A Tool for the Semantic Analysis and Recommendation of Videos in e-Learning

Video lessons are increasingly adopted in education, especially in universities and lifelong learning projects. Their popularity is due to the people's familiarity with video and to other intrinsic characteristics of this medium, such as the message rapidity and its reproducibility. Accordingly, Massive Open Online Courses are gaining a prominent role in both formal and informal education and many universities provide video courses for their students through suited platforms or even freely accessible to everyone. To improve the effectiveness of video lessons and to make them part of a wider learning environment, we decided to investigate the possibility of making a system that, starting from a video, can suggest further “readings”. Such a system is thought for independent lifelong learners, for regular students, for teachers and instructional designers as well.