TY - JOUR
T1 - Students’ attitudes towards an AI-based interview for university admissions
T2 - Scale development and intervention effects
AU - Shin, Namin
AU - Choi, Eunyoung
AU - Chang, Sejin
N1 - Publisher Copyright:
© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.
PY - 2024/10
Y1 - 2024/10
N2 - This research endeavors to introduce a comprehensive scale tailored to gauge high school students' attitudes toward AI-based interviews for university admissions. Moreover, the study delves into the impact of information provisioning on students' attitudes toward AI-based interviews. The participant cohort comprised 604 high school students, who were on average 17.93 years old(S.D. = 0.80). The structured questionnaire, containing the newly formulated items, was distributed via Google Forms. In Study 1, two distinct scales were devised: the Positive Aspects of AI-based Interview Scale(PAAIS), encompassing 14 items to gauge affirmative perceptions, and the Negative Aspects of AI-based Interview Scale(NAAIS), comprising 11 items targeting adverse perceptions linked to AI-based interviews. The outcomes of exploratory factor analysis unveiled three sub-constructs composing PAAIS labeled as ‘comfortable,’ ‘convenient,’ and ‘fair,’ while NAAIS exhibited dimensions of ‘distrustful’ and ‘unpleasant.’ Subsequently, in Study 2, it was discerned that students’ attitudes towards AI-based interviews could be influenced through exposure to pertinent information concerning advanced AI technology or the underlying rationale behind such interviews. Notably, the absence of attitude alteration with respect to the ‘societal trend’ element underscores the perception that the principles governing recruitment and selection within corporate domains may not be seamlessly applicable to the university entrance examination domain due to differing contextual considerations. The paper includes a discourse encompassing reflections, implications, and constraints linked to the adoption of AI-based interviews in higher education institutions.
AB - This research endeavors to introduce a comprehensive scale tailored to gauge high school students' attitudes toward AI-based interviews for university admissions. Moreover, the study delves into the impact of information provisioning on students' attitudes toward AI-based interviews. The participant cohort comprised 604 high school students, who were on average 17.93 years old(S.D. = 0.80). The structured questionnaire, containing the newly formulated items, was distributed via Google Forms. In Study 1, two distinct scales were devised: the Positive Aspects of AI-based Interview Scale(PAAIS), encompassing 14 items to gauge affirmative perceptions, and the Negative Aspects of AI-based Interview Scale(NAAIS), comprising 11 items targeting adverse perceptions linked to AI-based interviews. The outcomes of exploratory factor analysis unveiled three sub-constructs composing PAAIS labeled as ‘comfortable,’ ‘convenient,’ and ‘fair,’ while NAAIS exhibited dimensions of ‘distrustful’ and ‘unpleasant.’ Subsequently, in Study 2, it was discerned that students’ attitudes towards AI-based interviews could be influenced through exposure to pertinent information concerning advanced AI technology or the underlying rationale behind such interviews. Notably, the absence of attitude alteration with respect to the ‘societal trend’ element underscores the perception that the principles governing recruitment and selection within corporate domains may not be seamlessly applicable to the university entrance examination domain due to differing contextual considerations. The paper includes a discourse encompassing reflections, implications, and constraints linked to the adoption of AI-based interviews in higher education institutions.
KW - AI-based interview
KW - Attitude towards AI-based interview
KW - Intervention effects
KW - Scale development
KW - University admission
UR - http://www.scopus.com/inward/record.url?scp=85190159661&partnerID=8YFLogxK
U2 - 10.1007/s10639-024-12649-4
DO - 10.1007/s10639-024-12649-4
M3 - Article
AN - SCOPUS:85190159661
SN - 1360-2357
VL - 29
SP - 20055
EP - 20076
JO - Education and Information Technologies
JF - Education and Information Technologies
IS - 15
ER -