Predict Physics Achievement in Middle School Education by Big Five Model and Artificial Neural Network
- Meng-Meng Yang, Soriya Aok, John Liu
- Corresponding Author
- Meng-Meng Yang
Available Online December 2017.
- https://doi.org/10.2991/seiem-17.2018.73How to use a DOI?
- big five model, physics achievement, middle school, artificial neural network, back propagation neural network,
- 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.
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 -