(untitled) (OCEM Journal of Management, Technology & Social Sciences, 2026)
This study used a convergent parallel mixed-methods design to examine at how generative Artificial Intelligence (AI) is reshaping educational practices, however there is limited evidence regarding its impact on students’ learning outcomes, especially in developing countries. This study further examined the relationships among AI-related skills, perceived usefulness, self-efficacy, motivation, and academic performance, as well as students’ experiences with generative AI in learning environments. Applying a survey design, this research collected survey data from two hundred ninety-nine ( N = 299) students in Nepal, Indonesia, and Brazil. This study also conducted semi-structured interviews with fourteen ( N = 14) interviewees. Quantitative results indicated low levels of AI literacy, self-efficacy, perceived usefulness, and motivation, all averaging means below midpoint scores of five point Likert scale of survey variables. Regression analyses revealed weak correlations between those independent variables and reported academic enhancement, suggesting that students often lack the confidence and skills required to integrate AI tools effectively into their learning activities. Conversely, qualitative results highlighted significant advantages of generative AI, such as improved learning efficiency, enhanced communication, and greater problem-solving capabilities. Interviewees noted that AI tools simplified complex concepts and saved time, despite receiving limited formal training. The integration of quantitative and qualitative results exposed a perception practice gap: while students benefited from generative AI, they generally underestimated their abilities and lacked structured guidance. The study concludes that successful AI integration in education required more than mere access to technology; it requires fostering AI literacy, self-efficacy, motivation, and ethical awareness through dedicated pedagogical support.