【作 者】：
刘三女牙，彭晛，刘智，孙建文，刘海
【关 键 词 】：
MOOC；文本评论；话题挖掘；LDA
【栏 目】：
网络教育
【中文摘要】：
研究以果壳网MOOC 学院的“财务分析与决策”课程为实验对象，通过分析课程评论帖进行学习者话题的
挖掘。文章不仅采用了高频词汇分析的定量方法，实现对学习者课程评论内容的整体认识，并且，根据参与评论学习者
的课程完成情况，分别对已完成和未完成两种类型的学习者展开定性的学习分析研究，应用非监督学习方法LDA 模型
自动挖掘和解析文本评论信息的特征结构和语义内容，并探究和追踪学习者关注的热点话题演化趋势。实验结果表明，
学习者认可和赞赏了该门课程，并且尤为关注课程内容以及教师授课形式话题；相比课程完成者，未完成者更倾向于解
释其未完成课程的主要原因，表达出更为消极的话题内容，并较少涉及课程本身相关的专业理论知识。
【英文摘要】：
This study takes the course Financial Analysis and Decision-making of MOOC college in
Guokr as the experimental subject to mine the learners' topics through analysis of course review posts.
Firstly, the study adopts the quantitative method of high frequency words analysis to realize the overall
understanding of the content of learners' course review. Then, the learning analysis is used to study the
learners who have completed the course as well as learners who haven't completed it respectively. The
unsupervised learning method LDA model is employed to automatically excavate and resolve the feature
structure and semantic content of text review information, explores and tracks the trend of hot topics that
learners are concerned about. The study results show that learners highly recognize and appreciate this
course, and pay special attention to the course content as well as teachers' teaching forms. Compared to
the completer, the learners who haven't completed the course tend to explain the main reasons for the
unfinished course, express more negative topics and less professional theoretical knowledge of the course.
【下 载】：
面向MOOC 课程评论的学习者话题挖掘研究