Artificial Intelligence (AI) is transforming modern education by enhancing how students learn, develop, and prepare for their careers. This study reviews recent research to explore how five core AI technologies—machine learning, natural language processing (NLP), robotics, expert systems, and computer vision—support higher education. A qualitative content analysis of academic sources was used to examine practical applications and outcomes for students. Machine learning helps personalise education by predicting student performance, recommending resources, and automating feedback. NLP enhances communication through virtual tutors, instant feedback, and language translation, promoting inclusive learning environments. Robotics enables hands-on experience, supporting technical skills and interdisciplinary learning. Expert systems simulate human decision-making, aiding in diagnostics, planning, and academic advising. Meanwhile, computer vision improves lab-based learning, supports virtual reality applications, and allows remote monitoring. Despite these benefits, challenges such as data privacy, algorithmic fairness, and the need for teacher training remain. NLP stands out as the most impactful technology due to its wide use and adaptability in educational contexts. The study concludes that integrating AI ethically and strategically can create more engaging, personalised, and future-ready education systems. Educators and policymakers are encouraged to focus on scalable AI tools while ensuring that human values remain central to learning. Continued research and collaboration across disciplines will be vital to fully harness AI’s potential in education.

artificial intelligence, university students, natural language processing

biology

Presentation: poster