Social education information technology. This survey article overviews some

Social Media Terms and Conditions•   Students are expected to actsafely by keeping personal information out of their posts. •    Students agree not to use theirfamily name, password, school name and location, or any other information thatcould enable someone to locate and contact them.

 •   Students are to use social mediaas an academic resource only and therefore behave as in the classroom. •  Students should not respond to comments that make them uncomfortable.Instead, they should report these comments to the instructor immediately.3.     ResearchStudy- A survey 3.1.       Abstract-Social LearningNetwork (SLN) In this paper, Abstract-Social Learning Network(SLN) type of social network implemented among students, instructors, andmodules of learning. It consists of the dynamics of learning behaviour over avariety of graphs representing the relationships among the people and processesinvolved in learning.

We Will Write a Custom Essay Specifically
For You For Only $13.90/page!

order now

Recent innovations in online education, including openonline courses at various scales, in flipped classroom instruction, and in professional andcorporate training have presented interesting questions about SLN. Collecting,analyzing, and leveraging data about SLN lead to potential answers to thesequestions, with help from a convergence of modelling languages and designmethods, such as social network theory, science of learning, and educationinformation technology. This survey article overviews some of these topics,including prediction, recommendation, and personalization, in this emergentresearch area. 3.2. MOOC Advanced educational technologies are developingrapidly and online MOOC courses are becoming more prevalent, creating anenthusiasm for the seemingly limitless datadriven possibilities toaffect advances in learning and enhance the learning experience.

For thesepossibilities to unfold, the expertise and collaboration of many specialistswill be necessary to improve data collection, to foster the development ofbetter predictive models, and to assure models are interpretable andactionable. The big data