Proceedings of the 2017 International Conference on Electronic Industry and Automation (EIA 2017)

A Conceptual Framework for Combination of Educational Data Mining and Software Cybernetics

Authors
Yi CAI, Qunxiong ZHU
Corresponding Author
Yi CAI
Available Online July 2017.
DOI
https://doi.org/10.2991/eia-17.2017.61How to use a DOI?
Keywords
educational data mining; software cybernetics; combination; framework
Abstract

Both educational data mining (EDM) and software cybernetics are emerging interdisciplinary research fields at present. This paper analyzes the combination mechanism between them in educational environment, and addresses a conceptual framework to improve the success of educational software. The framework regards educational software as the controlled object, EDM as the metric observer, and educational interpretation/evaluation as the feedback to satisfy the desired objectives relevant with the characteristics of integration, reliability and effectiveness.

Copyright
© 2017, 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/).

Download article (PDF)

Volume Title
Proceedings of the 2017 International Conference on Electronic Industry and Automation (EIA 2017)
Series
Advances in Intelligent Systems Research
Publication Date
July 2017
ISBN
10.2991/eia-17.2017.61
ISSN
1951-6851
DOI
https://doi.org/10.2991/eia-17.2017.61How to use a DOI?
Copyright
© 2017, 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  - Yi CAI
AU  - Qunxiong ZHU
PY  - 2017/07
DA  - 2017/07
TI  - A Conceptual Framework for Combination of Educational Data Mining and Software Cybernetics
BT  - Proceedings of the 2017 International Conference on Electronic Industry and Automation (EIA 2017)
PB  - Atlantis Press
SP  - 282
EP  - 286
SN  - 1951-6851
UR  - https://doi.org/10.2991/eia-17.2017.61
DO  - https://doi.org/10.2991/eia-17.2017.61
ID  - CAI2017/07
ER  -