Greetings Dr Agarwal,
The invisible part of MOOCs is the massive collection of data on the behavior of students. Here, we're talking about Learning Analytics and Big Data which should be used to improve the next generation of MOOCs. This is a common practice of Web 2.0, the improvement process à la Google that exploits the data of its millions of users to improve its search engine. Here, students' data are a goldmine.
It is not easy for a teacher to find the sources of confusion and less effective pedagogical approaches from the small samples of data collected with a class of 20 students each year. Moreover, those students are pretty similar (the sample is statistically pretty homogenous). At the contrary, a MOOC with its thousands of students from all around the world and with very different backgrounds can use effective statistical data mining methods to detect problems and improve teaching. MOOC can also use machine learning to discover situations (or patterns) where students have common problems, in order to present evidence or explanations to help them.
More, compared to human, a computer never gets angry and it is always ready to resume its explanations, making it an ideal teaching tutor.
Do you see the potential for continuous improvement of MOOCs mainly due to Big Data, the secret ingredient of MOOCs in the long term?
Claude Coulombe
Montréal