Student Perceptions and Preferences in Personalized AI-driven Learning
Student Perceptions and Preferences in Personalized AI-driven Learning
Author(s): Marta Slepankova, Kristýna Kiliánová, Petra Kočková, Kateřina KOSTOLÁNYOVÁ, Martin Kotyrba, Hashim HabiballaSubject(s): Education, Psychology, Higher Education , ICT Information and Communications Technologies, Socio-Economic Research
Published by: Vysoká škola ekonomická v Praze
Keywords: AI-personalized learning; AI-driven learning; Artificial intelligence; Personalized learning; Student perception;
Summary/Abstract: This study analyzed university students' attitudes and preferences towards AI-driven personalized learning. A mixed-method approach, combining quantitative and qualitative data collection through a questionnaire survey, was employed among 270 students at the University of Ostrava. Findings indicate that 64.1% of students perceived AI-generated and adapted chapters as more helpful and effective than traditional study materials, valuing content adaptability, real-time feedback, and increased motivation. However, 18.1% viewed AI-driven instruction as less beneficial, citing limited interactivity, lack of detailed feedback, and insufficient customization for advanced learners. The research confirmed that AI-driven personalized learning offers benefits but faces challenges regarding interactivity and feedback depth. Development of interactive features, improved analytical feedback, and thoughtful AI integration with traditional pedagogy are crucial for enhancing effectiveness and broader implementation.
Journal: Acta Informatica Pragensia
- Issue Year: 14/2025
- Issue No: 2
- Page Range: 261-271
- Page Count: 11
- Language: English
