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Article: Impressing Artificial Intelligence: Automated Job Interview Training in Professional English Subjects

TitleImpressing Artificial Intelligence: Automated Job Interview Training in Professional English Subjects
Authors
KeywordsAI interviewing
AI literacy
artificial intelligence (AI) in language learning
English for specific purposes
professional English
Issue Date12-Apr-2024
PublisherSAGE Publications
Citation
RELC Journal, 2024 How to Cite?
Abstract

More organizations are using automated job interview platforms to screen candidates at the early stages of the recruitment process. These platforms enable job candidates to take automated video interviews remotely using their personal devices. The interviews are analysed by artificial intelligence (AI) powered algorithms to produce analytics which inform hiring decisions. In this article, we explore the use of automated job interviewing within professional English subjects delivered to undergraduate students in Hong Kong. The innovation was introduced to help students to keep up with recruitment practices, provide speaking practice and explore AI-powered evaluation as a form of feedback. As well as outlining how automated interviewing was integrated into our teaching practice, we discuss student feedback on the experience and offer suggestions for future teaching practice with this technology. We also highlight considerations for practitioners such as the acceptance and adoption of AI technologies into language learning provision and the development of AI literacy skills. AI technologies have much potential for language teaching and this article offers a practical exploration into one such technology: automated job interviewing.


Persistent Identifierhttp://hdl.handle.net/10722/357232
ISSN
2023 Impact Factor: 3.6
2023 SCImago Journal Rankings: 1.333
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorJarvis, Andrew-
dc.contributor.authorHo, Anna-
dc.contributor.authorLim, Grace-
dc.date.accessioned2025-06-23T08:54:10Z-
dc.date.available2025-06-23T08:54:10Z-
dc.date.issued2024-04-12-
dc.identifier.citationRELC Journal, 2024-
dc.identifier.issn0033-6882-
dc.identifier.urihttp://hdl.handle.net/10722/357232-
dc.description.abstract<p>More organizations are using automated job interview platforms to screen candidates at the early stages of the recruitment process. These platforms enable job candidates to take automated video interviews remotely using their personal devices. The interviews are analysed by artificial intelligence (AI) powered algorithms to produce analytics which inform hiring decisions. In this article, we explore the use of automated job interviewing within professional English subjects delivered to undergraduate students in Hong Kong. The innovation was introduced to help students to keep up with recruitment practices, provide speaking practice and explore AI-powered evaluation as a form of feedback. As well as outlining how automated interviewing was integrated into our teaching practice, we discuss student feedback on the experience and offer suggestions for future teaching practice with this technology. We also highlight considerations for practitioners such as the acceptance and adoption of AI technologies into language learning provision and the development of AI literacy skills. AI technologies have much potential for language teaching and this article offers a practical exploration into one such technology: automated job interviewing.</p>-
dc.languageeng-
dc.publisherSAGE Publications-
dc.relation.ispartofRELC Journal-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjectAI interviewing-
dc.subjectAI literacy-
dc.subjectartificial intelligence (AI) in language learning-
dc.subjectEnglish for specific purposes-
dc.subjectprofessional English-
dc.titleImpressing Artificial Intelligence: Automated Job Interview Training in Professional English Subjects-
dc.typeArticle-
dc.identifier.doi10.1177/00336882241245449-
dc.identifier.scopuseid_2-s2.0-85190506027-
dc.identifier.eissn1745-526X-
dc.identifier.isiWOS:001201450000001-
dc.identifier.issnl0033-6882-

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