Analizying MOOCs from an educational perspective in Spain

ABSTRACT: This article is the result of a Teaching Innovation Project funded by the University of Cantabria’s Vice-Rectorate for Teaching Staff. Its goals are to analyze the phenomenon of MOOCs with pedagogical criteria and to develop a Best Practice Guide. The project was developed by the Universities of Cantabria and Oviedo, all the work was divided into three phases: 1) Theoretical review and the design of classroom activities, 2) The implementation of classroom activities and analysis of the main results and 3) The development of a MOOC Best Practice Guide. The results of the second phase at the University of Cantabria are presented here. They demonstrate the need to introduce these massive open online courses into degree programmes in Education, updating higher education studies and providing valuable knowledge for understanding the educational potential (not just technological or financial) of this online training

Authoring Interactive Videos for e-Learning: The ELEVATE Tool Suite

Interactive videos are becoming common as e-Learning tools, applied to different knowledge areas and for different teaching objectives. Active research concerns the definition of methodologies and authoring tools for teachers and instructional designers for the creation of interactive videos, as well as studies on how to evaluate their effectiveness in distance learning. In the context of the ELEVATE project, we are developing a tool suite that offers a novel environment for authoring and management, including a virtual reality component for video production. This suite is expected to be mainly adopted within blended online courses for professional (adult) training on emergency management procedures. This paper presents the architecture of the ELEVATE Tool Suite and gives an overview of how it can be used, pointing out the role of different stakeholders

MOOC dropouts: A multi-system classifier

In recent years, technology enhanced learning platforms became widely accessible. In particular, the number of Massive Open Online Courses (MOOCs) has—and still is—constantly growing. This widespread adoption of MOOCs triggered the development of specialized solutions, that emphasize or enhance various aspects of traditional MOOCs. Despite this significant diversity in approaches to implementing MOOCs, many of the solutions share a plethora of common problems. For example, high dropout rate is an on-going problem that still needs to be tackled in the majority of MOOCs. In this paper, we set out to analyze dropout problem for a number of different systems with the goal of contributing to a better understanding of rules that govern how MOOCs in general and dropouts in particular evolve. To that end, we report on and analyze MOOCs from Universidad Galileo and Curtin University. First, we analyze the MOOCs of each system independently and then build a model and predict dropouts across the two systems. Finally, we identify and discuss features that best predict if users will drop out or continue and complete a MOOC using Boosted Decision Trees. The main contribution of this paper is a unified model, which allows for an early prediction of at-risk or dropout users across different systems. Furthermore, we also identify and discuss the most indicative features of our model. Our results indicate that users’ behaviors during the initial phase of MOOCs relate to their final results