Proceedings of the 2012 National Conference on Information Technology and Computer Science

Research on Online Education Teacher Evaluation Model based on Opinion Mining

Authors
Caiqiang Li, Junming Ma
Corresponding Author
Caiqiang Li
Available Online November 2012.
DOI
10.2991/citcs.2012.264How to use a DOI?
Keywords
Online Education; Teacher Evaluation; Opinion Mining
Abstract

This paper analyzes the current common teacher evaluation methods, and points out the shortcoming of current methods of using the rubrics: they rely on the fixed rubric rules, and take less into account students opinion text published in the LMS (learning management system). The paper provides an online education teacher evaluation model based on opinion mining. The model collects opinion texts in the LMS by using web crawler, and processes them by using topic extraction and sentiment orientation classification, etc. And thus the model gets an overall evaluation of each teacher. This processing can primarily run automatically and enhance efficiency and effect of the teacher evaluation.

Copyright
© 2012, 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 2012 National Conference on Information Technology and Computer Science
Series
Advances in Intelligent Systems Research
Publication Date
November 2012
ISBN
978-94-91216-39-8
ISSN
1951-6851
DOI
10.2991/citcs.2012.264How to use a DOI?
Copyright
© 2012, 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  - Caiqiang Li
AU  - Junming Ma
PY  - 2012/11
DA  - 2012/11
TI  - Research on Online Education Teacher Evaluation Model based on Opinion Mining
BT  - Proceedings of the 2012 National Conference on Information Technology and Computer Science
PB  - Atlantis Press
SP  - 1041
EP  - 1044
SN  - 1951-6851
UR  - https://doi.org/10.2991/citcs.2012.264
DO  - 10.2991/citcs.2012.264
ID  - Li2012/11
ER  -