Design And Implementation of A Webbased University Admission And Placement Neural Network Model

ABSTRACT

Every year the number of applicants seeking admission into Nigerian Universities increases by leaps and bounds although the Universities lack the commensurate to meet the challenges of admitting the high number of applicants.

For this reason, the admission officers have to manually evaluate every candidate’s data against the set admission requirements to screen the applicants in order to select the number of candidates that their universities can accommodate.

The involved are very cumbersome, time-consuming and prone to a lot of human errors and irregularities.

Many candidates miss out on admission every year, and the most painful aspect of this manual process is that many who are not qualified for a particular course end up being given placement into such courses while the more qualified ones are left out.

Consequently, for lack of aptitude for the , the students struggle through and many even resort to cheating their way through examinations and then graduate out of the Universities ill-equipped for the job market and society.

On the other hand, some of the less fortunate but qualified ones who are not given University admission year after year, become so frustrated over time and end up in hideous lifestyles.

Whichever way, society suffers and national growth is hindered. In this work, a web-based model was designed to considerably take care of the above problems.

The system was developed to provide a time-efficient, detailed and unbiased automated procedure for selecting the most qualified candidates for admission into ,

and ensure that qualified candidates, who fail to meet the requirements for a particular course, are automatically placed into other courses for which they meet the admission requirements and where vacancies exist, using neural network model.

The model also provides an avenue for students to self-screening the .

TABLE OF CONTENTS

Contents Page
Blank Page ……………………………………………………………………….i
Cover Page ………………………………………………………………………ii
Title Page ……………………………………………………………………….iii
Declaration ………………………………………………………………………….iv
Certification ………………………………………………………………………v
Dedication ………………………………………………………………………vi
Acknowledgement …………………………………………………………………vii
Abstract ………………………………………………………………………… ix
Table of Contents ……………………………………………………………… xi
List of Tables ……………………………………………………………………..xiii
List of Figures …………………………………………………………………… xiv
Chapter One – Introduction
1.1 Background to the study and Statement of the Problem ………………….1
1.2 Research motivations ……………………………………………………..7
1.3 Research objectives ………………………………………………………10
1.4 Research methodology ……………………………………………………….10
1.5 Limitations to the study ………………………………………………………11
1.6 Contributions to knowledge ………………………………………………11
1.7 Organization of the Thesis ……………………………………………….13
Chapter Two – Literature Review
2.1 Artificial neural networks ………………………………………………..14
2.2 Electronic implementation of Artificial ………………………………….23
2.3 Structure of artificial neural networks…………………………………25
2.4 Training an artificial neural network ……………………………………..28
2.5 Network architectures …………………………………………………….33
2.6 Related works …………………………………………………………….36
2.7 Discriminant analysis …………………………………………………….43
Chapter Three – System Analysis and Modelling
3.1 The student selection problem ……………………………………………46
3.2 The model ………………………………………………………………..48
Chapter Four – System Design and Implementation
4.1 Software Platform for implementation …………………………………..57
4.2 The University Admission And Placement System Design ……………..63
4.3 System Implementation ………………………………………………….75
4.4 System Requirements ……………………………………………………76
Chapter Five – Conclusion and Recommendations
5.1 Conclusion ……………………………………………………………….84
5.2 Recommendations ……………………………………………………….85
References ……………………………………………………………………….86
Appendix A………………………………………………………………………96

INTRODUCTION

Background to the Study and Statement of the Problem

Higher education in Nigeria can be traced to 1932 when Yaba Higher College was established for the purpose of producing assistants who would relieve the then colonial administrators of menial tasks.

Thus in 1940, the UniversityCollege, Ibadan was established but the programmes offered there and then were narrow because the agenda of the colonial administration did not include the training of high-level manpower for many of the professions.

The AshbyCommission in 1960, recommended the establishment of regional universities in the then three regions of Nigeria.

Three universities were established: theUniversity of Nigeria, Nsukka (1960) in the Eastern region; the University of Ife, now Obafemi Awolowo University (1961) in the Western region and Ahmad Bello University, Zaria (1962) in the Northern region, while the existing University College, Ibadan was granted full-fledged University status in1962.

Also, the University of Lagos, Akoka came into existence in 1962 and as a city University, it provided courses in law, social sciences, medicine, humanities, engineering and part-time programmes for working students.

Lastly, the University of Benin was established in 1970, making it the sixth of the universities that have come to be known as Nigeria’s first generation universities (Adesina, 1988).

Today the higher education system in Nigeria is composed of universities, polytechnics, institutions of technology, colleges of education that form part of, or are affiliated to, universities, and professional, specialized institutions.

They can be further categorized as private, state or federal owned institutions.

REFERENCES

Adebiyi, A.B. (2006). A Web Based Model for Joint Admissions and MatriculationBoard (JAMB) Students Admission Placement. Unpublished M.Tech. Thesis.Federal University of Technology, Akure, Nigeria.
Adewale, O. S. (2006). University Digital Library: An Initiative to Improve Research,Teaching and Service. Adeyemo Publishing House, Akure, Nigeria, pp.134-142.
Anderson, D. and McNeil, G. (1992). Artificial Neural Networks Technology, Data &Analysis Center for Software. Rome, NY 13441-4909. [email protected]
Anderson, James A. (1986). Cognitive Capabilities of a Parallel System, SpringerVerlag.
Ashby D. and Kumar N. (1996). A Comparison of Neural Networks and ClassicalDiscriminant Analysis in Anticipating Default Among High-Yield BondsAssociation for Information Systems, Americas Conference [On-line], 1-4.http://hsb.baylor.edu/ramsower/ais.ac.96/papers/ashby.htm
Barinaga, M. (1990). Neuroscience Models the Brain, Science 247, pp 524-527
Bijayananda, N. and Srinivasan, R. (2004). Using Neural Networks to Predict MBAStudent Success, College Student Journal, March pp 1-7
Brown, Robert J. (1987). An Artificial Neural Network Experiment, Dr. Dobbs Journal.
Carbone, V. and Piras, G. (1998). Palomar project: Predicting School RenouncingDropouts, Using the Artificial Neural Networks as a Support for EducationalPolicy Decisions. Substance Use and Misuse 3, 717-750

StudentsandScholarship Team. 

Be the first to comment

Leave a Reply

Your email address will not be published.


*