| dc.description.abstract | Class management systems have been developed by various methods, but very few of them are well-developed and efficiently used due to the lack of details and the inability to improve further when many aspects of the systems are continuously changed. However, traditional solutions have failed to address these issues, resulting in their inefficiency. Some previous works could fix this problem by applying various technology methods; However, not all solutions can work well in a real educational system. This research will describe a methodology to collect data from students and generate useful information for further analysis, along with building a student management system improved from the previous and present model of student management. Also, machine learning algorithms, specifically classification, will be used to learn all information generated from the student data, analyze each of the student’s abilities, strengths, and weaknesses. Besides, the system can generate visual charts to help users understand clearly for making decisions to open suitable class which follow the most appropriate skills which system have predicted. | en_US |
