A Study on the Recommendation Method of Digital Media Courses on Universities Based on Student Portraits

With the development of Internet + education, traditional teaching can no longer meet the needs of students. We use big data portrait technology to dig into the learning pattern, learning effect and group characteristics of learners, and use course recommendation to recommend courses for students. Finally, through the combination of online learning and traditional teaching, a concrete case of blended teaching is established to test the learning effect of students. The practical results show that by establishing student portraits can accurately provide services for students' personalized development and provide new models, new means and new paths for students' scientific management.