{"title":"Impressing Artificial Intelligence: Automated Job Interview Training in Professional English Subjects","authors":"Andrew Jarvis, Anna Ho, Grace Lim","doi":"10.1177/00336882241245449","DOIUrl":null,"url":null,"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.","PeriodicalId":3,"journal":{"name":"ACS Applied Electronic Materials","volume":"27 24","pages":""},"PeriodicalIF":4.7000,"publicationDate":"2024-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Electronic Materials","FirstCategoryId":"98","ListUrlMain":"https://doi.org/10.1177/00336882241245449","RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
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.
期刊介绍:
ACS Applied Electronic Materials is an interdisciplinary journal publishing original research covering all aspects of electronic materials. The journal is devoted to reports of new and original experimental and theoretical research of an applied nature that integrate knowledge in the areas of materials science, engineering, optics, physics, and chemistry into important applications of electronic materials. Sample research topics that span the journal's scope are inorganic, organic, ionic and polymeric materials with properties that include conducting, semiconducting, superconducting, insulating, dielectric, magnetic, optoelectronic, piezoelectric, ferroelectric and thermoelectric.
Indexed/Abstracted:
Web of Science SCIE
Scopus
CAS
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Portico