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Design and implementation of a webbased university admission and placement neural network model

 

Table Of Contents


  • 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

  • – Introduction
  • 1.1Background to the study and Statement of the Problem ………………….1
  • 1.2Research motivations ……………………………………………………..7
  • 1.3Research objectives ………………………………………………………10
  • 1.4Research methodology ……………………………………………………….10
  • 1.5Limitations to the study ………………………………………………………11
  • 1.6Contributions to knowledge ………………………………………………11
  • 1.7Organization of the Thesis ……………………………………………….13

Chapter TWO

LITERATURE REVIEW

  • – Literature Review
  • 2.1Artificial neural networks ………………………………………………..14 10
  • 2.2Electronic implementation of Artificial ………………………………….23
  • 2.3Structure of an artificial neural networks …………………………………25
  • 2.4Training an artificial neural network ……………………………………..28
  • 2.5Network architectures …………………………………………………….33
  • 2.6Related works …………………………………………………………….36
  • 2.7Discriminant analysis …………………………………………………….43

Chapter THREE

SYSTEM DESIGN AND IMPLEMENTATION

  • – System Analysis and Modelling
  • 3.1The student selection problem ……………………………………………46
  • 3.2The model ………………………………………………………………..48

Chapter FOUR

SYSTEM TESTING AND EVALUATION

  • – System Design and Implementation
  • 4.1Software Platform for implementation …………………………………..57
  • 4.2The University Admission And Placement System Design ……………..63
  • 4.3System Implementation ………………………………………………….75
  • 4.4System Requirements ……………………………………………………76

Chapter FIVE

SUMMARY, CONCLUSION AND RECOMMENDATIONS

  • – Conclusion and Recommendations
  • 5.1Conclusion ……………………………………………………………….84
  • 5.2Recommendations ……………………………………………………….85 References ……………………………………………………………………….86 Appendix A………………………………………………………………………96 11 LIST OF TABLES Table 2.5: Network selector table Table 4.1: UME admission requirements table Table 4.2: O/L admission requirements table Table 4.3: Candidate JAMB UME subjects table Table 4.4: Candidate O/L first sit table Table 4.5: Candidate O/L second sit table Table 4.6: Admission Results Table

Thesis Abstract

Every year the number of applicants seeking admission into Nigerian Universities
increases by leaps and bounds although the Universities lack the commensurate
facilities 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 procedures involved are very
cumbersome, time consuming and prone to a lot of human errors and irregularities.
Many candidates miss out on the 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 course, 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 the 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, the 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
universities, 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 self-screening admission system.
8
The system design, implementation and results are presented in chapter four. The
implementation was based on AMP (Apache, MySQL, and PHP) open source solutions.

 

 


Thesis Overview

<p> </p><p>INTRODUCTION<br>1.1 Background to the Study and Statement of the Problem<br>Higher education in Nigeria can be traced to 1932 when Yaba Higher College<br>was established for the purpose of producing assistants who would relieve the<br>then colonial administrators of menial tasks. Thus in 1940, the University<br>College, Ibadan was established but the programmes offered there and then were<br>narrow because the agenda of the colonial administration did not include the<br>training of high-level manpower for many of the professions. The Ashby<br>Commission in 1960, recommended the establishment of regional universities in<br>the then three regions of Nigeria. Three universities were established: the<br>University of Nigeria, Nsukka (1960) in the Eastern region; the University of<br>Ife, now Obafemi Awolowo University (1961) in the Western region and<br>Ahmadu Bello University, Zaria (1962) in the Northern region, while the<br>existing University College, Ibadan was granted full-fledged University status in<br>1962. Also, the University of Lagos, Akoka came into existence in 1962 and as<br>a city University, it provided courses in law, social sciences, medicine,<br>humanities, engineering and part-time programmes for working students. Lastly,<br>the University of Benin was established in 1970, making the sixth of the<br>Universities that have come to be known as Nigeria’s first generation<br>Universities (Adesina, 1988).<br>Today the higher education system in Nigeria is composed of universities,<br>polytechnics, institutions of technology, colleges of education that form part of,<br>or are affiliated to, universities, and professional, specialized institutions. They<br>can be further categorized as private, state or federal owned institutions. Federal<br>14<br>universities categorized as first, second, or third generation universities, are<br>owned and funded by the federal government, while state universities are owned<br>and financed by the states (there are 36 states in all), and private universities are<br>owned and funded by individuals or religious organisations. As seen from<br>above, the first generation universities are the six universities established in the<br>1960s and early 1970’s; second generation universities are seven universities<br>established in the mid 1970’s; while third generation universities refer to the<br>eleven institutions, including the universities of technology, established in the<br>1980’s and 1990’s (Hartnett, 2000).<br>According to the National Universities Commission (NUC)’s report on the<br>results of the November 2005 System-Wide Accreditation Exercise, there are<br>twenty-five (25) federal universities including three (3) universities of<br>agriculture, twenty (20) state universities, twenty (23) private universities, five<br>(5) degree-awarding colleges of education, sixty-nine (69) National Certificate<br>in Education (NCE) – awarding colleges of education, one (1) military<br>university, four (4) inter-university centres. This gives a total of one hundred<br>and forty-two (142) higher education institutions excluding the polytechnics and<br>the ten (10) newly approved private universities in 2006.<br>Higher education in Nigeria can be further divided into the public or private, and<br>the university or non-university sectors. Public universities, owned by the<br>federal and state governments, dominate the higher education system. The nonuniversity<br>sector is composed of polytechnics, institutions of technology,<br>colleges of education, and professional institutions. There is no sharp distinction<br>between the university and the non-university sectors; most of the institutions in<br>the latter sector are affiliated with universities.<br>15<br>1.1.2 Access to Higher Education in Nigeria<br>There are three levels of university education in Nigeria. The university level<br>first stage offers a Bachelor’s degree after a minimum of three years and a<br>maximum of six years study (e.g. in medicine). The university level second<br>stage offers a Master’s degree following one year of post-Bachelor’s study or<br>one of post-graduate diploma study and a year of post-Bachelor’s study in the<br>relevant discipline. The university level third stage offers doctorate degree of<br>two to three years duration after the Master’s degree. To gain admission into the<br>first level of university education, a potential student has to pass the competitive<br>University Matriculation Examination (UME).<br>In Nigeria and in fact most nations of the world, the University is the highest<br>citadel of learning for the production of high-level human resources for the<br>labour market. In recognition of this and the role of higher education in<br>perpetuating national unity, the Federal Government of Nigeria took appropriate<br>steps to ensure equity with regard to access to university education. The Joint<br>Admissions and Matriculation Board (JAMB) was created by Act No. 2 of 1978<br>of the Federal Military Government (JAMB, 2004). The main aim for the<br>establishment of the Joint Admissions and Matriculation Board (JAMB) was to<br>provide an opportunity for eligible Nigerians to have access to university<br>education, and to diversify the intakes, and achieve a high rate of national spread<br>in the placement of applicants into Nigerian universities (JAMB, 2004). In<br>addition, the JAMB was to place suitably qualified candidates into the existing<br>tertiary institutions after taking into account the vacancies available in each<br>tertiary institution. Placement was to be done on the basis of merit, catchment<br>16<br>area, and with a special focus on females and the Educationally Less<br>Advantaged States (Omoike and Aluede, 2007).<br>The Federal Government controls the universities and other higher education<br>institutions through the following organs: the Federal Ministry of Education; the<br>National Universities Commission, which among other things allocates funds to<br>federal universities and also prescribes the spending formula; and the Committee<br>of Vice Chancellors of Nigerian Universities, which acts as a coordinating body<br>and offers advice to government and universities’ governing councils on matters<br>of general and specific concern to higher education.<br>Individual university administration is the joint responsibility of the university’s<br>Governing Council and the Senate. Although the Governing Council remains<br>the highest policy-making body in the university, an appointed Vice-Chancellor<br>acts as the Chief Executive Officer, coordinating both academic and<br>administrative functions. Within universities and colleges, the institutes and<br>centers are more or less autonomous. The university system polity consists of<br>three distinct categories of staff viz: administrative, academic and technical,<br>each having a union that protects the interest of members. For instance, the<br>Academic Staff Union of Universities (ASUU) safeguards the interests of the<br>academicians in the Nigerian university system. Most universities operate the<br>semester system, where a session comprises of two semesters. The university<br>academic year begins in October and runs through to July.<br>The Federal Government in order to make education relevant to the needs and<br>aspirations of the people and so bring about the desired development reviewed<br>her educational system by introducing the 6-3-3-4 system of education<br>17<br>(Maduewesi and Imhanlahimi, 2006). By this system, before reaching university<br>entrance level, students undertake 12 years of school education, the first six<br>years of which are spent at primary school while the remaining six years are<br>split between junior and senior secondary school education. Then the last four<br>years of the education system are spent on an average four–year course in the<br>university.<br>Generally, students are 18 years old at the start of their university education,<br>though some students are able to gain admission at the younger age of 16.<br>Students may be admitted into the first year of a four-year degree course based<br>on results achieved in the Universities Matriculation Examination (UME)<br>conducted by the Joint Admissions and Matriculation Board (JAMB). Entrance<br>to the first year of a three-year programme is based on results obtained in the<br>West African School Certificate (WASC) O level, in addition to either the<br>General Certificate of Education (GCE) A level, or equivalent examinations<br>such as the Interim Joint Matriculation Board Examination (IJMBE), and the<br>National Diploma (ND) certificates.<br>Admission is through the Joint Admissions and Matriculation Board (JAMB) for<br>both UME and direct entry applicants. For UME, interested applicants purchase<br>the JAMB form and subsequently write the University Matriculation<br>Examination (UME). Based on the score profile of applicants and the<br>recommended enrolment figure for the admission year, a minimum cut-off score<br>is usually proposed for UME admissions. For instance, for the 2005/2006<br>session, a total enrolment figure was proposed as follows: ARTS (2139) and<br>18<br>SCIENCE (3210) for Ahmadu Bello University, and the proposed merit cut-off<br>score was 234 for that session.<br>1.1.3 Statement of the Problem<br>As stated in the preceding section, the Joint Admissions and Matriculations<br>board has the responsibility of placing suitably qualified candidates into<br>Nigerian tertiary institutions after taking into account the vacancies available in<br>each institution. However, the records show that well over 500,000 candidates<br>seek placements into universities annually in Nigeria and only about 13% (on<br>approximation) of them secure admission, which is a far cry from the target.<br>Admission decisions are made by educational institutions by considering a<br>variety of factors. Some of the evaluation criteria normally used are: JAMB<br>UME subject combination; university’s admission requirements; overall scores<br>in JAMB UME results; UME merit cut-off score; five credits obtainable in ‘O’<br>level certificate (in not more than two sittings); catchment area considerations;<br>and educationally less developed states (elds) considerations. In 2006, the Post<br>UME criterion was introduced whereby, a potential candidate having sat and<br>passed the JAMB UME, is examined by his/her University of choice. The Post<br>UME criterion further narrow down or increases the chances of the candidates<br>being selected and placed in the course of their choice or any available course.<br>Faced with all the multiple criteria as stipulated above, the admission officer<br>manually evaluates every candidate’s data against the various admission<br>19<br>requirements before taking admission and placement decisions. This process is<br>quite cumbersome and highly not cost-effective in terms of cost and processing<br>time. Also, as with every manual process, it is fraught with inaccurate decisions<br>resulting from avoidable human processing errors and at times deliberate<br>manipulations to achieve some unwholesome personal aims like admitting<br>unqualified candidates who has personal affiliations with the admission officer.<br>The inherent problems with the manual system of admission gave rise to the<br>need for development of a computerised model that can be used to carry out the<br>admission procedures with a view to:<br>(a) reducing to the barest minimum the admission processing cost and time<br>in terms of man-hours<br>(b) removing all elements of human errors be they intentional or<br>unintentional<br>(c) streamlining admission processing work<br>(d) making admission decisions more objective and impartial<br>(e) admitting only qualified candidates and<br>(f) providing a self-screening and evaluation mechanism for candidates.<br>1.2 Research Motivations<br>Every year more than 500,000 applicants seek placement to universities. Of<br>these applicants only about 13% are selected for admission. That shows that a<br>large number of these candidates miss out on the opportunity of being admitted<br>into the Universities and, for some candidates, this trend continues for many<br>years leading to frustrations.<br>20<br>This problem has remained difficult to surmount because, for any admission and<br>placement process, several admission criteria are considered and the candidates’<br>data would have to be manually evaluated against the various admission<br>requirements by each university’s admission officer before selecting the few<br>qualified candidates. And this is not an easy task.<br>Every Nigerian that seeks admission into the University must have one thing or<br>the other to do with one of the following agencies:<br>i. Joint Admission and Matriculation Board (JAMB);<br>ii. West African Examination Council (WAEC);<br>iii. National Examination Council (NECO);<br>iv. National Teacher’s Institute (NTI);<br>v. Interim Joint Matriculation Board (IJMB).<br>Adebiyi (2006) developed a web-based model for JAMB candidates’ admission<br>and placement into Nigerian Universities. In addition to the general admission<br>requirement of five ‘O’ level credits in not more than two sittings, Adebiyi, in<br>his model, took into consideration other admission requirements such as UME<br>subject combination and total score requirements, and University’s course<br>subject combination requirements as the criteria for admission and placement.<br>His model also presented an opportunity for students self – screening admission<br>system.<br>21<br>The model however, did not take into consideration candidates that get<br>University placement based on variables such as catchment areas and those from<br>educationally less developed states (elds). Since these variables are part of the<br>standard criteria in the University admission and placement process in Nigeria,<br>Adebiyi’s model would deny admission and placement to many candidates who<br>these variables are meant to favour.<br>This study therefore makes an improvement on the model presented by Adebiyi<br>(2006). This is achieved by the development of a web-based model that takes<br>into consideration admission requirements other than those considered by his<br>model. These admission requirements include:<br>a. UME subject combination and total score requirements,<br>b. University’s course subject combination requirements,<br>c. ‘O’ level subject combination and credit pass requirements,<br>d. Post UME requirements,<br>e. Candidates from the University’s catchment area, and<br>f. Candidates from the educationally less developed states.<br>In this era of modern computer technology and information science,<br>sophisticated information systems can be built to make decisions or predictions<br>based on information contained in available past data. Such systems are called<br>learning systems and are currently used for the purpose of classification and<br>prediction. A student data evaluation approach based on neural networks was<br>described in his dissertation (Sheel et. al., 2002). This was used to determine the<br>placement of university students into basic mathematics courses. The existing<br>22<br>approach used the results of a mathematics placement examination given to<br>incoming freshmen to determine course placement, but the study suggested<br>neural networks to be suitable alternatives to such examinations.<br>1.3 Research Objectives<br>The objective of this study is to develop and implement a web-based model for<br>the Admission and Placement of Potential Students into Nigerian Universities.<br>The model evaluates potential students’ data against University admission<br>requirements thereby streamlining and automating the processing work involved<br>in student admission and placement procedures. In addition, the model will<br>provide candidates with an opportunity to perform self-screening and personally<br>evaluate their chances of gaining admission and placement into the Universities<br>of their choice.<br>1.4 Research Methodology<br>A review of related literature is made along with a few related works, and a webbased<br>admission and student placement process model was developed. The<br>technological approach to the implementation was based on open source<br>solutions. The system requirement in terms of software and hardware includes a<br>web server, which is apache extended with support for PHP and MySQL<br>relational database.<br>In recognition of the sensitivity of the data contained in the system,<br>communications over the public network are protected with open-ssl library for<br>data encryption and authentication and role-based authorisation was built into<br>23<br>the system to specify access rights to the database system. System testing was<br>carried out succinctly with real test data which were obtained from the faculty of<br>science of the Ahmadu Bello University, Zaria. Also, as a follow up to the testrunning<br>and subsequent debugging of the system, the system was implemented.<br>At the end of it all, potential students should be able to go on the relevant<br>University’s website and verify whether they qualify for admission and<br>placement into that University. This is self-screening.<br>1.5 Limitations to the Study<br>Some limitations to this study are identified in the area of time-constraint and<br>physical restriction to real data. Due to the volume of work involved in this<br>study, much time is needed to design the model, develop the program code, testrun,<br>debug and fully implement the new system, than is available for the period<br>of this study. Other limitations include the unavailability of constant electric<br>power supply, the erratic nature of Internet connectivity in most parts of the<br>country, and the training and retraining of dedicated staff who will monitor the<br>system.<br>1.6 Contributions to Knowledge<br>By the development of this Web-based Admission and Placement model,<br>potential candidates’ data are evaluated against the university admission<br>requirements and the most qualified candidates are thereby selected. The new<br>system has tremendous contributions to knowledge, as seen below:<br>(i) government’s policy to promote higher education, learning and research<br>is realised since the automated system frees a lot of man-hours to staff<br>24<br>involved in the cumbersome, time-consuming admission process, and,<br>the recovered time can be gainfully employed in capacity building.<br>(ii) many more people now have fair opportunity to increase in knowledge<br>because, when candidates fail to meet some of the admission<br>requirements for their first course, the automated system automatically<br>considers such candidates for placement into any other course for which<br>they meet the requirements, provided there are vacant positions.<br>(ii) a time-efficient, detailed and unbiased automated procedure for selecting<br>the most qualified candidates for admission into universities is put in<br>place and most (if not all) of the bottlenecks that is rife with the current<br>time consuming and error-prone manual admission and placement<br>processes becomes history.<br>(iii) the prevalence of cheating is reduced and hard work is encouraged<br>through the student self-screening admission system .<br>(iv) University admission and placement is made more reliable and this goes<br>to reduce the tendency to corrupt practices even in the larger society.<br>(v) since it provides better admission opportunity for qualified candidates,<br>better qualified graduates will now be turned out into the job market as<br>opposed to the output that comes from persons who struggle through the<br>universities because they were never qualified to be there in the first<br>instance.<br>(vi) with qualified candidates admitted, lecturers have more time on their<br>hands for research which ultimately increases knowledge in all<br>ramifications, since they do not have to over labour themselves to impart<br>25<br>knowledge to students who do not possess the aptitude for university<br>education.<br>1.7. Organization of the Thesis<br>This report is divided into five (5) chapters. In chapter one, a general introduction and<br>background of the study is given, stating the problem, research motivations, objective,<br>methodology, scope of the research and its contributions to knowledge.<br>Chapter two presents a review of various literature in the field of artificial neural<br>networks and some related works that support this research work.<br>In chapter three, the system analysis and modelling is presented showing a detail of the<br>research methodology.<br>The system design and implementation is contained in chapter four with emphasis on<br>the software platform for the implementation, the system hardware requirements and the<br>results of the implementation.<br>Finally, chapter five presents the conclusion and recommendations from the study.<br>26</p><p>&nbsp;</p> <br><p></p>

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