The project mainly focused on
developing an application for information extract or retrieval from pool of
data (i.e. a large database) to form basis for decision making. Information
extracted from the database in the course of data mining process can be
presented in graphical format in form of graphs patterns, histogram, etc. and
also in text format. The reason for suggesting the project is the need for
employing computer software medium for sanitizing academic standard through
computer based decision making. Data mining package can present clear reasons
and factor that affects students’ performance and hence allow administrators to
derive strategic means of tackling such issues. The package will be developed
in a .net integrated development environment (.net IDE). The package IDE is
chosen following the fact that extracted information needs to be presented in
an enhanced pictorial/graphical format and easy communication with the database
for program flexibility in windows platform.
TABLE OF CONTENTS
Table of Contents
1.1 GENERAL INTRODUCTION
Statement of the problem
Aims and objectives
Significance of the study
Scope and limitations
Organization of report
Definition of terms/acronyms
2.0 LITERATURE REVIEW
Data mining in higher education
Review of general text
Research and evolution of data mining
Data mining process
Data mining in higher education
3.0 PROJECT METHODOLOGY
3.1. Methods of data
3.2 Description of the
Problems of the existing system
Description of the proposed system
Advantages of the proposed system
Design and implementation methodologies
4.0 DESIGN, IMPLEMENTATION AND DOCUMENTATION
OF THE SYSTEM
Design of the system
4.2 Output design
4.3 Input Design
4.4 Database design
4.5 Procedure Design
of the system
4.6.1 Hardware Support
4.6.2 Software support
of the system
4.7.1 Operating the system
4.7.2 Maintaining the system
Source Program listing
Data mining is
a branch of computer science which deals with the process of extracting
patterns from large data sets by combining methods from statistics and
artificial intelligence with database management. Data mining is seen as an
increasingly important tool by modern business to transform data into business
intelligence giving an informational advantage. It is currently used in a wide
range of profiling practices, such as marketing, surveillance, fraud detection,
and scientific discovery. (Clifton, 2010)
The related terms data dredging, data
fishing and data snooping
refer to the use of data mining techniques to sample portions of the larger
population data set that are (or may be) too small for reliable statistical
inferences to be made about the validity of any patterns discovered. These
techniques can, however, be used in the creation of new hypotheses to test
against the larger data populations. (Clifton, 2010)
Performance monitoring involves assessments
which serve a vital role in providing information that is geared towards
helping students, teachers, administrators, and policy makers to take
decisions.(Counsil, 2001) The changing factors in contemporary education has
led to the quest to effectively and efficiently monitor students’ performance
in educational institutions, which is now moving away from the traditional
measurement and evaluation techniques to the use of Data Mining Techniques
which employ various intrusive data penetration and investigation methods to
isolate vital implicit or hidden information. Due to the fact that several new
technologies have contributed and generated huge explicit knowledge, causing
implicit knowledge to be unobserved and stacked away within huge amounts of
data. The main attribute of data mining is that it subsumes Knowledge Discovery
which according to Frawley (1991) is a nontrivial process of identifying valid,
novel, potentially useful and ultimately understandable patterns in data
processes, thereby contributing to predicting trends of outcomes by profiling
performance attributes that supports effective decisions making. This project
deploys theory and practice of data mining as it relates to students’
performance and monitoring program in Kwara State Polytechnic, Ilorin.
developments and new programming techniques have improved understanding and use
of Artificial Intelligence (AI). The isolation of hidden data and exposed
relationships embedded within it, without a prior knowledge of the nature of
any inherent relationship leading [Rubenking 2001] to assert that data mining
is a logical evolution of database technology with the development of enhanced
query tools such as SQL, database managers are capable querying data more
flexibly. Rules derived from various algorithms during the implementation of
Data Mining Tools in researches, support this opinion.
educational institutions target activities within its organizations with
computer-based tools to handle and store huge data available in educational
processes for hidden patterns. The face value assessment of students at the
point of entry can only be confirmed or dispelled by the dynamic follow-up
monitoring of students’ performance during the course of study leading to serve
as an indicator of the suitability and unsuitability of students before admission
and during their course of study.
Set Theory is used in applications involving educational assessment and
performance as it is regarded as efficient and effective in uncertain
situations involving performance assessment. It is known that Expert Fuzzy
scoring systems noted [Nolan 1998]; help teachers make assessment in less time
and with a level of accuracy that compares favorably to the best teacher examiner.
The package will be developed using dot net frame work(c#) crumple with mysql
database. Graphics will be use in this project work to give a quick view of the
level of performance of student fetching record from the database.
1.2 STATEMENTS OF
ideal goal of higher education is to continually maintain sustainable
increasing graduation rates and growth with the most efficient procedures that
allows for the accounting of input resources. The degree of quality students’
involves the pertinent issue of how to enhance and evaluate it through overt
and covert processes. Hence, Data Mining processes for knowledge is the data
which while dependent on quality, characteristics and preparation, supports and
facilitates the thorough examination of
the data’s different aspects for knowledge discovery in tertiary processes. The
result helps Kwara State Polytechnic, Ilorin to predict the degree of
likelihood of a student’s persistence, learning outcomes in terms of
performance and by using computer-based evaluation tools, meaningful learning
outcome topologies are created using charts and graphical representations.
Other studies have shown that some techniques are particularly beneficial for
the various sub process.
1.3 AIM AND
OBJECTIVES OF THE STUDY
The aim of this project is to design a computer-based
application that summarizes all the qualities of assessment and performance
monitoring of students’ which when expanded holds key information that answers
questions on students’ academic performances. The objectives are as follow:
To observe and compare individual, segmented
and well aggregated students’ performance variables by analyzing the whole
student base activities and then building one predictive model.
To provide a continuous
“Just-In-Time” student performance assessment model for predicting performance
with reasonable degree of accuracy, thereby enhancing monitoring of student
academic pursuance and any other stakeholder’ interests, at any point, for any
student during the student’s tenure at the educational institution.
computer-based modeling process that will be effective and integrate all the
data objects and rules needed for performance prediction allowing for quality
control in the institution,using .netime.
1.4 SIGNIFICANCE OF
Data mining is a system of searching
through large amounts of data. It is a relatively new concept which is directly
related to computer science. Despite this, it can be used with a number of
older computer techniques such as statistics.
There are a number of software
products that have been designed for those who wish to use data mining
techniques. Once you are able to search through large amounts of information,
you will be able to analyze it in a large number of different ways. Once you've
analyzed the information, you can make conclusions and decisions which are
based on logic. While the term data mining is a new concept, the concept of
searching through data for patterns is not. Many large institutions have
powerful computers that allow them to search through information to analyze
reports over a given period of time.
What sets data mining apart from
these older research methods is that data mining is a result of the advancement
of computer processing power. In addition to this, the storage capabilities of
contemporary computers have allowed data mining to be much more accurate than
techniques that were used in the past. Because most data mining tools come in
the form of software, the costs involved with searching and analyzing
information have greatly dropped.
1.5 SCOPE AND LIMITATIONS OF THE STUDY
Data mining in academics needs large
volume of data which analytical conclusions can be drawn from. This project
work focused on developing an application that will take live data of students’
GP per semester and store it in a database. Analysis of Students’ Academic
Performance Monitoring and Evaluation can be drawn from the stored results.
Reports of the performance evaluation can be extracted and categorized by
users’ choice; per semester, session evaluation of students’ performance
grouped by department, institute or the entire polytechnic as a whole.
The proposed system does not take account of
evaluating any factor affecting students’ performance. The system as well is
not target at computing students’ result or function as record keeping software
for students in the institution. Due to difficulties foreseen in covering the
entire polytechnic as a case study for the research, the research coverage is
limited to Institute of Basic and Applied Sciences (IBAS).
1.6 ORGANISATION OF THE REPORT
research work provides efficient way of handling importation and exportation
operation job and sheds more light on how to design software for it. The
project consists of five chapters. The preliminaries contain the title page,
table of contents and abstract.
one contains the introduction of the study, statement of the research problem,
aims and objectives of the study, significance of the study, and the
organization of the report.
two contains the literature review on data mining and its implementation in
academic and students’ performance analysis. It also discusses issues related
to data mining and it is used for academic performance in higher institutions.
three contain analysis of the existing and proposed system, which entails
method employed in gathering facts, analysis and problems of the existing
system, its contain the description of the current system, problems of the
existing system, Description of the proposed system, Advantage of the proposed
system , Disadvantage of the proposed system, implementation techniques and
choice of programming language.
four is basically contains Design implement and Documentation of the system. It
contain output design, input design, file design, procedure design, contain
implementation technique, programming language, Hardware and Software, it
contains document of the system.
five contains the summary, Experience, problem encountered, Recommendation and
1.7 DEFINITION OF TERMS
SQL, often referred to as Structured Query Language, is a
database computer declarative language designed for managing data in relational
database management systems (RDBMS), and originally based upon relational
algebra and topple relational calculus. [http://en.wikipedia.or/wiki/SQL]
Data Mining: Generally, data mining
(sometimes called data or knowledge discovery) is the process of analyzing data
from different perspectives and summarizing it into useful information -
information that can be used to increase revenue, cuts costs, or both.
Decision trees: The term neural network was traditionally used
to refer to a network or circuit of biological neurons. The modern usage of the
term often refers to artificial neural networks, which are composed of
artificial neurons or nodes.
Co linearity: A set of points is collinear (also co-linear or colinear) if they lie on a single straight line or a projective
line (for example, projective line over any field). [http://en.wikipedia.or/wiki/collinearitydata_modelling]
Data Modeling: Data modeling is a
method used to define and analyze data requirements needed to support the
business processes of an organization. The data requirements are recorded as a
conceptual data model with associated data definitions. [http://en.wikipedia.or/wiki/data_modelling]
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