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- W4386331946 abstract "The introduction of MOOCs raised the expectation of a disrupting potential within education systems. These expectations, however, have not been met, despite the fact that more than a decade has passed. The main reason seems to be the high dropout rate of students in Massive Open Online Courses (MOOCs). With the start of the COVID-19 pandemic, the context of education systems has changed dramatically, as all were forced to shift to an online mode of education. In these new settings and leveraging the advancement of Artificial Intelligence (AI), in this research work, we report the findings by analyzing 90,294 reviews of MOOC completers in two subjects: Information Technology (IT) and Business. Using topic modeling with transformers, we have discovered the key themes that characterize MOOC completers’ reviews. The results show that for IT and Business courses, completers are not interested only in completing the course and earning a certificate, but are also interested in various aspects related to the course, instructor, and assessment. Furthermore, completers suggest that having short videos is more engaging and allows them to easily understand the content and have the ability for quick review. An interesting finding is that the completers of IT courses rated highly the organization and delivery of labs and hands-on sessions. Based on these findings, we propose some avenues for further development for MOOCs that consider the completers’ views and could potentially increase the retention rate in the MOOC environment." @default.
- W4386331946 created "2023-09-01" @default.
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- W4386331946 date "2023-01-01" @default.
- W4386331946 modified "2023-09-27" @default.
- W4386331946 title "Leveraging Topic Modeling to Investigate Learning Experience and Engagement of MOOC Completers" @default.
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- W4386331946 doi "https://doi.org/10.1007/978-3-031-41226-4_6" @default.
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