What Drives Students' AI Learning Behavior: A Perspective of AI Anxiety

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Bibliographic Details
Title: What Drives Students' AI Learning Behavior: A Perspective of AI Anxiety
Language: English
Authors: Yu-Min Wang (ORCID 0000-0002-2096-6801), Chung-Lun Wei, Hsin-Hui Lin, Sheng-Ching Wang, Yi-Shun Wang (ORCID 0000-0002-0161-5520)
Source: Interactive Learning Environments. 2024 32(6):2584-2600.
Availability: Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals
Peer Reviewed: Y
Page Count: 17
Publication Date: 2024
Document Type: Journal Articles
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: Learning Processes, Artificial Intelligence, Anxiety, Employment Opportunities, Learning Motivation, Self Efficacy, Student Surveys, Student Attitudes, Foreign Countries, Intention, Social Media, College Students, Technology Education
Geographic Terms: Taiwan
DOI: 10.1080/10494820.2022.2153147
ISSN: 1049-4820
1744-5191
Abstract: As artificial intelligence (AI) technology rapidly develops and is deployed, students increasingly need to understand and learn AI-related skills for future employment. This study investigates how students' AI learning anxiety and AI job replacement anxiety affect intrinsic/extrinsic learning motivations and subsequent AI learning intention. The moderating effect of learning self-efficacy is also examined. An online survey instrument collected data from a sample of students in Taiwan, and partial least-squares structural equation modeling (PLS-SEM) technique was employed to test the proposed model. The results indicate AI learning anxiety negatively affects learning motivations, but AI job replacement anxiety has a positive impact on extrinsic motivation. Learning self-efficacy and intrinsic/extrinsic motivations positively affect learning intention. Learning self-efficacy positively moderates the influence of intrinsic learning motivation on student AI learning intention but negatively moderates the influence of extrinsic learning motivation on student AI learning intention. The findings highlight the importance of AI anxiety and can be used to guide course design in an AI learning setting.
Abstractor: As Provided
Entry Date: 2024
Accession Number: EJ1439579
Database: ERIC
Description
Abstract:As artificial intelligence (AI) technology rapidly develops and is deployed, students increasingly need to understand and learn AI-related skills for future employment. This study investigates how students' AI learning anxiety and AI job replacement anxiety affect intrinsic/extrinsic learning motivations and subsequent AI learning intention. The moderating effect of learning self-efficacy is also examined. An online survey instrument collected data from a sample of students in Taiwan, and partial least-squares structural equation modeling (PLS-SEM) technique was employed to test the proposed model. The results indicate AI learning anxiety negatively affects learning motivations, but AI job replacement anxiety has a positive impact on extrinsic motivation. Learning self-efficacy and intrinsic/extrinsic motivations positively affect learning intention. Learning self-efficacy positively moderates the influence of intrinsic learning motivation on student AI learning intention but negatively moderates the influence of extrinsic learning motivation on student AI learning intention. The findings highlight the importance of AI anxiety and can be used to guide course design in an AI learning setting.
ISSN:1049-4820
1744-5191
DOI:10.1080/10494820.2022.2153147