A Proposal of Educational Video Gamification as a Service - Moraes, Daniel de Sousa; Guedes, Álan L. V.; Busson, Antonio J. G.; Soares Neto, Carlos de Salles; Colcher, Sérgio (Anais Estendidos do Simpósio Brasileiro de Sistemas Multimídia e Web (WebMedia), 2019)
Online and hybrid courses are characterized by the use of technologies teaching support and student-centered methodologies. In particular, the use of content authoring, storage, distribution, and presentation technologies has contributed to the emergence of Virtual Learning Environments (VLEs), such as Moodle, and MOOCS (Massive Open Online Course), such as EdX. However, those types of courses still suffers from problems involving student engagement. To improve this engagement, this article discusses the proposal of a Deep Learning as a Service (DLaS) called EVGAS (Educational Video Gamification As a Service). More precisely, EVGAS is a service for recommending and gamifying activities in existing educational VLE videos. First, EVGAS uses Deep Learning techniques to classify videos from an AVA. Then, it accesses repositories of activities, such as Khan Academy and UVA OnlineJudge, in order to select activities according to the topics classified from the videos. Finally, EVGAS adds VLA activities and gamification. It allows the teacher to monitor student progress, including in relation to each topic of the video. As a result, this paper presents high level requirements and an EVGAS Mockup.