Proceedings of the 2018 International Conference on Advances in Social Sciences and Sustainable Development (ASSSD 2018)

Research on Blended Learning Based on Competition

Authors
Bocheng Liu, Jianfeng Xu, Mengmeng Shi
Corresponding Author
Bocheng Liu
Available Online May 2018.
DOI
https://doi.org/10.2991/asssd-18.2018.68How to use a DOI?
Keywords
blended learning,SPOC,data mining
Abstract

Currently,data mining in the background of big data has become the core technology of big data analysis.Data mining engineers and big data analysts have gradually become more and more popular.This article explores the blended learning based on the combination of SPOC and competition driven, and conducts teaching practice in data mining courses to verify teaching effectiveness.Focusing on the teaching methods reform that combines theory and practice,so that competitions can be a useful supplement to daily teaching.Combined with competition activities to improve curriculum assessment system.After practice,preliminary verified its feasibility and effects.

Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2018 International Conference on Advances in Social Sciences and Sustainable Development (ASSSD 2018)
Series
Advances in Social Science, Education and Humanities Research
Publication Date
May 2018
ISBN
978-94-6252-500-9
ISSN
2352-5398
DOI
https://doi.org/10.2991/asssd-18.2018.68How to use a DOI?
Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Bocheng Liu
AU  - Jianfeng Xu
AU  - Mengmeng Shi
PY  - 2018/05
DA  - 2018/05
TI  - Research on Blended Learning Based on Competition
BT  - Proceedings of the 2018 International Conference on Advances in Social Sciences and Sustainable Development (ASSSD 2018)
PB  - Atlantis Press
SP  - 323
EP  - 326
SN  - 2352-5398
UR  - https://doi.org/10.2991/asssd-18.2018.68
DO  - https://doi.org/10.2991/asssd-18.2018.68
ID  - Liu2018/05
ER  -