I've been working through Andrew Ng's Machine learning class (https://www.coursera.org/learn/machine-learning/home/welcome) on Coursera, and I think it's wonderful. It begins a bit slow-paced, and I definitely supplement the lectures with readings and the class notes for CS 229 (http://cs229.stanford.edu/materials.html) that broadly match the content of the online course, but I absolutely love the course.
The lectures are well-paced and have 'in-line' quizzes to test your understanding as you go. The problem sets are easy to do at any time, with optional components and instructions that let you understand the material better if you want to deep dive. The course itself is available to start whenever you choose, which means barrier for entry is very low.
MOOCs may not be everything that they first promised, but they definitely win in terms of the sheer accessibility of content and the flexibility of the format. I would not be learning machine learning right now if the only available format was dead-tree or (worse) putting together information piecemeal from blog posts.
It's great if MOOCs help you with high-level tech stuff. But that's not what most students want or need. Someone in a low-level math or composition class is likely to need far more interaction with their instructor (which is what I take the article to be arguing).
I suppose that passes as a basic explanation, but I agree that a better definition would be nice.
In the last MOOC I signed up for one of the first things I read once inside was that it was 80% male and I should go encourage some females to join. Being a male I took this as a signal that I wasn't particularly wanted or valued in that course and I thought allow me to help your gender ratio by not participating.
It's strange they're simultaneously alienating their core users in order to "increase diversity" and complaining that their numbers aren't staying high enough.