Integrating Artificial Intelligence in Personalized Learning: A Future-Oriented Approach to Enhance Student Engagement and Achievement - Ibrahim bin Salem (International Journal of Post Axial: Futuristic Teaching and Learning, 2024)
This study explores the integration of Artificial Intelligence (AI) in personalized learning and its impact on student engagement and achievement. Utilizing a qualitative research design, specifically a case study approach, we gathered data through in-depth interviews, participant observations, and document analysis involving students and teachers from various educational levels. The findings reveal that AI tools significantly enhance personalized learning by customizing learning paths, providing real-time feedback, and facilitating differentiated instruction. Students reported increased engagement and improved academic performance due to the interactive nature and adaptive capabilities of AI-driven platforms. Teachers highlighted the importance of professional development and support to effectively implement these technologies. However, challenges such as technical issues, data privacy concerns, and the steep learning curve associated with new AI tools were also identified. Despite these limitations, participants were optimistic about the future potential of AI in education and suggested improvements for better curriculum integration and user-friendly interfaces. The study emphasizes the need for robust technical infrastructure, clear ethical guidelines, and continuous innovation to maximize the benefits of AI in personalized learning. The implications of these findings suggest that AI has the potential to transform educational practices by creating more engaging, effective, and individualized learning experiences. Future research should focus on addressing the identified challenges and exploring the long-term impacts of AI integration in diverse educational contexts.