基于协同过滤算法的学生选课偏好研究——以河北北方学院为例

Students’Preference for Course Selection Based on Collaborative Filtering Algorithm:Taking Hebei North University as Example

目的个性化推荐是基于统计理论与机器学习算法的一项重要技术手段,将其应用到高等教育领域,有助于解决大学生在选课时存在的随意性和盲目性问题。方法构建一个基于item协同过滤算法的学生选课推荐系统,并用编程语言对算法进行实践。同时,在全校范围内抽选2个专业共计60名同学进行系统试用,并调查相关学生的使用反馈。结果56名同学对课程推荐结果十分满意,4名同学比较满意。结论基于item协同过滤算法的学生选课推荐算法,存在可以进一步推广的潜力。构建基于该算法的学生选课推荐系统,有助于学生实现对课程的优化匹配,也有助于提升学校的教学管理效率。

Objective Personalized recommendation is an important technical means based on statistical theory and machine learning algorithm.Its application to the field of higher education will help to solve the problems of randomness and blindness of college students in course selection.Methods By constructing a recommendation system of course selection based on item collaborative filtering algorithm,the algorithm was practiced with Python language.At the same time,a total of 60 students from two majors in the university were selected for the system trial,and the feedback of relevant students was investigated.Results There were 56 students very satisfied with the course recommendation results,and 4 students relatively satisfied.Conclusion The recommendation algorithm of students’course selection based on item collaborative filtering algorithm has the potential of promotion.Constructing the recommendation system of course selection based on the algorithm is helpful to improve the efficiency of students in course selection and the ability of the school in teaching management.