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@article{ART002826592},
author={Kim Seonghun and Sion Park and Jiwon Park and Youjin Oh},
title={A Study on the Intention to Use of the AI-related Educational Content Recommendation System in the University Library: Focusing on the Perceptions of University Students and Librarians},
journal={Journal of Korean Library and Information Science Society},
issn={2466-2542},
year={2022},
volume={53},
number={1},
pages={231-263},
doi={10.16981/kliss.53.1.202203.231}

TY - JOUR
AU - Kim Seonghun
AU - Sion Park
AU - Jiwon Park
AU - Youjin Oh
TI - A Study on the Intention to Use of the AI-related Educational Content Recommendation System in the University Library: Focusing on the Perceptions of University Students and Librarians
JO - Journal of Korean Library and Information Science Society
PY - 2022
VL - 53
IS - 1
PB - Korean Library And Information Science Society
SP - 231
EP - 263
SN - 2466-2542
AB - The understanding and capability to utilize artificial intelligence (AI) incorporated technology has become a required basic skillset for the people living in today’s information age, and various members of the university have also increasingly become aware of the need for AI education. Amidst such shifting societal demands, both domestic and international university libraries have recognized the users’ need for educational content centered on AI, but a user-centered service that aims to provide personalized recommendations of digital AI educational content is yet to become available. It is critical while the demand for AI education amongst university students is progressively growing that university libraries acquire a clear understanding of user intention towards an AI educational content recommender system and the potential factors contributing to its success. This study intended to ascertain the factors affecting acceptance of such system, using the Extended Technology Acceptance Model with added variables - innovativeness, self-efficacy, social influence, system quality and task-technology fit - in addition to perceived usefulness, perceived ease of use, and intention to use. Quantitative research was conducted via online research surveys for university students, and quantitative research was conducted through written interviews of university librarians. Results show that all groups, regardless of gender, year, or major, have the intention to use the AI-related Educational Content Recommendation System, with the task suitability factor being the most dominant variant to affect use intention. University librarians have also expressed agreement about the necessity of the recommendation system, and presented budget and content quality issues as realistic restrictions of the aforementioned system.
KW - AI-related Education Content;Digital Content;University Library Recommendation System;Intention to Use;Technology Acceptance Model(TAM)
DO - 10.16981/kliss.53.1.202203.231
ER -

Kim Seonghun, Sion Park, Jiwon Park and Youjin Oh. (2022). A Study on the Intention to Use of the AI-related Educational Content Recommendation System in the University Library: Focusing on the Perceptions of University Students and Librarians. Journal of Korean Library and Information Science Society, 53(1), 231-263.

Kim Seonghun, Sion Park, Jiwon Park and Youjin Oh. 2022, "A Study on the Intention to Use of the AI-related Educational Content Recommendation System in the University Library: Focusing on the Perceptions of University Students and Librarians", Journal of Korean Library and Information Science Society, vol.53, no.1 pp.231-263. Available from: doi:10.16981/kliss.53.1.202203.231

Kim Seonghun, Sion Park, Jiwon Park, Youjin Oh "A Study on the Intention to Use of the AI-related Educational Content Recommendation System in the University Library: Focusing on the Perceptions of University Students and Librarians" Journal of Korean Library and Information Science Society 53.1 pp.231-263 (2022) : 231.

Kim Seonghun, Sion Park, Jiwon Park, Youjin Oh. A Study on the Intention to Use of the AI-related Educational Content Recommendation System in the University Library: Focusing on the Perceptions of University Students and Librarians. 2022; 53(1), 231-263. Available from: doi:10.16981/kliss.53.1.202203.231

Kim Seonghun, Sion Park, Jiwon Park and Youjin Oh. "A Study on the Intention to Use of the AI-related Educational Content Recommendation System in the University Library: Focusing on the Perceptions of University Students and Librarians" Journal of Korean Library and Information Science Society 53, no.1 (2022) : 231-263.doi: 10.16981/kliss.53.1.202203.231

Kim Seonghun; Sion Park; Jiwon Park; Youjin Oh. A Study on the Intention to Use of the AI-related Educational Content Recommendation System in the University Library: Focusing on the Perceptions of University Students and Librarians. Journal of Korean Library and Information Science Society, 53(1), 231-263. doi: 10.16981/kliss.53.1.202203.231

Kim Seonghun; Sion Park; Jiwon Park; Youjin Oh. A Study on the Intention to Use of the AI-related Educational Content Recommendation System in the University Library: Focusing on the Perceptions of University Students and Librarians. Journal of Korean Library and Information Science Society. 2022; 53(1) 231-263. doi: 10.16981/kliss.53.1.202203.231

Kim Seonghun, Sion Park, Jiwon Park, Youjin Oh. A Study on the Intention to Use of the AI-related Educational Content Recommendation System in the University Library: Focusing on the Perceptions of University Students and Librarians. 2022; 53(1), 231-263. Available from: doi:10.16981/kliss.53.1.202203.231

Kim Seonghun, Sion Park, Jiwon Park and Youjin Oh. "A Study on the Intention to Use of the AI-related Educational Content Recommendation System in the University Library: Focusing on the Perceptions of University Students and Librarians" Journal of Korean Library and Information Science Society 53, no.1 (2022) : 231-263.doi: 10.16981/kliss.53.1.202203.231