MASTER COURSE SELECTION PREDICTION MODEL USING MODIFY HYBRID NEURO-FUZZY INFERENCE SYSTEM

Abstract
Many of the students have completed their graduation, but they are not sure of their future course that will lead them to a good career as a professional. They are mystified or do not know an acceptable choice of higher education courses. This is a very key factor of their careers to encourage and improve awareness of the proper guidance for their career progression. This paper suggests a novel modify approach with the use of hybrid neural network and fuzzy system as “Fuzzy Inference System (FIS)” for the analysis of an IT Postgraduates student selection course. The prediction of course selection based on student academic performance and psychological factors are important students. Mainly for the performance prediction of course selection which is a very critical decision-making method to make the student’s career path. This study is helpful for those students who want to enroll higher education study in specific course. However, previous techniques often considered by many researcher scholars using academic past performance data and personal data for prediction, leading to the creation of complicated predicting methods whose results are helpful to interpret. Also, this paper explores the use of highly effective psychological factors attributes with other factors such as student personal factors, academic factors and socioeconomic factors that are easily accessible and interpretation.

Authors
Priti Shailesh Patel1, Jaimin Undavia2, Dharmendra Bhatti3
Shree Ramkrishna Institute of Computer Education and Applied Sciences, India1, Charotar University of Science and Technology, India2, Uka Tarsadia University - Maliba Campus, India3

Keywords
Course Selection, Fuzzy Inference System, Academic Factors, Socioeconomic Factors, Psychological Factors
Published By :
ICTACT
Published In :
ICTACT Journal on Soft Computing
( Volume: 11 , Issue: 1 )
Date of Publication :
October 2020
DOI :

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