A NEW PARADIGM IN EDUCATION: ARTIFICIAL INTELLIGENCE-ENHANCED PERSONALIZED LEARNING
The importance of Artificial Intelligence (AI) in modern times cannot be overstated, as it has become a transformative force across nearly every aspect of society. AI is playing an increasingly important role in education, transforming traditional methods of teaching and learning toward more personalized, adaptive approaches. This paper offers an in-depth examination of AI in the educational sector, highlighting the importance of personalized learning and the role of educational technology. AI-enhanced personalized learning utilizes advanced technologies to customize educational content for each student. By adjusting the pacing of lessons, AI ensures that students learn at a speed that suits their individual progress. It provides real-time feedback tailored to the unique needs, preferences, and cognitive abilities of each learner, enhancing their overall educational experience. This transformation holds great promise in significantly enhancing student engagement. By providing personalized content and immediate feedback, it encourages deeper involvement, motivating students to take an active role in their education. Additionally, this shift has the potential to improve academic performance by addressing individual learning needs. Ultimately, AI-powered personalized learning systems foster a more engaging, adaptive, and efficient educational environment. However, the widespread implementation of AI in education presents challenges, including ethical concerns. This paper explores the potential benefits and challenges of AI-powered personalized learning systems, emphasizing the need for guidelines for responsible AI implementation in education. The findings suggest that with careful planning and ethical consideration, AI can significantly enhance educational outcomes, offering a more inclusive and effective learning environment for diverse student populations.
Authors
- Salih Uǧur (ORCID: https://orcid.org/0000-0002-8810-8141)
Institutions
- Niğde Ömer Halisdemir Üniversitesi (TR)
Publication Details
- Journal
- Advanced Linguistics
- Published
- 2025-06-27
- DOI
- https://doi.org/10.20535/.2025.15.327338
- Citations
- 1
- Primary Topic
- Online Learning and Analytics
- Type
- article
- Field-Weighted Citation Impact
- 1.69