大数据视角下外语慕课讨论区评论的对比研究——基于情感分析和内容分析
A Comparative Study of Comments in Discussion Forums of LMOOC from the Perspective of Big Data:Sentiment Analysis and Content Analysis
蒋媛兰 1彭剑娥2
作者信息
- 1. 中山大学 外国语学院,广东 广州 510275
- 2. 汕头大学 文学院,广东 汕头 515063
- 折叠
摘要
本研究以 30 门国家精品英语慕课和 30 门普通英语慕课的讨论区评论为研究对象,采用情感分析和内容分析的研究方法,对比两类慕课的评论情感均值、课程评分和主题分布的异同.研究发现:1)精品慕课的评论情感均值和课程评分均显著高于普通慕课.2)两类慕课的评论主要反映五大主题,即对慕课的态度、对慕课的评论、对慕课教师教学的评价、学习效果、建议.3)学习者对慕课的积极态度和对教师教学的积极评价在精品慕课中的占比高于在普通慕课中的占比;学习者对慕课的评论以及学习效果在两种慕课类型上没有显著差异.研究结果为外语慕课教学设计提供了增强师生互动、增加双语字幕和提高教师口语水平的重要启示.
Abstract
This study employed sentiment analysis and content analysis to analyze students'comments posted in discussion forums of two types of Language Massive Online Open Courses(LMOOCs)(30 quality LMOOCs and 30 regular LMOOCs),and compared students'sentiment,course rating,and the distribution of the themes summarized from the comments.The results show that the sentiment values of student comments and the course rating of quality LMOOCs are both significantly higher than those of regular LMOOCs.Five major themes are identified from the student comments in the discussion forums of LMOOCs:attitudes towards LMOOCs,reviews on LMOOCs,assessment of LMOOC instruction and instructors,learning outcomes,and suggestions.Students'positive attitudes towards quality LMOOCs and positive assessment of instruction and instructors in these LMOOCSs are higher than in regular LMOOCs.However,there is no significant difference in the distribution of students'reviews on LMOOCs and learning outcomes between the two types of LMOOCs.These findings underscore the important role of teacher-student interaction,bilingual subtitles,and instructors'oral proficiency in LMOOC pedagogical design.
关键词
外语慕课/学习者评论/情感分析/内容分析/对比研究Key words
LMOOCs/students'comments/sentiment analysis/content analysis/comparative study引用本文复制引用
出版年
2024
NETL
NSTL
万方数据