反馈式个性化试题推荐方法

FEEDBACK PERSONALIZED QUESTION RECOMMENDATION METHOD

面向学生的试题推荐是个性化在线教育领域重要的研究课题,现有的试题推荐方法忽视了难度和认知层次的区分。通过从难度、认知层次、题型和考核的知识点对试题属性进行标准化,以及定义难度能力矩阵和认知能力矩阵来评价学生的能力,提出基于内容的试题推荐算法和基于反馈的自适应的难度调整策略。个性化的试题推荐系统框架以及应用表明,该方法能够客观评价学生的能力和试题特性,能根据学生个体差异进行推荐的同时避免教师在试题属性初始设置中的偏差。

Question recommendation for students is a significant research direction in the field of personalized online education. Unfortunately,current studies ignore the distinction between the difficulty of questions and cognitive level.Students＇ abilities are evaluated by standardizing question attributes from difficulty,cognitive level,question type,and assessment knowledge points,and by defining a difficulty capability matrix and a cognitive ability matrix. Therefore,we proposed a content-based question recommendation algorithm and a feedback-based adaptive difficulty adjustment strategy. The personalized recommendation system framework and applications show that the method can objectively evaluate students＇ abilities and characteristics of the questions. It can also make recommendations based on student individual differences while also avoiding teachers＇ deviations in the initial setting of the test attributes.