Abstract:
Numerous chances for individualized learning experiences arise from this, especially when it comes to customizing course material to suit the interests and learning styles of students. To evaluate and improve course delivery, instructors may now use analytics and reports from learning management systems, which offer quantitative data. However, it takes a lot of time and effort to manually analyze this data to find trends and improve the course contents regularly. By combining deep learning techniques with learning management systems, this procedure can be automated, enabling the creation of intelligent course materials with high accuracy and eliminating the need for manual intervention. To predict and improve learning outcomes at scale, a deep learning model is proposed in this research, with an analysis of the factors affecting the application of deep learning in Azerbaijani education. Adopting such a model might lower development and maintenance costs, lessen risks, and improve communication among the parties involved in Azerbaijan’s educational system.
