Study on Prediction System for Student Academic Performance utilizing Educational Data Mining

Main Article Content



Grading students’ academic performance is a more difficult and challenging work
which will help educators to keep track of progress of performance of students. For this the
Educational Data mining (EDM) is a most active and demanding research field. It target is to
finding of useful information from the educational dataset by using data mining techniques.
Most important tasks of EDM are the prediction of the students’ performance. Various
researchers all around the globe have published research work on prediction of students’
performance. EDM plays an important role in the world of business to help the educational
institution for the prediction as well as for make necessary decisions depends on the students’
academic performance. Now a day’s enhancement of students’ performance will affects the
students’ career and also the reputation of the institute The main aim of this review paper is to
explore the methodology developed and used by these researchers and the findings of their
research work in uncomplicated and simplest manner. We presented a comparative study on the
effectiveness from prediction of student’s performance by applying the EDM techniques. The
study results make one important conclusion, which showing that the EDM methods are
adequately effective for prediction of students’ academic performance, and these predictions are
useful to make the necessary decisions and actions by management and teachers.
Teaching-Learning-based Optimization is an optimization technique which does not require
any algorithm-specific parameters and is popular for its less computational cost and high
consistency. Therefore, it has achieved great success application by the researchers in various
disciplines of engineering. It works on the philosophy of teaching and learning which is used to
solve multi-dimensional, linear and nonlinear problems with appreciable efficiency. Recently
the basic TLBO algorithm is improved to enhance its exploration and exploitation capacities
and the performance. However, there is less surveys on TLBO algorithm recent advances and its
application. In this paper, the successful researches of TLBO algorithm of the past decade are


Download data is not yet available.


Metrics Loading ...

Article Details

How to Cite
NILESH V. INGALE, DR. M. SIVAKKUMAR , DR.VARSHA NAMDEO. (2021). Study on Prediction System for Student Academic Performance utilizing Educational Data Mining. Turkish Journal of Computer and Mathematics Education (TURCOMAT), 11(3), 1273–1281.
Research Articles