Although there is a plethora of online learning engagement studies, relatively little attention has been paid to the relationship between learning engagement and academic performance in the context of online general education courses. Accordingly, this study takes an online general education course offered by a university in eastern China as an example, proposes a model for evaluating online learning engagement and specific metrics for the model, and conducts a cluster analysis of the online learning engagement of 422 undergraduate students who took the course as sample data through a clustering K-means algorithm. Based on the relationship between learners’ online learning behavioral engagement and academic performance, learners were classified into three categories: “active learners”, “go-with-the-flow learners” and “passive learners”. The study concludes that the classification of online learning engagement and academic performance is beneficial for teachers and administrators to grasp the whole learning process of learners in the context of online general education courses, clarify the types of online learning engagement and their characteristics, and provide data reference for students’ personalized learning support service system, thus promoting the establishment of a high-quality school-based general education course system.