Analysis and Prediction of Influencing Factors of College Student Achievement Based on Machine Learning - Wang, Dongxuan; Lian, Dapeng; Xing, Yazhou; Dong, Shiying; Sun, Xinyu; Yu, Jia (Frontiers in Psychology, 2022)
This paper's main objective is to analyze the reasons college student academic performance fluctuates. Based on this, machine learning and educational data mining techniques are used to explore the main influencing factors of college student performance. The questionnaire is designed refers to the relevant literature and the actual situation of the objects. The study objects are freshmen students from a university in Hebei Province, China. Firstly, the chi-square test is used to analyze the contents of the questionnaire and screen out the main factors affecting student performance. Then, the main influencing factors are selected as inputs of the mathematical model to analyze and predict student performance. Also, the test standard is established. By comparing various machine learning models, it is found that the SVC model shows the best and most stable effect. The average recall rate, precision rate, and accuracy rate can reach 82.83%, 86.18%, and 80.96%, respectively. Finally, according to the research results, some specific suggestions are provided for students, teachers and schools.