Problem Tagging and Solution-Based Video Recommendations in Learning Video Environments

Learning in the 21st century has a quite bigger dimension regarding learning techniques than years before. Specifially, digitization enables new possibilities such as interactive learning platforms, which are often applied in distance education or distributed learning. But regardless of the source of learning, there is still a major problem - what do we do if we do not understand the content of a learning source at a specific point? Learning is a continuous process that by no means always runs smoothly. Every learner encounters learning obstacles during the learning process, which on the one hand prolong the process and on the other hand complicate or even terminate it. To remove such obstacles, supervised learning is needed, which is easier in a digital environment. In this work, an approach is presented to remove such obstacles in a learning video environment. This paper has two main contributions: first, an approach to solve this typical problem in a learning video environment by tagging problematic positions to provide additional information regarding the specific problem; and second, an extension of the approach to socialize such an learning environment by using problem tagging to recommend learning videos regarding a specific problem, recommended by other learners, to speed up and facilitate the learning process for each learner.