Regulatory profiles for self-directed learning in MOOC

Participation in massive and open learning environments gives a new role to the learner as an individual who, connected with others and with the resources within their reach, learns autonomously. In this research, we rely on educational regulation as a necessary mechanism for self-directed learning processes in MOOCs. The purpose is to analyse a process of metacognitive enrichment of the design of a MOOC, with the contribution of the learners themselves. We implement a design-based research model, where self-regulation is, at the same time, the object of study and purpose of the design, which is used to personalize and make learning more flexible in an open massive environment. We develop a tool for the profiling of learners in their self-direction of learning in relation to three competency axes: motivational, social and reflective. The learners themselves participate in the development of this tool through a series of co-design workshops. The article presents the results of the process of design and implementation of the tool (or learner profile test): on the one hand, it presents the qualitative analysis of the contributions to the workshops for the construction of the tool and, on the other, the results after its implementation in the MOOC. The main contributions have to do, on the one hand, with the design solutions provided to support regulated learning and ML in MOOCs. On the other hand, they show the need to take care of the motivational components in the design of MOOCs, as well as the introduction of metacognitive aids that activate the self-monitoring strategies of the participants and progressively improve their self-perception and the alignment of their attitude with their activity in the MOOC, especially regarding the social learning dimension.