Development of Intelligent Systems to Support Academic Staff in the Teaching Process

This study focuses on the development of intelligent systems designed to support academic staff in the teaching process by improving instructional planning, assessment, and feedback. A mixed-methods approach was employed, encompassing system design, implementation, and pilot testing with university educators. The results revealed gains in efficiency, personalized instructional guidance, and enhanced decision-making capabilities. The findings emphasize the potential of intelligent systems to optimize teaching practices, alleviate administrative workload, and foster data-driven educational strategies, thereby contributing to more effective and adaptive learning environments.