IJBLEIJBLE

International Journal of Business, Law, and EducationInternational Journal of Business, Law, and Education

This research explores factors influencing university students satisfaction and intention to continue using AI-based applications. By analyzing the roles of perceived ease of use, usefulness, and risk, the study assesses how these elements drive technology engagement and the extent to which perceived risk moderates user experience. A survey was administered to 210 university students within a quantitative research framework. Findings reveal that perceived usefulness and ease of use drive continuance intention, with satisfaction mediating this relationship. However, perceived risk showed no significant effect, challenging previous empirical evidence that emphasizes its role as a key moderator in technology adoption. The study concludes that improving the functionality and usability of AI tools is key to driving student persistence. Given that perceived risk plays a less significant role than previously theorized, institutions should focus on promoting user-friendly, impactful AI solutions to maximize technology integration and sustained use.

The study demonstrates that perceived usefulness and ease of use significantly influence students intention to continue using AI-based applications.Satisfaction plays a crucial mediating role in this relationship, highlighting its importance in driving sustained technology engagement.Contrary to previous research, perceived risk did not significantly impact continuance intention, suggesting that students prioritize the benefits and usability of AI tools over potential risks.Therefore, institutions should prioritize developing and promoting user-friendly and impactful AI solutions to maximize technology integration and sustained use among students.

Future research should broaden the sample to include students from diverse regions and institutions to achieve a more comprehensive understanding of AI acceptance. Further studies could explore additional determinants influencing technology adoption, such as trust in technology or specific AI application features. Additionally, investigating the long-term effects of AI integration on student learning outcomes and skill development is crucial. Exploring the ethical implications of AI use in education, including issues of bias and data privacy, is also warranted. Finally, research should focus on developing pedagogical strategies that effectively integrate AI tools into the curriculum to enhance student learning experiences and prepare them for the future workforce, ensuring that AI is used responsibly and equitably to support educational goals.

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