There is a large variation in background and purpose of massive open online course (MOOC) learners. To improve the overall MOOC learning experience, it is important to identify which MOOC characteristics are most important for learners. For this purpose, in this article, we analyzed about 150 000 open-ended learner responses from 810 MOOCs to three postcourse survey questions about their learning experience: (Q1) What was your most favorite part and why? (Q2) What your least favorite part and why? (Q3) How could the course be improved? We used the latent Dirichlet allocation topic model to identify prominent topics present in learner responses to each question. We determined the theme of each identified topic through qualitative analysis. Our results show that the following aspects of MOOCs can significantly impact the learning experience: quality of course content, accurate description of prerequisites and required time commitment in course syllabus, quality of assessment and feedback, meaningful interaction with peers and educators, engaging instructor and videos, accessibility of learning materials, and usability of platform.

中文翻译：

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使用 LDA 主题建模和定性分析分析来自 MOOC 学习者的大量开放式反馈

大规模开放在线课程 (MOOC) 学习者的背景和目的存在很大差异。为了改善整体 MOOC 学习体验，重要的是要确定哪些 MOOC 特征对学习者最重要。为此，在本文中，我们分析了来自 810 个 MOOC 的大约 150 000 个开放式学习者对三个关于他们学习体验的课后调查问题的回答：（Q1）你最喜欢的部分是什么，为什么？(Q2) 你最不喜欢的部分是什么，为什么？(Q3) 如何改进课程？我们使用潜在的狄利克雷分配主题模型来识别学习者对每个问题的回答中存在的突出主题。我们通过定性分析确定了每个确定主题的主题。我们的研究结果表明，MOOC 的以下方面可以显着影响学习体验：