
Research Subject
Enhancement of university EFL students' interactional competence (dimensions including technological integration, task design, student engagement, learning objectives, technological limitations, and novelty effect) via AI dialogue systems
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2023-01-01
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