2025/10/25 by Xi Cheng, Yuansheng Huang, Zhang Weixiao +2 · 1 voice
Computer Science · Medicine · #Artificial Intelligence in Healthcare and Education #Intelligent Tutoring Systems and Adaptive Learning #Online Learning and Analytics
paper · pdf · doi:10.70389/pjs.100141
openalex publication_date 2025/10/25 · openalex created_date 2025/10/30 · openalex updated_date 2026/07/21
The aim is to evaluate the effectiveness of generative artificial intelligence (GAI) in enhancing student engagement, personalising learning, and improving teaching practices. A mixed-methods approach was employed, including surveys with 200 students and 50 teachers, semi-structured interviews, and classroom observations. The survey measured the extent of GAI integration, its perceived benefits, and challenges faced by both students and teachers. Interviews provided in-depth insights into the experiences of educators, while classroom observations assessed GAI’s impact on teaching and learning. The results indicated that 65% of students rated GAI integration as high, particularly in information technology and natural sciences courses. Teachers reported enhanced feedback and more dynamic interactions with students. However, challenges related to teacher training, technical issues, and ethical concerns were identified. GAI was particularly successful in adaptive learning tools, such as automatic code checking in IT and virtual models in science courses. In conclusion, GAI has the potential to transform educational processes by personalising learning and enhancing student-teacher interactions. However, its successful integration requires addressing issues such as teacher preparedness, technical infrastructure, and ethical standards. The findings suggest that educational institutions must invest in proper training and support systems to maximise the benefits of GAI in higher education.