Understanding the affect expressed by learners is essential for enriching the learning experience in Massive Open Online Courses (MOOCs). However, online learning environments, especially MOOCs, pose several challenges in understanding the different types of affect experienced by a learner. In this paper, we define two categories of emotions, explicit emotions as those collected directly from the student through self-reported surveys, and implicit emotions as those inferred unobtrusively during the learning process. We also introduce positivity as a measure to study the valence reported by students chronologically, and use it to derive insights into their emotion patterns and their association with learning outcomes. We show that implicit and explicit emotions expressed by students within the context of a MOOC are independent of each other, however, they correlate better with students' behavior compared to their valence. [For the full proceedings, see ED599096.]