Analysis of learning in Moroccan secondary education: computer model and data-driven pedagogy

Research in Moroccan secondary education highlights the underexploited potential of learning analytics to personalize instruction despite rapid digital transformation. A computational model is proposed to translate student digital interaction data into actionable insights for non-technical educators, focusing on key indicators like engagement and academic achievement, thereby supporting data-driven pedagogical approaches.

This development is crucial for integrating advanced analytical capabilities into educational systems, enabling more personalized and effective learning experiences. By empowering non-technical educators with data-driven insights, institutions can enhance operational efficiency and improve student outcomes in an increasingly digital landscape.

Learning analytics holds significant potential for personalizing instruction and improving teaching practices within educational contexts undergoing digital transformation.

Forward consideration, not a verified fact.