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Seventh IEEE International Conference on Advanced Learning Technologies (ICALT 2007)
Niigata, Japan
July 18-July 20
ISBN: 0-7695-2916-X
ASCII Text
x 
 
Pokpong Songmuang, Masahiro Ando, Masahito Nagamori, Maomi Ueno, Toshio Okamoto, "E-Testing Construction Support System with some Prediction Tools," Advanced Learning Technologies, IEEE International Conference on, pp. 437-438, Seventh IEEE International Conference on Advanced Learning Technologies (ICALT 2007), 2007.
 
 
BibTex
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@article{ 10.1109/ICALT.2007.132,
author = {Pokpong Songmuang and Masahiro Ando and Masahito Nagamori and Maomi Ueno and Toshio Okamoto},
title = {E-Testing Construction Support System with some Prediction Tools},
journal ={Advanced Learning Technologies, IEEE International Conference on},
volume = {0},
year = {2007},
isbn = {0-7695-2916-X},
pages = {437-438},
doi = {http://doi.ieeecomputersociety.org/10.1109/ICALT.2007.132},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Advanced Learning Technologies, IEEE International Conference on
TI - E-Testing Construction Support System with some Prediction Tools
SN - 0-7695-2916-X
SP437
EP438
A1 - Pokpong Songmuang,
A1 - Masahiro Ando,
A1 - Masahito Nagamori,
A1 - Maomi Ueno,
A1 - Toshio Okamoto,
PY - 2007
KW - null
VL - 0
JA - Advanced Learning Technologies, IEEE International Conference on
ER -
 
Pokpong Songmuang, The University of Electro-Communications, Japan
Masahiro Ando, The University of Electro-Communications, Japan
Masahito Nagamori, The University of Electro-Communications, Japan
Maomi Ueno, The University of Electro-Communications, Japan
Toshio Okamoto, The University of Electro-Communications, Japan
This paper proposes an e-testing construction support system (eTCSS) with the prediction tools for the constructed test. This paper performs some comparison experiments to find the best predictive performances models for the Predictive response-time distribution and the Predictive response-time distribution. Furthermore, the amount of test information based on the Item Response Theory, which is important to improve the measurement efficiency of the constructed test, is applied to be the prediction tool of the eTCSS. Finally, this paper evaluates the system by using actual data. The results show the effectiveness of the system.
Citation:
Pokpong Songmuang, Masahiro Ando, Masahito Nagamori, Maomi Ueno, Toshio Okamoto, "E-Testing Construction Support System with some Prediction Tools," icalt, pp.437-438, Seventh IEEE International Conference on Advanced Learning Technologies (ICALT 2007), 2007
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