Naranjo-Zolotov, Mijail JuanovichFranco, Joana Vala Pires2025-06-272025-06-26http://hdl.handle.net/10362/184555Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Business IntelligenceStudent absenteeism remains a persistent issue in higher education, now further influenced by the increasing integration of artificial intelligence (AI) into academic contexts. Tools like ChatGPT and adaptive learning platforms provide students with increased flexibility and personalized support, potentially decreasing the perceived necessity of attending face-to-face classes. Although previous studies have addressed behavioural and psychological aspects of absenteeism, little attention has been given to the interaction between these factors and AI usage. This research bridges that gap by proposing a comprehensive framework that combines locus of control, self-efficacy, and digital displacement theories to examine how AI impacts student attendance and autonomous learning behaviours. A quantitative survey was conducted with 291 university students in Portugal, and the data were analysed using partial least squares structural equation modelling (PLS-SEM). The validated model accounts for 38.7% of the variance in absenteeism and 34.4% in self-efficacy for independent learning. Results show that internal locus of control, peer influence, time management skills, and AI tool usage significantly affect both constructs. This study offers valuable insights into the behavioural dynamics of absenteeism and independent learning in AI-supported educational settings, with implications for educational institutions and policymakers navigating AI’s growing presence in academia.engArtificial intelligenceStudent absenteeismIndependent learningSelf-efficacyLocus of controlDigital displacementSDG 4 - Quality educationSDG 9 - Industry, innovation and infrastructureSDG 10 - Reduced inequalitiesmaster thesis203968972