Intelligent system for predicting students performance
By: Manga, I
.
Contributor(s): El-Yakub.
Publisher: Haryana IOSR - International Organization of Scientific Research 2022Edition: Vol.24(1), Jan-Feb.Description: 36-42p.Subject(s): Computer EngineeringOnline resources: Click here
In:
IOSR Journal of Computer Engineering (IOSR-JCE)Summary: One of the causes of the gradual decline of the Nigerian Educational System can be attributed to the
inadequacies and flaws in universities admission process. In this paper, we seek to address this problem by
predicting the first-year performances of prospective students using Fuzzy Logic based on prior academic
achievements presented during admission process. A range of conventional secondary school subjects were
used as the input variables in a Mamdani Model. MATLAB fuzzy logic toolbox was used to model the fuzzy rules
logic in this study with computer science course (CSC) criteria in the x axis, General studies course (GST)
criteria is in y axis, and solution criteria Performance (P) is in z axis. The results show that a student with a
model output of CSC=0.857, MTH=0.796, PHY=0.864, GST=0.638, CHM=0.489 model output P=0.446.
Output P=0.446 means that the student will most likely perform above the 95th percentile of the Grade Point
Average (GPA). The design was successfully tested and implemented.
| Item type | Current location | Call number | Status | Date due | Barcode | Item holds |
|---|---|---|---|---|---|---|
Articles Abstract Database
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School of Engineering & Technology Archieval Section | Not for loan | 2022-2074 |
One of the causes of the gradual decline of the Nigerian Educational System can be attributed to the
inadequacies and flaws in universities admission process. In this paper, we seek to address this problem by
predicting the first-year performances of prospective students using Fuzzy Logic based on prior academic
achievements presented during admission process. A range of conventional secondary school subjects were
used as the input variables in a Mamdani Model. MATLAB fuzzy logic toolbox was used to model the fuzzy rules
logic in this study with computer science course (CSC) criteria in the x axis, General studies course (GST)
criteria is in y axis, and solution criteria Performance (P) is in z axis. The results show that a student with a
model output of CSC=0.857, MTH=0.796, PHY=0.864, GST=0.638, CHM=0.489 model output P=0.446.
Output P=0.446 means that the student will most likely perform above the 95th percentile of the Grade Point
Average (GPA). The design was successfully tested and implemented.
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