Generative artificial intelligence (GenAI) has the potential to significantly impact educational practices. Despite the apparent increase in the adoption among students, empirical research on understanding AI use and acceptance among university students is scarce. To address this gap, this study employed an extended technology acceptance model (TAM) incorporating subjective norms, perceived enjoyment, self-efficacy, and compatibility with 943 undergraduate students from 140 universities across Turkey. Findings revealed that attitude toward use, perceived usefulness, self-efficacy, and compatibility significantly predicted behavioral intention to use GenAI tools. Notably, subjective norms had a limited influence on students’ intentions to use GenAI tools, challenging traditional assumptions about social pressures in technology adoption. These insights highlight that students prioritize personal perceptions over social influences in adopting GenAI technologies. Theoretically, the study provides insights into the proposed extended TAM, by validating it in a unique socio-cultural context. Practically, the study provides recommendations on how to foster acceptance of GenAI by enhancing the usability, compatibility, and enjoyment of GenAI tools while addressing potential perceived risks and ethical concerns. The study contributes to understanding GenAI’s role in education, providing a foundation for future investigations into additional factors influencing the use and acceptance of GenAI tools in higher education settings.

FATİH Projesi Üzerine Yapılan Akademik Çalışmaların İçerik Analizi

Emotions play a significant role in shaping technology adoption decisions, influencing not only perceptions but also behavioural intentions. In this study, we investigated the structural relationships among online learning self-efficacy, positive and negative emotions, perceived ease of use, perceived usefulness and behavioural intention in the context of learning management system (LMS) use and acceptance. Using the technology acceptance model and control-value theory as theoretical frameworks, we tested two research models using data collected from 216 pre-service teachers enrolled in teacher education degree programmes in Turkey. The results revealed that online learning self-efficacy had a positive direct effect on positive emotions, perceived ease of use, perceived usefulness and behavioural intention as well as a negative direct effect on negative emotions. Positive emotions significantly contributed to behavioural intention, whereas negative emotions showed no significant effect, potentially due to the context of mandatory use of the LMS. The findings underscore the importance of fostering positive emotional experiences and enhancing online learning self-efficacy to promote effective LMS adoption. The study makes a novel contribution by integrating class-related achievement emotions into the technology acceptance model framework alongside online learning self-efficacy. Future research should explore the interplay of emotions and cognitive evaluations in diverse contexts, particularly voluntary versus mandatory technology use. Implications for practice and policy: To enhance LMS acceptance and use, we recommend incorporating features in LMS design that foster positive emotions such as pride, enjoyment and hope. Teacher education programmes should offer practical training and support to help students build confidence in using LMSs, which can also enhance their emotional engagement. Universities and policymakers should provide training for instructors on how to create supportive, confidence-building LMS environments for students.

Information technologies are an indispensable part of modern business, education, and personal lives. However, the COVID-19 pandemic has shown everybody around the world the insufficiency of available information technology infrastructures and the importance of establishing strong infrastructures for citizens from all backgrounds and geographic locations. The challenge has been especially hard for educational institutions because very few were truly prepared for an emergency transition to distance education. This chapter aims to explain the main components of a modern university information technology infrastructure and offer guidance in establishing a strong infrastructure for sustainable quality education.