Integration and assessment of streaming video content and API development into a spaced repetition service

Abstract: There are a lot of spaced repetition system based online learning services available nowadays, but none of them are popular or widely accepted as a good means for studying. The problem of these services is, instead of exploiting and utilizing the possibility of modern technology, they simply brought this old school learning method to the web as an application with exactly the same experience as one could have with textbooks and flash cards. This master’s thesis project concerns Sharplet, a spaced repetition system based web service, who is trying to stand out by offering some features that none of the other comparable services have. One of these features is the integration of YouTube video clips, so that in addition to text and pictures, study materials may now include both audio and video material. This thesis begins by reviews spaced repetition systems in general, and then focuses on some of the existing services and how to provide a better service. Next the thesis describes the design, implementation, and evaluation of a new service that includes both audio and video content. The main practical result of this master’s thesis project is a working prototype audio and video enabled spaced repetition based service. Unfortunately, the actual performance of this prototype is unacceptable, hence there is a need to improve its performance before it can be integrated with the production spaced repetition system.