A Novel Technique for the Evaluation of Posterior Probabilities of Student Cognitive Skills

To achieve excellent marks in job interviews and written examinations, a student must acquire impressive cognitive skills (CS) value. Nevertheless, the effects of frustration and CS related human factors (CSRFs) profoundly influence the student's skills during the aforementioned cognitive tasks. The recent methods present significant student's skills measurement techniques that compute the relationship among frustration, CS, and CSRF. Meanwhile, these methods become insufficient if the student's characteristics are not correctly quantized and simulated. No prior work can measure the posterior probabilities of student's CS during interviews and written examinations. In the current attempt, a novel CS measurement technique is proposed that simulates the nonlinear relationship among CS, frustration, and CSRF. First, the range of CS (0 to 20) is quantized and split into 21 periodic discrete outcomes. Proposing such range and then breaking it into components ensure the accuracy of CS prediction technique. Second, frustration is divided into four effects that have a strong association with CS. Third, the latent variable CSRF is split into two factors (mother job and exposure). Frustration and CSRF are referred to as umbrellas, while the effects of frustration and the factors of CSRF are referred to as layers of the umbrellas. The technique estimated the posterior probabilities of CS outcomes under the umbrella of frustration effects. Furthermore, the obtained posterior probabilities of CS are refined under the umbrella of CSRF factors. During the extensive experiment, the proposed technique is tested on two datasets. The obtained results show that the relationship among CS, frustration, and CSRF is successfully simulated because we achieved significant prediction accuracy. In the end, we compared the proposed approach with the prior competitive methods which concluded this study.