Exploring Students’ Engagement Patterns in SPOC Forums and their Association with Course Performance
Zhi Liu 1 2 * , Niels Pinkwart 3, Hai Liu 1, Sannyuya Liu 1 2, Guangtao Zhang 3
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1 National Engineering Research Center for E-Learning, Central China Normal University, Wuhan, CHINA
2 National Engineering Laboratory for Educational Big Data, Central China Normal University, Wuhan, CHINA
3 Department of Computer Science, Humboldt University of Berlin, Berlin, GERMANY
* Corresponding Author

Abstract

With the popularity of Small Private Online Courses (SPOCs) in higher education, a plentiful of discussion data has been increasingly generated in SPOC forums. With 752 undergraduates’ discussion posts, this study aims to investigate students’ engagement patterns within SPOC forums in terms of engagement behaviors and emotions. Firstly, we designed a behavioral code rule to identify posting- and content-level behaviors, and examined their association with course performance. Secondly, we built an emotion lexicon including positivity, negativity and confusion word sets, and adopted an emotion calculation approach to visualize emotional evolutionary trends and to examine emotional differences in registration types and course performance. The results show that, (1) the high-performing group was more active in the most engagement behaviors except for interactive postings. (2) The registered group delivered more threads and wrote richer vocabulary in post content. (3) Whether students were registered for a course or not did not have a significant effect on their emotional expressions, but the registered group exhibited more confusion in forum interactions at the end of the semester. (4) Positive emotion was prevailing for the entire population. Furthermore, compared with the low-achieving group, the high-performing group had higher emotion densities in three types of emotions.

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Article Type: Research Article

https://doi.org/10.29333/ejmste/91667

EURASIA J Math Sci Tech Ed, 2018 - Volume 14 Issue 7, pp. 3143-3158

Publication date: 14 May 2018

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