Increasing the Accuracy of the Model for Predicting the Performance of University Students

This paper discusses approaches to preparing educational data on students' learning outcomes to improve the accuracy of predicting their academic performance over a given period. The rules for checking initial data for using them in a forecasting model are considered, implemented, and investigated. The rules help to work with poor-quality initial data and improve the accuracy of modeling. Modeling of students' learning outcomes is based on a nonparametric estimate of the Nadaraya-Watson regression function. The article presents some fragments of computational experiments that show acceptable results from a practical point of view.