Autorregúlate, a Methodology to support self-regulated learning in MOOC courses
DOI:
https://doi.org/10.35575/rvucn.n71a4Keywords:
ADDIE, Self-regulation, MOOC, Educational technology, UDLAbstract
Global education is facing major challenges, including the lack of strategies and methods to ensure that students are truly engaged in the learning process, self-regulating their learning, and promoting successful completion of the educational process. In this research, we introduce Autorregúlate, a methodology to support self-regulated learning in Massive Open Online Courses (MOOCs), which from the design of the MOOC contributes to maintaining motivation and self-regulation throughout the course. Autorregúlate provides concrete and easy-to-implement guidelines for diverse teams in the creation of MOOCs, based on Zimmerman's self-regulation model. The methodology was validated in real MOOC courses using two evaluation instruments, the Questionnaire OSLQ and the Keller's Motivation Survey. Results show high levels of motivations (M=3,83; SD=0,7). On the other hand, results revel self-regulation strategies adoption by the participants, in particular, Goal setting (M=4,0; SD=0,7), Environmental structuring (M=4,1; SD=0,7), Task strategies (M=3,7; SD=0,7), Time management (M=3,84; SD=0,8), Seeking help (M=4,1; SD=0,8) and Self-evaluation (M=4,0; SD=0,7). Therefore, Autorregúlate support students on self-regulating their learning while achieving a sustained motivation.
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