Stina Westman, J. Kauttonen, Aarne Klemetti, Niilo Korhonen, Milja Manninen, Asko Mononen, Salla Niittymäki, Henry Paananen
{"title":"Artificial Intelligence for Career Guidance – Current Requirements and Prospects for the Future","authors":"Stina Westman, J. Kauttonen, Aarne Klemetti, Niilo Korhonen, Milja Manninen, Asko Mononen, Salla Niittymäki, Henry Paananen","doi":"10.22492/ije.9.4.03","DOIUrl":null,"url":null,"abstract":"Career guidance in the era of life-long learning faces challenges related to building accessible services that bridge education and employment services. So far, only limited research has been conducted on using artificial intelligence to support guidance across higher education and working life. This paper reports on development on using artificial intelligence to support and further career guidance in higher education institutions. Results from focus groups, scenario work and practical trials are presented, mapping requirements and possibilities for using artificial intelligence in career guidance from the viewpoints of students, guidance staff and institutions. The findings indicate potential value and functions as well as drivers and barriers for adopting artificial intelligence in career guidance to support higher education and life-long learning. The authors conceptualize different modes of agency and maturity levels for the involvement of artificial intelligence in guidance processes based on the results. Recommended future research topics in the area of artificially enhanced guidance services include agency in guidance interaction, developing guidance data ecosystem and ethical issues.","PeriodicalId":52248,"journal":{"name":"IAFOR Journal of Education","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2021-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IAFOR Journal of Education","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.22492/ije.9.4.03","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Social Sciences","Score":null,"Total":0}
引用次数: 3
Abstract
Career guidance in the era of life-long learning faces challenges related to building accessible services that bridge education and employment services. So far, only limited research has been conducted on using artificial intelligence to support guidance across higher education and working life. This paper reports on development on using artificial intelligence to support and further career guidance in higher education institutions. Results from focus groups, scenario work and practical trials are presented, mapping requirements and possibilities for using artificial intelligence in career guidance from the viewpoints of students, guidance staff and institutions. The findings indicate potential value and functions as well as drivers and barriers for adopting artificial intelligence in career guidance to support higher education and life-long learning. The authors conceptualize different modes of agency and maturity levels for the involvement of artificial intelligence in guidance processes based on the results. Recommended future research topics in the area of artificially enhanced guidance services include agency in guidance interaction, developing guidance data ecosystem and ethical issues.