DIGITAL LIBRARY
EXAMINING FACTORS AFFECTING STUDENTS’ PREPAREDNESS FOR AI TECHNOLOGY
1 National Yunlin University of Science and Technology, Department of Information Management (TAIWAN)
2 National Yunlin University of Science and Technology, Bachelor Program in Business and Management (TAIWAN)
About this paper:
Appears in: INTED2024 Proceedings
Publication year: 2024
Page: 2562 (abstract only)
ISBN: 978-84-09-59215-9
ISSN: 2340-1079
doi: 10.21125/inted.2024.0710
Conference name: 18th International Technology, Education and Development Conference
Dates: 4-6 March, 2024
Location: Valencia, Spain
Abstract:
Artificial intelligence (AI) technology has expanded the scope of education and reshaped the information and abilities that individuals require to live well and work efficiently. Achieving students’ AI technology preparedness for a future with AI has always been an objective of technology education initiatives. Prior studies have demonstrated that their technological readiness level significantly influences students’ desire to learn new technologies. Despite the allure of AI technology, its potential benefits will remain unrealized until students adopt and utilize new AI technology. In particular, one way to conceptualize AI technology readiness is as a general mental state. This is a crucial factor in determining whether or not AI applications are used to mediate students’ learning. Students who are highly prepared for AI technology are more likely to participate in AI technology-assisted learning activities and pursue careers in AI technology. Nevertheless, little study has been done so far on students’ technological preparedness for AI or the factors that influence it. Few studies have been offered to test and assess students’ AI technology preparedness in the context of university commerce and management education despite the importance of AI education programs. To close this research gap, this research aims to identify the variables influencing students’ preparedness for AI technology. Three research propositions are presented in this study: first, that there is a positive correlation between AI self-efficacy and AI technology readiness; second, that there is a negative correlation between anxiety regarding AI and preparedness for AI technology; and third, that there is a positive correlation between perceived learning effectiveness and preparedness for AI technology. A framework for comprehending the variables influencing students’ preparedness for AI technology is provided by this study. The proposed propositions are anticipated to advance future studies on AI education in the context of commerce and management education at universities.
Keywords:
Artificial intelligence, Technology readiness, Learning effectiveness, AI education, University commerce and management education.