Presentation of the Guidelines for Improving Teaching and Learning for Students of Sukhothai Thammathirat Open University: Application of Information from Data Mining Analysis
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Abstract
The objectives of this research were to 1) present guidelines for improving the teaching and learning of the courses in management science that were analyzed, and 2) develop a model for the characteristics of students in the dominant group and underprivileged group in management science. The sample was 233 Sukhothai Thammathirat Open University studying management science, political science, and law. The purposively sampled students had ID numbers ranging from 60 to 63. The research instruments were a questionnaire on factors related to education in the distance learning system and data on educational outcomes in subjects in management science that had the least number of students who passed the exam, and academic achievements in general education subjects. The research methodology was divided into 5 steps: 1) Data Collection: Information from the online questionnaire and students’ educational results; 2) Data Preparation: Selecting completed data to prepare for analysis; 3)Feature Selection:Specific attributes were selected for analysis; 4)Data Transformation: The data was converted into the CSV format; 5) Data Analysis: The data was analyzed using data mining techniques with the RapidMiner program, selecting the decision tree classification method.The research findings revealed that the decision tree data classification efficiency of the dominant group (Class S) of students gave an accuracy of 77.06% and the decision tree data classification efficiency of the underprivileged group (Class W) gave an accuracy of the model of 66.52%. From the research, 8 rules could be created as decision rules.
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