Justin Reich teaches this session of MIT's CMS.595 Learning, Media, and Technology, laying out three genres of large-scale learning: instructor-guided, algorithm-guided, and peer-guided models. He traces how each approach structures teaching and interaction differently before turning to Massive Open Online Courses specifically, examining their history and the recurring problems that have limited their impact, including low completion rates and the gap between enrollment numbers and actual learning outcomes. The lecture treats MOOCs as a case study within the broader question of what happens to pedagogy when class size scales into the thousands or millions, and what gets lost or gained in instructor presence, feedback, and peer interaction along the way. Running about 73 minutes, it is one entry in a course examining how media and technology reshape education, grounded in MIT's own experience building and studying MOOC platforms.