Management of AI-Based Education Data to Optimize the Learning Process - Oci, Markus; Na, Li; Hui, Zhou (Al-Hijr: Journal of Adulearn World, 2025)
The rapid advancement of artificial intelligence (AI) technologies has led to their growing integration in educational systems, promising to revolutionize the learning process. AI has the potential to optimize learning by personalizing educational experiences, improving decision-making, and enhancing the management of educational data. However, despite these advancements, there is still a lack of systematic approaches to managing AI-based education data in a way that can consistently optimize the learning process. This study aims to explore how AI-based education data management can enhance the learning process by improving data-driven decision-making, student engagement, and performance tracking. A mixed-methods research design was used, combining qualitative case studies and quantitative data analysis. The study involved analyzing AI-driven data management tools used in several educational institutions to optimize learning outcomes. Surveys, interviews, and data analysis were used to evaluate the effectiveness of these tools in real-world educational settings. The results indicate that AI-based data management tools significantly enhance the learning process by providing real-time feedback, personalized learning paths, and better resource allocation. Educators and students reported increased engagement and improved learning outcomes due to the use of AI-powered tools. This study concludes that effective management of AI-based education data is essential for optimizing the learning process. Educational institutions should prioritize the integration of AI-driven data systems to maximize learning outcomes and efficiency.