Analysis of Students Engagement and Learning Performance in a Social Community Supported Computer Programming Course
Yu-Sheng Su 1, Ting-Jou Ding 2, Chin-Feng Lai 3 *
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1 National Central University, TAIWAN
2 MingDao University, TAIWAN
3 National Cheng Kung University, TAIWAN
* Corresponding Author

Abstract

In Taiwan, the social community, Facebook has been more and more powerful ever since being launched, and it serves as if a strong magnet, attracting teachers and students to share and discuss on such platform, and also to search for films, pictures, and messages of their specific interests. Some researchers have probed into the learning interaction and efficacy of a computer programming course, and the results show that not only could the learning interactions between teachers and students enhance, but also between students themselves under this environment supported by Facebook. We propose four steps of learning analytics to study students’ behaviors and learning performances in a social community supporting computer programming course. Furthermore, our learning analytics method could decrease the time and energy consuming process, which includes collecting, correlating and organizing students’ participative patterns. A reported case, focuses on students’ engagement behaviors and its influence on students’ learning outcomes, is carried out with 43 freshmen at a university in northern Taiwan. The results show that our learning analytics method benefits students’ participative behaviors, which are related to students’ learning achievements in the computer programming course supported by social community, since students could obtain better understanding under such learning mode.

License

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/10.12973/eurasia.2017.01058a

EURASIA J Math Sci Tech Ed, 2017 - Volume 13 Issue 9, pp. 6189-6201

Publication date: 15 Sep 2017

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Article Downloads: 118

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