Engineering students' perceptions and actual use of AI-based math tools for solving mathematical problems - Kimberly F. Garcia; Ardvin Kester S. Ong; Ma. Janice J. Gumasing; Cesar Romeo V. Delos Reyes (Acta Psychologica)
The immediate advancement of AI technologies as educational technology revolutionized the learning environment of students; contributing to their academic performance will require an understanding of the factors that influenced the acceptance of AI tools. Insufficient studies were seen from literature review that focused on the integrated factors that influenced the perception of acceptance and actual usage of AI-based math tools among engineering students. The objective of this study was to evaluate the variables that influenced the engineering students' perceptions of adoption and actual academic use of AI-based math tools as academic assistance. This study identified the determinants of behavioral, technology use, and motivation by utilizing the higher-order Unified Theory of Acceptance and Use of Technology (UTAUT3), self-determination theory, and the variable trust to examine the behavioral intention influencing adoption of AI tools. A total of 565 valid respondents were analyzed through purposive sampling using structural equation modeling. The results revealed that hedonic motivation, perceived competence, performance expectancy, and habit are the most significant indicators of both students' behavioral intentions and actual use of AI-based math tools. The outcome indicated that students are more inclined to utilize AI tools when they find them engaging and are convinced that they can employ them efficiently and incorporate the tools in their academic routines. From the result, perceived autonomy was deemed insignificant to behavioral intentions, suggesting that students utilize AI tools for functionality and benefits in their academic performance rather than the adaptability of the tools. The outcome of the study may be considered evaluating the behavioral intention and adoption of the students towards innovative AI tools. The results in this study could be extended and applied to the assessment of factors in educational technology studies. Proper ethical use, managerial implications, and theoretical contributions were also discussed after obtaining the output of this study – deeming AI math tools as guide and resource among students and not as a substitute for solutions on mathematical problems.