基于教育数据挖掘学生表现预测模型构建研究

Performance Prediction Model Based on Data Mining Based Education Students

自教育数据挖掘成功从人工智能中独立出来,就获得研究学者的广泛关注,现已成为教育研究领域的热点。为了实现学生表现的准确预测,首先阐述了教育数据挖掘的概念、方法、核心应用及研究动态,并在此基础上从学生表现预测教育数据准备、数据筛选、数据预处理、数据转换、数据挖掘模型建立及结果分析等六个方面详细阐述了教育数据挖掘方法下学生表现预测模型构建的方法及设计流程,以期为未来的研究者提供一种思路和借鉴。

Data mining success from educational independence and from artificial intelligence will attract widespread attention onthe researchers and it has become a hot research field in education. In order to achieve accurate prediction of student performance, firstelaborate the concept of education data mining methods, the core applications and research trends. On this basis, performance predic-tion is from the student data preparation, data filtering, data preprocessing, data conversion, data mining modeling and results analy-sis, elaborated under the educational data mining student performance prediction model. Investigate the construction methods and de-sign processes, with a view to the future and to learn from the ideas provided by the researchers.