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Master Course Selection Prediction Model Using Modify Hybrid Neuro-fuzzy Inference System


Affiliations
1 Department of Computer Science, Shree Ramkrishna Institute of Computer Education and Applied Sciences, India
2 Department of Computer Science and Applications, Charotar University of Science and Technology, India
3 Department of Information Technology, Uka Tarsadia University - Maliba Campus, India
     

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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.

Keywords

Course Selection, Fuzzy Inference System, Academic Factors, Socioeconomic Factors, Psychological Factors.
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  • Master Course Selection Prediction Model Using Modify Hybrid Neuro-fuzzy Inference System

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Authors

Priti Shailesh Patel
Department of Computer Science, Shree Ramkrishna Institute of Computer Education and Applied Sciences, India
Jaimin Undavia
Department of Computer Science and Applications, Charotar University of Science and Technology, India
Dharmendra Bhatti
Department of Information Technology, Uka Tarsadia University - Maliba Campus, India

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.

Keywords


Course Selection, Fuzzy Inference System, Academic Factors, Socioeconomic Factors, Psychological Factors.