An Assessment of Student-Researcher Satisfaction with the Use of Artificial Intelligence in Thesis Writing

Jena Mae  Fatagani-valerio,; Jay Renee  Valerio,; Jonalyn  Balancio,; Jonald  Pimentel,

An Assessment of Student-Researcher Satisfaction with the Use of Artificial Intelligence in Thesis Writing

Jena Mae Fatagani-valerio | Jay Renee Valerio | Jonalyn Balancio | Jonald Pimentel

Abstract:

The rapid advancement of artificial intelligence (AI) and its increasing integration into academic workflows necessitate a deeper understanding of its impact on student learning and experience. This research explores the use of AI tools in undergraduate thesis writing, focusing on student satisfaction and the factors influencing student perceptions. By examining the experiences of 121 students (83 BSIT, 38 BTVTEd) at Sultan Kudarat State University, this research contributes to the growing body of knowledge on the role of AI in higher education. Overall satisfaction with AI tools was generally high. However, a more nuanced analysis revealed no significant differences between BSIT and BTVTEd students across various satisfaction measures (overall satisfaction, ease of use, enjoyable experience), as indicated by Mann-Whitney U tests. Lower ratings for reliability, interface, and validity/plagiarism, however, suggest areas for tool improvement, despite high ratings for usability, functionality, features, and performance. A linear regression analysis, exploring the correlation between satisfaction and thesis outcomes, yielded a low R-squared (0.0512), indicating limited explanatory power. Surprisingly, a significant negative correlation emerged between thesis organization and overall satisfaction, warranting further investigation. Other thesis outcome measures showed no significant relationship with satisfaction. These findings highlight the need for further research to identify additional factors influencing satisfaction and to explore the unexpected negative correlation, potentially through qualitative methods. This research contributes valuable insights into student experiences with AI in thesis writing, informing future tool development and pedagogical approaches

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