Because MOOCs bring big data to the forefront, they confront learning science with technology challenges. We describe an agenda for developing technology that enables MOOC analytics. Such an agenda needs to efficiently address the detailed, low level, high volume nature of MOOC data. It also needs to help exploit the data's capacity to reveal, in detail, how students behave and how learning takes place. We chart an agenda that starts with data standardization. It identifies crowd sourcing as a means to speed up data analysis of forum data or predictive analytics of student behavior. It also points to open source platforms that allow software to be shared and visualization analytics to be discussed.