Proceedings of the 2018 International Workshop on Education Reform and Social Sciences (ERSS 2018)

Educational Development Technology in Artificial Intelligence Era

Authors
Guibao Liu, Yingfang Zhao
Corresponding Author
Guibao Liu
Available Online January 2019.
DOI
https://doi.org/10.2991/erss-18.2019.34How to use a DOI?
Keywords
Educational Development Technology; Artificial Intelligence; Innovation.
Abstract

In order to effectively combine the traditional educational mode with Artificial Intelligence (AI), the Bayesian conditional probability prediction model was adopted. Basing a knowledge map and a knowledge database, the answer to the student's mathematical subjective question was judged. Through the research and application of key technologies for error type positioning, the error knowledge points of each line were accurately found. A comprehensive feedback evaluation system for the complete error type was implemented. Therefore, the application of inference knowledge base technology saves teachers' time and improves the efficiency of marking.

Copyright
© 2019, 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 Workshop on Education Reform and Social Sciences (ERSS 2018)
Series
Advances in Social Science, Education and Humanities Research
Publication Date
January 2019
ISBN
978-94-6252-664-8
ISSN
2352-5398
DOI
https://doi.org/10.2991/erss-18.2019.34How to use a DOI?
Copyright
© 2019, 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  - Guibao Liu
AU  - Yingfang Zhao
PY  - 2019/01
DA  - 2019/01
TI  - Educational Development Technology in Artificial Intelligence Era
BT  - Proceedings of the 2018 International Workshop on Education Reform and Social Sciences (ERSS 2018)
PB  - Atlantis Press
SP  - 173
EP  - 176
SN  - 2352-5398
UR  - https://doi.org/10.2991/erss-18.2019.34
DO  - https://doi.org/10.2991/erss-18.2019.34
ID  - Liu2019/01
ER  -