Governments and institutions are facing the new demands of a rapidly changing society. Among many significant trends, some facts should be considered (Silverstein, 2006): (1) the increment of number and type of students; and (2) the limitations imposed by educational costs and course schedules. About the former, the need of a continuous update of knowledge and competences in an evolving work environment requires life-long learning solutions. An increasing number of young adults are returning to classrooms in order to finish their graduate degrees or attend postgraduate programs to achieve an specialization on a certain domain. About the later, due to the emergence of new types of students, budget constraints and schedule conflicts appear.
Andrew Ng [Co-Founder of Coursera, Stanford Professor, Chief Scientist at Baidu, and All-Around Machine Learning Expert] is writing a book during the summer of 2016. The book is titled, Machine Learning Yearning. It you visit the site and signup quickly you can get draft copies of the chapters as they become available. Andrew is an excellent teacher. His MOOCs are wildly successful, and I expect his book to be excellent as well.
You can't read something about education these days without reading about how technology will change everything. Sorry to be a downer, but technology will change nothing if what is meant by technology is that we have new ways of delivering the same old material. The basic philosophy behind education for millennia has been that experts know stuff, so the experts (or their agents) will tell you the stuff you need to know. The problem is learning simply doesn't work that way. People learn by trying things out and seeing how it goes.
In the last years, knowledge technologies have been exploited for self-regulation functionalities inside e-learning systems. The definition of integrated system suitably scaffolding learners to improve their experi- ence is still lacking though. In this work, we propose an innovative Web-based educational environment that sustains metacognitive self-regulated learning processes upon Semantic Web and Social Web methods and technologies.