The aim of this paper is to track down elements of self-regulated learning in a massive open online course regarding social capital. Specifically, the study is oriented to explore the relationship between feeling of belonging to an online community and individual and collective regulation of learning. For this aim, a combination of two already tested scales was operated, adapted for the research interests of this study and administered to a sample of MOOC participants. Several structural equation modelling analyses demonstrate that co-and self-regulated learning strategies lead to MOOC achievement (final exam score), and social capital is only a moderator of co-regulated learning (collective evaluation of content and collective decision-making) but not for selfregulated learning (individual environment control).

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Background The peripheral venous catheter is the most frequently used medical device in hospital care to administer intravenous treatment or to take blood samples by introducing a catheter into a vein. The aim of this study was to examine the effect of motor imagery associated with actual training on the learning of peripheral venous catheter insertion into a simulated venous system. Method This was a prospective monocentre study in 3rd year medical students. Forty medical students were assigned to the experimental group (n = 20) performing both real practice and motor imagery of peripheral venous catheter insertion or to the control group (n = 20) trained through real practice only. We also recruited a reference group of 20 professional nurses defining the benchmark for a target performance. Results The experimental group learned the peripheral venous catheter insertion faster than the control group in the beginning of learning phase (p < 0.001), reaching the expected level after 4 sessions (p = .87) whereas the control group needed 5 sessions to reach the same level (p = .88). Both groups were at the same level at the end of the scheduled training. Conclusions Therefore, motor imagery improved professional motor skills learning, and limited the time needed to reach the expected level. Motor imagery may strengthen technical medical skill learning.

One of the main purposes of environmental education is to tackle the youth belief system and raise specific concerns linked to ecology and sustainability. Nonetheless, the educational approach to ecological concerns is partly about the methods used to reach effective results. The advancement of technologies and the rapid spread of social media have accelerated the use of online means of communication. While technology and digital tools have proven effective for educational purposes, it becomes necessary to examine the relationship between technology and environmental education, particularly in the Lebanese context. This position paper provides a review of studies on education, the environment, and digital tools, more specifically, studies conducted in Lebanon. It particularly focuses on the engagement of educational institutions and social incentives to raise environmental awareness and develop ecological behaviors in Lebanon. The results of this study will help stakeholders and researchers for future implementation of digital solutions in the Lebanese context toward a greener agenda.

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This paper uses data mining from a French project management MOOC to study learners’ performance (i.e., grades and persistence) based on a series of variables: age, educational background, socio-professional status, geographical area, gender, self- versus mandatory-enrollment, and learning intentions. Unlike most studies in this area, we focus on learners from the French-speaking world: France and French-speaking European countries, the Caribbean, North Africa, and Central and West Africa. Results show that the largest gaps in MOOC achievements occur between 1) learners from partner institutions versus self-enrolled learners 2) learners from European countries versus low- and middle-income countries, and 3) learners who are professionally active versus inactive learners (i.e., with available time). Finally, we used the CHAID data-mining method to analyze the main characteristics and discriminant factors of MOOC learner performance and dropout.

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