摘要
教育信息化进程不断加快,使得在线教育蓬勃发展,但其开放化、多元化令学习成果的诊断和认证变得困难.该文针对在线课程教育体系的特殊需求,以MOOC在线精品课程"电路原理"为例提出了一种基于贝叶斯网络的在线课程学习成果诊断与认证方法 .以学习产出为导向构建认知测量模型动态诊断学习者的知识结构和专业能力,并结合国内外元数据标准进行元数据XML绑定,将学习成果及其评估结果嵌入工程教育开放徽章作为认证机制,实现在线课程学习成果展示和验证.
The continuous acceleration of education informatization has made online education flourish,but its openness and diversification make it difficult to diagnose and authenticate learning outcomes.In this paper,based on the special needs of the online course education system,a diagnosis and authentication method of online course learning results based on Bayesian network is proposed by taking the MOOC online quality course “circuit principle” as an example.Based on the learning output,the cognitive measurement model is used to dynamically diagnose the learner’s knowledge structure and professional ability.Metadata XML binding is combined with domestic and foreign metadata standards,and the learning results and evaluation results are embedded in the engineering education open badge as certification mechanism,so as to achieve online course learning results display and verification.
作者
彭馨
谭貌
段斌
于歆杰
章兢
PENG Xin;TAN Mao;DUAN Bin;YU Xin-jie;ZHANG Jing(College of Information Engineering,Xiangtan University,Xiangtan 411105;Department of Electrical Engineering,Tsinghua University,Beijing 100084 China)
出处
《湘潭大学学报（自然科学版）》
CAS
2018年第6期1-10,共10页
Journal of Xiangtan University(Natural Science Edition)
基金
湖南省普通高等学校教学改革研究项目
