Abstract
The integration of the resources of massive open online courses (MOOCs) for the learning process is crucial. The power of the Internet and big data analysis technology brings the ultimate benefits for learners. With the help of the recommendation systems (RSs), the complexity in finding the needed learning materials is limited. MOOCs-based RSs provide suggested quality of courses to learners. Recently Deep Learning techniques have evolved to enhance MOOC's course recommendation results. This survey investigated different deep learning techniques in MOOCs for course recommendation due to the high performance and significant performance of these special types of neural network algorithms. This survey contributes to the field of MOOC's recommendation systems by overviewing the current research trends and the use of different deep learning models with MOOCs recommendation systems. Literature in the utilization of deep course recommendation systems is promising and outperforms the traditional recommendation techniques. (C) 2021 INT TRANS J ENG MANAG SCI TECH.