摘要
课程评论蕴含了学习者对慕课的感知、反应、需求、行为表现等要素,是研究慕课的基础数据源之一.本研究采用词频统计、词汇共现网络、文档位置对应分析和结构主题模型等方法对课程评论进行观点挖掘和可视化分析.结果表明,中国学习者外语慕课学习呈现出积极的学习情感,正性学习体验主要受到课程教师、课程支持和课程内容实用性三个维度的影响,负性学习体验受到成绩考核、作业评价与个性化支持三个维度的影响.此外,与语言技能课程相比,学习者对文学和专门用途外语课程的体验和需求维度存在较大差异.大数据驱动的可视化分析结果能够为外语慕课的学习体验设计与教学设计提供宏观和微观支持,为高质量外语慕课建设提供参考.
Abstract
Course reviews contain elements such as learners'perceptions,reactions,demands,and behavior towards Massive Open Online Courses(MOOCs),serving as one of the fundamental data sources for MOOCs research.This study utilizes methods such as word frequency analysis,word co-occurrence network analysis,correspondence analysis of document positions,and structural topic modeling to mine opinions from course reviews and visualize the learning experience.The results indicate an overall positive learning experience,with teacher support,course support,and course content practicality being key influencers.Students'negative learning experience is also influenced by three focal dimensions:course test,assignment feedback and personalized support.Additionally,learners exhibit distinct needs for literature and ESP courses compared to general language courses.These data-driven insights have significant implications at both macro and micro levels for enhancing the teaching design of Language MOOCs to optimize the learning experience,offering reference for the development of high-quality Language MOOCs.
NETL
NSTL
万方数据