Data mining in higher educational institutes in Saudi Arabia

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CHAPTER 1: INTRODUCTION1

Background1

Problem Statement2

Research aims and objectives2

Research Questions3

Significance3

Rationale4

Summary4

CHAPTER 2: LITERATURE REVIEW5

Data Mining Conceptual Framework5

Tasks of Data Mining Process5

Association Rule Learning6

Clustering6

Classification6

Regression7

Summarization7

Data mining models and alogorithms7

Application of data mining in higher educational sector in Saudi Arabia8

Orientation towards Students9

Orientation towards Educators10

Orientation towards administrators and academics responsible10

Benefits of Data Mining11

Summary11

CHAPTER 3: METHODOLOGY12

Research Design12

Literature Search12

Keyword Used13

REFERENCES14

CHAPTER 1: INTRODUCTION

Data mining is an extremely dominant novel technology that has found enormous potential in information systems (Ranjan & Malik, 2007, p. 503). The technique has found applications in several industries. This study focuses on its application in higher educational institutes in Saudi Arabia. Higher educational institutes are the central points of research and development. They act in a competitive environment in order to accumulate, generate and share knowledge (Bresfelean, 2008, p. 1). This research paper carries out an in depth study for mining the educational data and information collected from higher educational institutes in Saudi Arabia. Data mining is a technique in which all the data collected through different applications, events registrations and other databases can be strategically processed to enhance the decision making process (Luan, 2004, p. 2). Data mining has found applications in various fields and businesses. This study focuses on the application of data mining in universities.

The project mainly focuses on the effective utilization of data gathered from different applications to make smart source of useful information for facilitating the decision making process. This is made through implementing the suitable data mining model in order to understand the relationship of the data in the applications used and generate identified and classified information as a distillation data for human judgment.

Background

Data mining has been proven to provide solutions to problems of many industries in which it has been applied. It has helped the industries by extracting useful information such as anomalies, trends, changes, patterns etc. out of the raw data. It has found application in insurance, pharmaceutical, road traffic, motor industries, engineering, food industries, telecommunication, manufacturing, healthcare, retail, banking, financial services and so forth. However, it has not been previously used in the educational sector (Ali, 2013, p. 376). The main objective of high educational institutes is to offer high quality education to its students. One way for achieving such a high quality is to discover knowledge regarding various aspects of the students. This knowledge is hidden in the enormous data sets of the university. This information and knowledge can be extracted using and applying various tools and techniques of data mining on those enormous data sets. Based on the different goals of universities, many questions are required to be asked in order to understand the exact requirements. Questions such as what data do we collect? What information do we currently have? What can help greatly in assessing the organization's goals and specifying what decisions are needed to be made out of the available information? Application of data mining tools on enormous data sets can yield significant results (Baradwaj & Pal, 2011, ...