Generative AI use and self-learning in higher education: the role of learning difficulties - Saleh, Dana; ElSayary, Areej (Frontiers in Education, 2026)
The rapid development of GenAI tools and their adoption in education have shown promising potential to personalize learning experiences. However, their effectiveness is influenced by factors such as familiarity, frequency of use, and the impact on self-learning. This study investigates the undergraduate students' familiarity with Generative AI (GenAI) tools, their frequency of use, and the perceived impact of GenAI on self-learning, with particular consideration of differences between students with and without learning difficulties. Prompt engineering is also included as a secondary aspect of students' GenAI experience. The research employed a quantitative survey design, utilizing validated scales to measure familiarity, usage experience, and perceived learning impact. Reliability and validity of the measurement model were established using Confirmatory Composite Analysis in SmartPLS. The study involved undergraduate students (N = 78) enrolled in GenEd courses, aged 17–21 (M = 18.5, SD = 0.86). Descriptive results showed that students reported low to moderate familiarity with GenAI tools, but they frequently engaged with them for academic purposes. Despite limited formal training, most participants rated the impact of GenAI on their self-learning positively, particularly in terms of communication skills, time efficiency, and confidence. A smaller portion of students indicated negative impacts, reflecting concerns about over-reliance and reduced critical engagement. Structural modeling further demonstrated significant positive relationships between GenAI familiarity, frequency of use, and perceived impact. These findings highlight a pattern of utility-driven adoption, in which students benefit from GenAI despite having a limited foundational understanding. The study highlights the importance of institutions strengthening AI literacy, providing structured pedagogical guidance, and integrating GenAI responsibly to support meaningful and ethical learning practices.