语法试题个性化推荐系统的研究

Research on personalized recommendation system of grammar test question

为了提高试题个性化推荐系统对语法试题推荐的有效性,定义了韩语语法点矩阵、得分模型、潜在学习特征向量等,建立了学习态势算法,设计了试题智能推荐的整体框架。该系统以学习者的态势计算为基础,对学习者语法学习能力估算,再进行试题推荐。通过两组学习者对比,根据系统的平均使用时间、成绩提高率、答卷正确率和试题推荐精准率等指标进行评估,结果显示,该推荐系统对学习者有显著的助学效果。

In order to improve the effectiveness of the personalized test question recommendation system for grammar test question recommendation,Korean grammar point matrix,score model and potential learning feature vector are defined,the learning situation algorithm is established,and the overall framework of test question intelligent recommendation is designed.On the basis of learners'situation calculation,the system estimates learners'grammar learning ability,and then recommends test questions.Through the comparison between the two groups of learners,the evaluation is carried out according to the indicators such as the average use time of the system,the improvement rate of scores,the correct rate of answers and the accuracy rate of test question recommendation.The results show that the recommendation system has a significant help learning effect on learners.