Massive open online courses (MOOCs) offer many opportunities for research into several topics related to pedagogical methods and student incentives. In the context of over 20 years of online learning research, we discuss lessons to be learned from observational comparisons and experiments on randomly chosen groups of students. We target two MOOCs for our study. We investigate dropout rates and how students who decide to drop out differ from those who continue courses. We discuss class forums and video lectures and how these interactions correlate with achievement. We explore the strong correlation between procrastination and achievement and implications for MOOC design. We examine the role of certifications offered by MOOCs and how different options can affect outcomes. We also examine the potential of linking data across courses. We discuss survey data in the context of these MOOCs. These research opportunities offer big data challenges, which are addressed with parallel computing techniques.