基于免疫RBF网络的在线开放课程学生学习数据管理模型  

Student Open Learning Data Management Model Based on Immune RBF Network

作　　者：李冰毅[1] LI Bingyi(Xi'an Railway Vocational And Technical Institute,Xi'an,Shaanxi,710026,China)

机构地区：[1]西安铁路职业技术学院,陕西西安710026

出　　处：《西安轨道交通职业教育研究》2020年第4期1-5,共5页Xi'an Rail Transit Vocational Education Research

摘　　要：由于在使用在线开放课程教学过程中,教师无法与学生“面对面”交流,故而无法直观掌握学生的学习情况。因此本文针对在线课程的用户数据,定义了若干用于评价学生学习态度的学习属性,并对这些属性做了特征化的模式分析,建立了学生学习状态的评价模型,给出不同学生应获教师关注度的参考值。最后利用免疫RBF网络建立了学生学习数据管理模型,对在线用户数据模式化处理后利用该模型可预测出对应学生的应获关注度,从而帮助教师制定针对性的教学方案,提高在线课程教学效果。经实际教学数据验证,本文提出的数据管理模型评价体系客观科学,预测准确率可达80%以上,应用本文提出的学生数据管理模型,教师可针对学生特点开展教学,做到真正意义上的因材施教,对教学改革和教学效果意义重大。Because the teacher can't communicate with the students“face-to-face”during the course of using the online open course,it is impossible to intuitively grasp the students'learning.Therefore,for the user data of online courses,this paper defines a number of learning attributes for evaluating students'learning attitudes,and makes a characteristic model analysis of these attributes,and establishes an evaluation model of students'learning status,giving the reference value of teachers’concern degree to different students.Finally,the student learning data management model is established by using the immune RBF network.After the online user data is modeled,the model can predict the corresponding attention of the students,thus helping the teachers to develop targeted teaching programs and improve the online teaching effect.Based on the actual teaching data,the data management model evaluation system proposed in this paper is objective and scientific,and the prediction accuracy rate can reach more than 80%.Using the student data management model proposed in this paper,teachers can carry out teaching according to the characteristics of students,and realize the practical teaching according to their aptitude.It is of great significance to teaching reform and teaching effects.

关 键 词：在线开放课程 数据管理 人工免疫 RBF网络 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构] G203[自动化与计算机技术—计算机科学与技术]