Problem tagging and solution-based video recommendations in learnign video environments
Autor: Alexander Lehmann
Abstract— Learning in the 21st century has a quite bigger dimension regarding to learning-techniques than years before. Especially the digitization enables new possibilities for example interactive learning platforms which are often applied in the distance education or distributed learning [1]. 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 his learning process, which on the one hand prolong the process and on the other hand complicate or even terminate it. To remove such obstacles, an observed learning is needed, which is more easily in a digital environment. Thus, 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 to a specific problem, recommended by other learners to additional speed up & facilitate the learning process of each learner.
