Machine-Learning based MOOC Education Data Analysis

MOOC (Massive Open Online Courses), as a product of Internet + education, provides learners with quality courses while allowing learners to engage in the act of learning anytime and anywhere. However, because online learning is all about self-awareness, students are prone to unsatisfactory examination results. Analysis of the learning dataset generated by learners in the MOOC model reveals that each learning behavior has an impact on learners’ final grades, and the correlation size varies. And three algorithms, K-NN, LVQ, and SVM, are used to predict learners’ grades, personalize instructional interventions for students with inappropriate learning behaviors, and compare and analyze the three models to improve learners’ final grades using a more suitable algorithmic model.