Visual Analysis of Finance Courses on Chinese University MOOC Platform Based on Web Crawler

Abstract

Finance is a professional basic course for economics and finance majors. The purpose of the present research is to use web crawler technology to capture data such as institutions, teaching teams, student participation scale, scoring and evaluation of finance and related derivative courses on the Chinese university MOOC platform, and to analyze and display the data visually to understand the current situation of course construction. This research uses Xpath, Pandas, Beautiful Soup, and other tools in Python to develop a web crawler program for automatic test login, capture course information, and perform visual analysis on the obtained data. The study found that the current finance course resources of MOOC platforms in Chinese universities are not fully utilized; Central University of Finance and Economics, Southwestern University of Finance and Economics, and Hunan University attach great importance to curriculum construction. 985 universities have higher strength in curriculum team building; All national quality courses were first started earlier than 2019. After 2020, the pace of construction of new courses in finance slowed down. Chinese university MOOC platform should strengthen the publicity of high-quality courses, and the course team should enrich course resources to increase the utilization rate of courses and improve the ability of college students to solve financial problems.