EFFECTIVE COMPLETION RATE DESIGN FOR MOOCS OF THE BINATIONAL LABORATORY PROJECT FOR SMART ENERGY SUSTAINABILITY MANAGEMENT AND TECHNOLOGICAL TRAINING

The completion rate in MOOC has been the subject of many criticisms and observations; the reality is that this educational topic has been adapted from non-systematic ways from the classroom education to the open one without the necessary conceptual adjustments.
Completion rates that MOOC have maintained over time, have been judged as very low, as well as unreliable and poorly calculated, to improve this situation, it has expressed the need for new models for theorizing on an effective terminal efficiency to be specifically designed for open, massive and online learning environments.
For some years, in the e-learning guild, ROI economic models of completion rates have been developed to evaluate, account for and pay for the work done by the advisors/teachers/tutors of e-learning courses. These models are the perfect foundation to design and develop the basis of an effective completion rate for open and massive online learning environments.
An effective completion rate design for MOOC should, in the first instance, differentiate among all types of users (some of which do not exist in face-to-face training, which partly explains some of the causes of the confusion in its interpretation and adaptation to the online environment) of the services offered in a MOOC.

Methodology:
A model for calculating the effective completion rate was designed, to quantify completion rates (abandonment, approval and disapproval) in MOOC, based on an economic model of terminal efficiency for online training environments. One of the most important model features to highlight is that it takes into account and differences among the various types of users of an open and massive online learning environment. The four most relevant at the MOOC ending are: 1) registered users who never entered the course (nevers); 2) registered users who entered the course but did not perform any task (droopies); 3) registered users who entered the course and did part of or all of the activities but did not achieve a passing grade and failed the course (failed); and 4) registered users who did part of or all of the activities and passed the course (approved).
The model in its pilot stage has been applied in the quantification, evaluation and comparison of the effective completion rate with some results of previous studies carried out with classic completion rate models on energy sustainability. MOOC in MéxicoX and EDX platforms were reviewed during the years 2017 and 2018 within the framework of the Binational Laboratory project for smart Energy Sustainability Management and Technological Training.

The results of this pilot study have indicated in its early stages, using and applying the student taxonomy and differentiating their grades (particularly zeros) by putting aside "never" users participating in the MOOC, the effective completion rates vs the classical completion rates could reach a ratio of 1:7, which means that the MOOC effective completion rate is about 7 times higher than the quantified by the classical model.