Proceedings of the 2018 4th International Conference on Social Science and Higher Education (ICSSHE 2018)

Research on Blended Learning Mode of SPOC-based Computer Science Course for the Deaf

Authors
Zhili Liu, Yan Li, Hanjing Li, Dengfeng Yao
Corresponding Author
Zhili Liu
Available Online September 2018.
DOI
https://doi.org/10.2991/icsshe-18.2018.17How to use a DOI?
Keywords
SPOC, computer science course, blended learning, the deaf, special education
Abstract
As one of the traditional courses of higher education in China, computer science course for the deaf college students has to be adjusted in teaching content, and the course presentation, learning mode as well. The traditional teaching mode should be blended for dynamic mode instead of static teaching, learning quality and efficiency to be improved. The writer in this paper, therefore, has designed the blended learning mode of SPOC-based computer science course from four phases including leading end analysis, resource design, activity design and teaching evaluation, and also designed teaching cases originated from the course of Database Principles and Applications with off-line teaching plus on-line activities and on-line learning plus off-line activities. At the end of this essay, a teaching experience has been carried out to test the assumption that this blended learning mode of SPOC-based course can really promote the teaching effect of computer science course, students’ degree of satisfaction improved.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Cite this article

TY  - CONF
AU  - Zhili Liu
AU  - Yan Li
AU  - Hanjing Li
AU  - Dengfeng Yao
PY  - 2018/09
DA  - 2018/09
TI  - Research on Blended Learning Mode of SPOC-based Computer Science Course for the Deaf
BT  - Proceedings of the 2018 4th International Conference on Social Science and Higher Education (ICSSHE 2018)
PB  - Atlantis Press
SP  - 66
EP  - 69
SN  - 2352-5398
UR  - https://doi.org/10.2991/icsshe-18.2018.17
DO  - https://doi.org/10.2991/icsshe-18.2018.17
ID  - Liu2018/09
ER  -