High dropout rates and low pass rates are prevalent problems encountered by online learning platforms. Drawing upon the theory of attention allocation, this study aims to investigate the factors influencing the effectiveness of Massive Open Online Courses (MOOCs), as well as the potential moderating effects. An empirical analysis of 8,609 courses on a Chinese MOOC platform (Zhihuishu) is conducted. The findings indicate that course quality, content richness and interactivity significantly influence course dropout rates and pass rates. Besides, content richness moderates the relationship between course quality and learning effectiveness. Frequent online interaction is associated with lower pass rates in high-quality courses, but the moderating effect of interactivity on dropout rates is insignificant. This study contributes to the extant literature by examining course-level factors that affect learning effectiveness. It also offers new theoretical insights and provides valuable suggestions for the design of MOOCs.