Proceedings of the 2018 International Seminar on Education Research and Social Science (ISERSS 2018)

Big Data Analysis in General Education: Opportunities and Concerns

Authors
Wenjun Lyu, Zhaoqing Feng
Corresponding Author
Wenjun Lyu
Available Online July 2018.
DOI
https://doi.org/10.2991/iserss-18.2018.14How to use a DOI?
Keywords
Big Data, Education Data Mining, Predictive Analysis, General Education
Abstract
General education, as important part of higher education, is putting increasing attention on big data courses in universities. This paper discusses the opportunities and concerns about big data analysis in general education by stating predictive analytics, personalized learning planning and introducing machine learning techniques in these aspects. A basic framework of opportunities, an integrated application process, machine learning applications are introduced and performance prediction as well as course recommendation system are given combining the specialty of general education. Concerns are suggested from open online platform, universities, governments and institutions that more security is hard needed in cross-disciplinary learning environment as opportunities are multifaceted.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Proceedings
2018 International Seminar on Education Research and Social Science (ISERSS 2018)
Part of series
Advances in Social Science, Education and Humanities Research
Publication Date
July 2018
ISBN
978-94-6252-540-5
ISSN
2352-5398
DOI
https://doi.org/10.2991/iserss-18.2018.14How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Wenjun Lyu
AU  - Zhaoqing Feng
PY  - 2018/07
DA  - 2018/07
TI  - Big Data Analysis in General Education: Opportunities and Concerns
BT  - 2018 International Seminar on Education Research and Social Science (ISERSS 2018)
PB  - Atlantis Press
SN  - 2352-5398
UR  - https://doi.org/10.2991/iserss-18.2018.14
DO  - https://doi.org/10.2991/iserss-18.2018.14
ID  - Lyu2018/07
ER  -