Teaching Reform of Modern Optimization Algorithm Course Based on MOOC

The research on teaching reform of modern optimization algorithms based on MOOC is a research carried out by researchers at the University of Tokyo in Japan. The purpose of this study is to determine whether students’ learning outcomes and cognition have changed after using MOOC based modern optimization algorithm courses. This is one of the most important aspects of teaching because it determines how students will learn and what they will be able to do with the knowledge gained from this course. This article first analyzes the principles and methods of association rules and collaborative filtering, analyzes and designs the recommendation system in response to actual business scenarios, and proposes a fusion recommendation scheme. Then, through association analysis, it collects and collates relevant data on students’ learning conditions in the MOKE system, and merges and integrates the student achievement data to be mined to obtain time series data of students’ elective courses and achievements; And use discretization and data sparsization for preprocessing to obtain highly structured data items that can be mined and processed using Veka. The main purpose of this study is to assess whether there are differences between traditional courses taught by professors and courses taught through online platforms, try to find solutions to the current problems of college students’ low learning efficiency, lack of initiative, and low knowledge conversion rate, and strive to recommend courses that are more suitable for their learning and conducive to their long-term development and planning.