Research on the Application of Data Mining Technology in English Course Performance Analysis

In the era of high-quality development of education, the analysis of students' course performance is no longer a single evaluation of students' learning ability, but more comprehensively serves the cultivation of students' comprehensive ability, career planning and the reform of teaching mode in colleges and universities. However, the current course performance analysis and processing methods mostly stay in the stage of data statistics, which can not directly obtain the hidden characteristics of data and judge its future development trend, which limits the full display of data value. In this regard, based on the actual application requirements, this paper will deeply discuss the feasibility of data mining technology in the field of teaching management in colleges and universities, and put forward a set of construction scheme of student performance analysis and processing model to promote the numerical transformation and upgrading of student course achievement analysis and processing methods. Practice has proved that this scheme takes college English courses as the research object. First, it digs out the key factors affecting English course performance through Apriori association rule algorithm, and then uses decision tree algorithm to build a prediction model, and adjusts the current teaching strategies according to the prediction results, thus realizing the deep mining of the data value of students' performance, providing strong support for educational decision-making and teaching reform.