摘要
随着信息技术的飞速发展,有越来越多的学习者开始借助网络自主学习。网络学习资源丰富,学习不受时空限制,但网络学习中却存在着信息迷航、效率低下等弊端且越来越突出。文章根据MOOC平台上学习者的历史数据,抽取关键信息,结合软件工程专业课程知识图谱,将学习者的历史数据与知识图谱相结合,应用课程推荐度的量化算法和数据路径推荐算法,科学有效地为学习者规划学习路径,为学习者提供适宜指导,使其走出学习迷航。实验结果证明,该文构建的学习路径推荐方法适用可行,具有一定的应用推广价值。
With the rapid development of information technology,more and more learners use the network to learn independently.Network learning resources are rich,and learning is not limited by time and space,but there are many drawbacks in network learning,such as information maze,low efficiency,and so on.Based on the historical data of learners on the MOOC platform,this paper extracts key information,combines the knowledge map of software engineering courses,combines the historical data of learners with the knowledge map,applies the quantitative algorithm of course recommendation and the data path recommendation algorithm,scientifically and effectively plans the learning path for learners,provides appropriate guidance for learners,and makes them go out of the learning maze.The experimental results show that the learning path recommendation method constructed in this paper is applicable and feasible,and has certain application and promotion value.
作者
程山英
CHENG Shanying(School of Math and Computer Science,Jiangxi Science and Technology Normal University,Nanchang 330019,China)
出处
《现代信息科技》
2022年第21期169-172,共4页
Modern Information Technology
基金
江西省教育科学“十四五”规划2021年度课题“知识图谱视域下基于MOOC平台数据的学习路径推荐研究”(21YB132)。
