{"title":"The Role of Individual Capabilities in Maximizing the Benefits for Students Using GenAI Tools in Higher Education.","authors":"Jia Qi, Ji'an Liu, Yanru Xu","doi":"10.3390/bs15030328","DOIUrl":null,"url":null,"abstract":"<p><p>Although the adoption and benefits of GenAI (Generative Artificial Intelligence) tools among higher education students have been widely explored in existing studies, less is known about how individual capabilities influence the use of these tools. Drawing on the Information System Success Model (ISSM) and the Expectation-Confirmation Model (ECM), this study examines how students' capabilities, including critical thinking, self-directed learning ability, and AI literacy, impact the quality of information obtained from GenAI tools. Additionally, it explores the relationships among information quality, student satisfaction, and the intention to continue using GenAI tools in higher education. Survey data from 1448 GenAI tools users in Chinese universities reveal that students with stronger capabilities tend to extract higher-quality information, which in turn fosters their satisfaction with GenAI tools and the intention to continue using these tools. The findings highlight the crucial role of individual capabilities in maximizing the potential of GenAI tools, and it emphasizes the need to cultivate students' critical thinking, self-directed learning ability, and AI literacy to achieve sustainable success in the GenAI era. Theoretically, this study extends the ISSM and ECM by exploring the impact of students' capabilities and the mediating role of user satisfaction between information quality and the intention to continue using GenAI tools. Practically, this study provides implications for educators and policymakers to enhance students' capabilities, thus maximizing the potential benefits of GenAI tools in higher education.</p>","PeriodicalId":8742,"journal":{"name":"Behavioral Sciences","volume":"15 3","pages":""},"PeriodicalIF":2.5000,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11939294/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Behavioral Sciences","FirstCategoryId":"102","ListUrlMain":"https://doi.org/10.3390/bs15030328","RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"PSYCHOLOGY, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
Although the adoption and benefits of GenAI (Generative Artificial Intelligence) tools among higher education students have been widely explored in existing studies, less is known about how individual capabilities influence the use of these tools. Drawing on the Information System Success Model (ISSM) and the Expectation-Confirmation Model (ECM), this study examines how students' capabilities, including critical thinking, self-directed learning ability, and AI literacy, impact the quality of information obtained from GenAI tools. Additionally, it explores the relationships among information quality, student satisfaction, and the intention to continue using GenAI tools in higher education. Survey data from 1448 GenAI tools users in Chinese universities reveal that students with stronger capabilities tend to extract higher-quality information, which in turn fosters their satisfaction with GenAI tools and the intention to continue using these tools. The findings highlight the crucial role of individual capabilities in maximizing the potential of GenAI tools, and it emphasizes the need to cultivate students' critical thinking, self-directed learning ability, and AI literacy to achieve sustainable success in the GenAI era. Theoretically, this study extends the ISSM and ECM by exploring the impact of students' capabilities and the mediating role of user satisfaction between information quality and the intention to continue using GenAI tools. Practically, this study provides implications for educators and policymakers to enhance students' capabilities, thus maximizing the potential benefits of GenAI tools in higher education.