The Implementation of Deep Reinforcement Learning in E-Learning and Distance Learning: Remote Practical Work

The world has seen major developments in the field of e-learning and distance learning, especially during COVID-19 crisis, which revealed importance these two types education fruitful benefits they have offered a group countries, those that excellent infrastructure. At Faculty Sciences Semlalia, Cadi Ayyad University Marrakech, Morocco, we created simple electronic platform for remote practical work (RPW), its results been good terms student interaction even facilitating employment professor. objective this is to propose recommendation system based on deep quality-learning networks (DQNs) recommend direct students advance doing RPW according their skills each mouse or keyboard click per student. We are focusing technology because it strong, tremendous visibility problem-solving ability will demonstrate result section. Our enabled us collect range students’ teachers’ information interactions with learning content rely as inputs (a large number images second student) into our new output (doing RPW). This technique reflected an attempt embody virtual teacher’s image within then adequately trained DQN perform RPW.