Abstract:
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 id...Show MoreMetadata
Abstract:
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.
Published in: IEEE Transactions on Learning Technologies ( Volume: 14, Issue: 2, 01 April 2021)
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- IEEE Keywords
- Index Terms
- Qualitative Analysis ,
- Topic Modeling ,
- Latent Dirichlet Allocation ,
- Massive Open Online Courses ,
- Latent Dirichlet Allocation Topic ,
- Learning Experiences ,
- Online Courses ,
- Time Commitment ,
- Open-ended Responses ,
- Prominent Theme ,
- Quality Of Feedback ,
- Open Online Courses ,
- Survey Data ,
- Level Of Knowledge ,
- Learning Styles ,
- Additional Aspects ,
- Grounded Theory ,
- Qualitative Agreement ,
- Understanding Of Matter ,
- Collective Response ,
- Latent Dirichlet Allocation Model ,
- Open-ended Survey Responses ,
- Number Of Learners ,
- Learning Background ,
- Thematic Topics ,
- Part Of Course ,
- Different Types Of Learning ,
- Video Lectures ,
- Reading Materials ,
- Qualitative Level
- Author Keywords
Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- Qualitative Analysis ,
- Topic Modeling ,
- Latent Dirichlet Allocation ,
- Massive Open Online Courses ,
- Latent Dirichlet Allocation Topic ,
- Learning Experiences ,
- Online Courses ,
- Time Commitment ,
- Open-ended Responses ,
- Prominent Theme ,
- Quality Of Feedback ,
- Open Online Courses ,
- Survey Data ,
- Level Of Knowledge ,
- Learning Styles ,
- Additional Aspects ,
- Grounded Theory ,
- Qualitative Agreement ,
- Understanding Of Matter ,
- Collective Response ,
- Latent Dirichlet Allocation Model ,
- Open-ended Survey Responses ,
- Number Of Learners ,
- Learning Background ,
- Thematic Topics ,
- Part Of Course ,
- Different Types Of Learning ,
- Video Lectures ,
- Reading Materials ,
- Qualitative Level
- Author Keywords