In MOOCs, course reviews are valuable sources for exploiting learners’ attitudes towards the courses provided. This study employed an innovative structural topic modeling technique to analyze 1920 reviews of 339 courses regarding computer science to understand what primary concerns the learners had. Nine major topics, including course levels, learning perception, course assessment, teaching styles, problem solving, course content, course organization, critique, and learning tools and platforms were revealed. In addition, we investigated how the identified nine topics varied across reviews with different ratings. Results indicated that negative reviews tended to relate more to issues such as course assessment, learning tools and platforms, and critique, while positive reviews concerned more about issues such as course levels, course organization, and learning perception. This study provided tutors with novel implications for developing online courses, particularly computer science courses.
|Title of host publication||Database Systems for Advanced Applications. DASFAA 2020 International Workshops|
|Editors||Yunmook NAH, Chulyun KIM, Seon-Young KIM, Yang-Sae MOON, Steven Euijong WHANG|
|Number of pages||7|
|Publication status||E-pub ahead of print - 22 Sep 2020|
|Name||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
This research received grants from the Standing Committee on Language Education and Research (EDB(LE)/P&R/EL/175/2), the Education Bureau of the Hong Kong Special Administrative Region, the Internal Research Grant (RG93/2018-2019R), and the Internal Research Fund (RG 1/2019-2020R) of the Education University of Hong Kong.
- Online course reviews
- Structural topic model