PREDICTING STUDENT PERFORMANCE
USING FUZZY LOGIC
CHAPTER ONE
INTRODUCTION
1.0 BACKGROUND
TO THE STUDY
The
increasing demand for education in Nigeria especially tertiary education has
been an issue in recent times. Government–owned tertiary institutions as well
as those privately owned do not possess the capacity and manpower needed to
accommodate the growing number of young school leavers hoping to secure
admission into any of these tertiary institutions.
Huang
(2013) posits that predicting and evaluating the academic performances of
students has for a long time now been an interesting and important area of
research in many academic disciplines. Evaluating students’ academic
performances or achievement using the cumulative grade point average (CGPA) as
a pointer is a typical practice in every tertiary academic environment. A high
percentage of fresh students usually find themselves below the minimum grade
point required at the end of their first year.
Lee
(2008) pointed out that having a thorough understanding of a student’s prior
achievement or knowledge is important and will go a long way in helping
academic planners predict the future performance of such student.
Oladipupo
(2012) stressed the importance of predicting and evaluating the academic performances of students. In his survey
carried out in a privately owned university in Nigeria, the percentages of
students below the 2.5 CGPA at the end of the 2007/2008, 2008/2009 and
2009/2010 academic sessions was alarming. This percentage gives a clear view of
the declining nature of students’ academic performances in our tertiary
institutions.
Thus
predicting and evaluating students’ performances cannot be over-emphasised as
it is a useful tool for academic planners, educators and students alike, as it
gives an actual understanding of students’ weaknesses and proffer solutions.
Fuzzy
logic is an extended branch of Boolean logic and a unique form of logic that
deals with reasoning which is approximate other than fixed or exact and
recognizes more than the simple true/false values. It is also a way of
knowledge representation that is understandable to a computer. Fuzzy logic is a
special type of logic in which a statement can be represented with degrees of
truthfulness or falsehood. Zadeh (1996) describe fuzzy logic as computing with
words in a way that words or linguistic variables are used to replace numeric
values for reasoning and computing.
Zadeh
(1996) also buttressed the importance of fuzzy logic and its usage when the
data available is uncertain or imprecise to warrant the use of numbers or exact
values and also when imprecision can be tolerated. Fuzzy logic due to its
ability to handle imprecision and uncertainty has found its application in
numerous fields of study.
The
application of fuzzy logic in predicting and evaluating students’ academic
performances gives effective and attainable solutions as the knowledge of fuzzy
logic is suitably required when human evaluation is needed. Furthermore,
researches show that fuzzy logic is a more essential technique to handle
imprecision and uncertainty given that evaluating the prior knowledge or past
achievements of students with the aim of discovering the risk of students’
failure involves dealing with uncertain and imprecise data.
Therefore,
this project aims at implementing fuzzy logic in predicting students academic
performances as the fuzzy approach is likely to offer an alternative way of
handling imprecise data, especially in decision making.
1.1
STATEMENT
OF THE PROBLEM
The
inability of Nigerian graduates to cope well in any working environment they
find themselves has for long now raised a lot of concerns. This has been
attributed to the inadequacies and flaws in the universities admission process.
The criteria for students intake is no longer clearly defined hence the aim of
admitting suitably qualified candidates who are likely to perform better both
in school and in the real world after school has been defeated.
Obielumani
(2008) pointed out that due to the multi-ethnic nature of the country and the
increasing demand for quality education, the Nigerian federal government
introduced the quota system to enhance the increasing access to admission
opportunities for candidates who are from disadvantaged states in the country.
The
quota system has been defeated as lobbying, bribery and the likes have created
a flaw in the university admission process and the criteria for student
selection is not specified and thus the rightfully qualified students are
neglected.
In
essence, evaluating students’ academic performances is based on the CGPA and is
a regular practice in every tertiary institution. Most institutions consider a
CGPA of 3.5 and above as an indicator of good performance. Sansgiry (2006)
stated that the CGPA remains the most well-known factor or variable used by
academic planners to assess progression in an academic environment. Various
factors that have a likelihood of affecting students performances have been
identified but despite its limitations in providing a clear view of the state
of a student’s performance, the CGPA is just about the main instrument or factor
that academicians use in evaluating students academic performances.
This
project suggests that there is a need to combine other factors to predict the
future performances of students, the end of first year performances to be
precise, in order to enhance the evaluation of students admitted into tertiary
institutions.
1.2
AIM
AND OBJECTIVES
This
project aims at predicting the end of first year performances of students using
Fuzzy Logic based on previous or prior academic achievements presented during
admission process.
The
objectives of the study are;
1. To
model a Fuzzy Inference System (FIS).
2. To
predict the CGPA of students using the Fuzzy Inference System (FIS).
3. To
use the predicted CGPA as a yardstick for student performance evaluation.
1.3
SIGNIFICANCE
OF THE STUDY
With
the increasing competition among higher institutions of learning to admit
outstanding students, and with the limited space but highly competitive nature
of admission process, more attention is on how to grant admission to only the
best students and increase student retention rates and academic performance as
well as producing quality graduates that can cope in any working environment
and also the number of degree completion.
Also,
there is a growing interest and concern about the problem of poor performance
and school failure and the determination of its main contributing factors. So
far, there is limited number of researches which examine the influence of these
contributing factors on first year academic performances of students in
tertiary institutions.
This
project focuses on designing a predictive system framework using fuzzy logic to
serve as a basis for policy planners to predict and therefore evaluate the end
of 100 level performances of students admitted into tertiary institutions based
on their previous academic achievements.
1.4
SCOPE
OF THE STUDY
This
project is covers the use of fuzzy logic in predicting student academic
performance. That is, developing a model or framework of predictive system by
identifying the most suitable factors to predict end of first year performances
of prospective students which will then be used as a yardstick for student
performance evaluation, since reports show that Fuzzy Logic technique is an
important technique in handling imprecision and uncertainty.
1.5 LIMITATIONS
OF THE STUDY
This
work is intended to tackle and solve problems related to predicting end of
first year academic performance using fuzzy logic based on previous or prior
knowledge or academic achievements presented during admission or registration
process. It is limited to considering four factors only in modelling a fuzzy
inference system for predicting CGPA of students. These factors considered are
student’s mode of entry, UTME score, secondary school result and students age
at entry.