Proceedings of the 2017 2nd International Seminar on Education Innovation and Economic Management (SEIEM 2017)

Predict Physics Achievement in Middle School Education by Big Five Model and Artificial Neural Network

Authors
Meng-Meng Yang, Soriya Aok, John Liu
Corresponding Author
Meng-Meng Yang
Available Online December 2017.
DOI
https://doi.org/10.2991/seiem-17.2018.73How to use a DOI?
Keywords
big five model, physics achievement, middle school, artificial neural network, back propagation neural network,
Abstract
In order to predict physics achievement in middle school, this paper proposed a new method based on big five model. First, we collected 300 samples, in which 150 passed and the other 150 failed the final physics examination. Then, we submitted the five demographic features and five big-five personality trait features to the artificial neural network (ANN). Third, we used back propagation algorithm to train the ANN. The cross validation results show that our method yielded a sensitivity of 83.00± 2.09%, a specificity of 82.73± 4.12%, and an accuracy of 82.87± 2.75%.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Cite this article

TY  - CONF
AU  - Meng-Meng Yang
AU  - Soriya Aok
AU  - John Liu
PY  - 2017/12
DA  - 2017/12
TI  - Predict Physics Achievement in Middle School Education by Big Five Model and Artificial Neural Network
BT  - 2017 2nd International Seminar on Education Innovation and Economic Management (SEIEM 2017)
PB  - Atlantis Press
UR  - https://doi.org/10.2991/seiem-17.2018.73
DO  - https://doi.org/10.2991/seiem-17.2018.73
ID  - Yang2017/12
ER  -