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An
article by Jayan C Kurian & Blooma Mohan John
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Nowadays,
in an educational institution, every minute brings in hundreds of electronic
documents that are added to traditional databases.
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These
electronic databases that stores students’ information, teachers’
information, and class and schedule information, are large and complex, and
are expected to grow over the coming years.
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Each
one of us experiences a mounting frustration in the attempt of finding the
information they are looking for in these electronic databases.
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Data
mining tools provides an innovative solution for extracting useful information
from massive databases, automatically, quickly, and easily.
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An
educational institution has many diverse sources of information like databases
containing information about students, teachers, alumni, and contents of
various courses etc.
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The
education domain offers a fertile ground for many interesting and challenging
data mining applications.
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Few
of the challenges the educational institutions face today are to develop new
and faster solutions for:
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Defining admission requirements;
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Predicting which student will enroll a particular course;
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Helping students to select courses; Analyzing students skills based on test
performance;
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Predicting who will require additional training to graduate;
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Building intelligent tutoring systems;
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Targeting at those alumni, who are more likely to respond;
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Finding courses that are more popular among students, etc.
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Data
mining has emerged as a highly desirable tool to uncover and understand hidden
patterns in vast databases.
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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.
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Advanced data mining techniques
are used to extract useful patterns and built intelligent tutoring systems
that can help educators evaluate and interpret students’ learning skills in
order to assess the learning process, track students’ actions, identifies
the areas in which they require further attention and measure the course
effectiveness.
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The use of computers in
teaching/learning process led to the emergence of the so-called Intelligent
Tutoring Systems (ITS).
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SQL-Tutor an ITS, is a practice
environment for undergraduates enrolled in database courses. MFD (Mixed
numbers, Fractions, and Decimals) is also an ITS.
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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 student’s 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.
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National
University of Singapore used data mining applications for classifying and
selecting those students who required remedial classes in a given subject.
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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.
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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.
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By
acting on these predictive models, educational institutions can now
effectively address thorny issues from learning outcomes, retention and
tutoring.
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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.
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Article Contributed By: Jayan
C Kurian & Blooma Mohan John
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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
–
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.
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See also: Is
Information-Mode a new beginning?
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Mining the education domain
