TY - GEN
T1 - Simulation of Student Skills
T2 - 17th IEEE International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2018
AU - Ahmad, Sadique
AU - Li, Kan
AU - Amin, Adnan
AU - Faheem, Muhammad Yasir
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/10/4
Y1 - 2018/10/4
N2 - To pass a job interview or written examination, students must have a specific set of Cognitive Skills (CS). The effects of frustration (aggression, giving up, loss of self-confidence, and depression) negatively affect these particular skills. Traditionally, a psychologist is invited for a job interview to determine these skills. Thus, there is no existing work which can predict CS outcome of students influenced by the effects of frustration. In the current attempt, we propose a technique that simulates the relationship between CS and frustration effects. Therefore, by quantization, we defined a specific range (0.1< CS<10) for CS and then divided it into 34 periodic CS outcomes with a period of 0.3. Furthermore, Bayesian inference method is used to calculate the posterior probabilities of each outcome of CS under the influence of frustration effects. During the experiments, the proposed technique tested on test dataset that have prior probabilities of CS and frustration effects. The results show that the proposed technique successfully simulated the statistical associations between CS and frustration effects. Finally, we concluded our work by the comparison with other CS predictions techniques.
AB - To pass a job interview or written examination, students must have a specific set of Cognitive Skills (CS). The effects of frustration (aggression, giving up, loss of self-confidence, and depression) negatively affect these particular skills. Traditionally, a psychologist is invited for a job interview to determine these skills. Thus, there is no existing work which can predict CS outcome of students influenced by the effects of frustration. In the current attempt, we propose a technique that simulates the relationship between CS and frustration effects. Therefore, by quantization, we defined a specific range (0.1< CS<10) for CS and then divided it into 34 periodic CS outcomes with a period of 0.3. Furthermore, Bayesian inference method is used to calculate the posterior probabilities of each outcome of CS under the influence of frustration effects. During the experiments, the proposed technique tested on test dataset that have prior probabilities of CS and frustration effects. The results show that the proposed technique successfully simulated the statistical associations between CS and frustration effects. Finally, we concluded our work by the comparison with other CS predictions techniques.
KW - Cognitive Skills Measurement
KW - Simulation of Cognitive Skills
KW - Student Cognitive Skills Prediction
UR - http://www.scopus.com/inward/record.url?scp=85056464894&partnerID=8YFLogxK
U2 - 10.1109/ICCI-CC.2018.8482091
DO - 10.1109/ICCI-CC.2018.8482091
M3 - Conference contribution
AN - SCOPUS:85056464894
T3 - Proceedings of 2018 IEEE 17th International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2018
SP - 97
EP - 102
BT - Proceedings of 2018 IEEE 17th International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2018
A2 - Howard, Newton
A2 - Kwong, Sam
A2 - Wang, Yingxu
A2 - Feldman, Jerome
A2 - Widrow, Bernard
A2 - Sheu, Phillip
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 16 July 2018 through 18 July 2018
ER -