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Mining the education domain

An article by Jayan C Kurian & Blooma Mohan John

Nowadays, in an educational institution, every minute brings in hundreds of electronic documents that are added to traditional databases.

These electronic databases that stores studentsí information, teachersí information, and class and schedule information, are large and complex, and are expected to grow over the coming years.

Each one of us experiences a mounting frustration in the attempt of finding the information they are looking for in these electronic databases.

Data mining tools provides an innovative solution for extracting useful information from massive databases, automatically, quickly, and easily.

An educational institution has many diverse sources of information like databases containing information about students, teachers, alumni, and contents of various courses etc.

The education domain offers a fertile ground for many interesting and challenging data mining applications.

Few of the challenges the educational institutions face today are to develop new and faster solutions for:

- Defining admission requirements;

- Predicting which student will enroll a particular course;

- Helping students to select courses; Analyzing students skills based on test performance;

- Predicting who will require additional training to graduate;

- Building intelligent tutoring systems;

- Targeting at those alumni, who are more likely to respond;

- Finding courses that are more popular among students, etc.

Data mining has emerged as a highly desirable tool to uncover and understand hidden patterns in vast databases.

It is the process of discovering meaningful new correlations, patterns, and trends from data repositories. It uses pattern recognition technologies, statistical and mathematical techniques to discover new patterns.

Advanced data mining techniques are used to extract useful patterns and built intelligent tutoring systems that can help educators evaluate and interpret studentsí learning skills in order to assess the learning process, track studentsí actions, identifies the areas in which they require further attention and measure the course effectiveness.

The use of computers in teaching/learning process led to the emergence of the so-called Intelligent Tutoring Systems (ITS).

SQL-Tutor an ITS, is a practice environment for undergraduates enrolled in database courses. MFD (Mixed numbers, Fractions, and Decimals) is also an ITS.

These ITS adapts its instruction to meet the needs of each learner by intelligently selecting a topic on which the student should work, providing hits that match the studentís level of ability, and dynamically constructing problems that were appropriate for the student. Data mining techniques have been applied to the construction of student model.

National University of Singapore used data mining applications for classifying and selecting those students who required remedial classes in a given subject.

It is evident that educational institutions can use data mining algorithms and techniques as a powerful analytical tool that enables them to better allocate their resources and staff, to manage student relations, and to enhance the performance of both students and institution.

With the ability to uncover hidden patterns in large databases, the universities, schools and distance education institutions can build models that predict, with high degree of accuracy, the behaviour of their respective population clusters.

By acting on these predictive models, educational institutions can now effectively address thorny issues from learning outcomes, retention and tutoring.

Applications of data mining in academic framework are virtually unlimited. With so much information and so many diverse needs, it is indeed foreseeable that an integrated data mining system that is able to cater for special needs of an educational institution will be of great demand in the future.

Article Contributed By: Jayan C Kurian & Blooma Mohan John

NOTES: Jayan C Kurian is currently a Senior Lecturer (Information Technology Department) lecturing on technological courses at the Modern College of Business and Science, Sultanate of Oman.  The college is affiliated with the University of Missouri Ė St Louis , U.S.A.   His  most recent professional experience is as Subject Matter Expert for the Computing Technology Industry Association, U.S.A.   He is involved in reviewing their e-Business and A+ professional examination. Jayan's initial academic experience was with the School of Information and Communication Technology, Ngee Ann Polytechnic, Singapore.

See also: Is Information-Mode a new beginning?


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15 October 2004