Factors influencing learning outcome - application of decision tree algorithm - Lin, C.-J. (Proceedings Book of The 16th ITTF Sports Science Congress Budapest (HUN), April 19th - 20th, 2019, 2020)
The purpose of this study is to address the important factors of learning outcome in table-tennis courses. Classification and regression tree (CART) were employed to evaluate the data. Decision trees are a non-parametric supervised learning method used for classification and as a predictive tool. It is to model a series of events and look at how it affects an outcome. It can also provide information for decision makers in the decision-making process. The following factors were identified: teaching attitude, teaching material, teaching method, grading scheme and class management. Participants were 196 Table Tennis course students (82 male, 114 female). The data obtained from the survey were then analysed by using SPSS Modeler which is statistical analysis software used for data analysis, data mining and forecasting. The findings of this study demonstrate that grading scheme was the most important factor that impact student learning outcomes.