OER Knowledge CloudJournal ArticleMaya-Jariego, IsidroHolgado, DanielGonzález-Tinoco, ElenaCastaño-Muñoz, JonatanPunie, YvesParticipants in massive open online courses show a wide variety of motivations. This has been studied with the elaboration of classifications of the users according to their behavior throughout the course. In this study, we aimed to classify the participants in the MOOCs according to the initial motivations and intentions, before long interaction with the online device. Using a survey of 1768 participants in 6 MOOCs, we classify the participants according to: internal motives, external motives and intention of persistence. Three profiles of involvement in the course were identified: poorly motivated (16.7%), self referential (28.8%) and highly committed (54.5%). All three profiles showed significant differences in self-reported learning experiences at the end of the course. The intensity of the initial motivation was positively related to the satisfaction and perceived quality of the training experience. According to our analysis, identifying motivational profiles before starting the course allows to diagnose in advance the educational use and the diversity of individual training itineraries.20192019/06/24EnglishSpringer USEducational Technology Research and Development68203-224Spain10.1007/s11423-019-09682-3https://link.springer.com/article/10.1007/s11423-019-09682-31556-6501yescluster analysisinitial motivationslearning intentionmassive open online coursesopen educationself-regulation skillstypes of participantshttps://link.springer.com/article/10.1007/s11423-019-09682-3Spain, Europe