ERIC Number: EJ1480206
Record Type: Journal
Publication Date: 2025-Aug
Pages: 26
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-1360-2357
EISSN: EISSN-1573-7608
Available Date: 2025-02-26
Can Student Accurately Identify Artificial Intelligence Generated Content? An Exploration of AIGC Credibility from User Perspective in Education
Yulu Cui1; Hai Zhang2
Education and Information Technologies, v30 n12 p16321-16346 2025
With the development of artificial intelligence technology, it has become increasingly difficult to distinguish between Artificial Intelligence Generated Content (AIGC) and non-AIGC. Inaccuracies in identifying AIGC in higher education may lead to academic misconduct and risks, and the credibility of AIGC is also subject to certain doubts. Users are the direct perceivers of AIGC, and winning their trust is the goal of AI applications. Therefore, exploring the credibility of AIGC holds positive value in higher education. This study designed three specific tasks and collected data from students majoring in educational technology at a normal university through questionnaires. The findings indicate that students only have a 70% success rate in identifying AIGC, and the recognition rate for domain-specific AIGC content may be even worse, with only 60%. Finding also indicated that perceived technological acceptance is the primary factor influencing AIGC credibility and behavioral adoption. Students may also experience AI illusions during AIGC usage, leading to overreliance. This research provides reliable evidence for assessing AIGC credibility in higher education, enhancing students' cognition and application abilities regarding AIGC, and offering insights into promoting effective use of AIGC.
Descriptors: Artificial Intelligence, Technology Uses in Education, Educational Technology, Identification, Student Attitudes, Computer Attitudes, Accuracy, Credibility, College Students, Information Literacy, Computer Literacy
Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link-springer-com.bibliotheek.ehb.be/
Publication Type: Journal Articles; Reports - Research
Education Level: Higher Education; Postsecondary Education
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A
Author Affiliations: 1Xinyang Normal University, Xinyang, China; 2Northeast Normal University, Changchun, China

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