Predicting Students’ Academic Performance in Iranian Schoo

Mostafa Namjoo; Reza Akbari; Syed Mostafa Fakhrahmad

Data mining is the process of extracting valuable and novel knowledge from large data. It is analysis of data sets for finding patterns, relationships and help to summarize the knowledge for various goals. This investigation is motivated to study the students’ academic performance in high schools during 4 years which are collected from the department of education, Shiraz, Iran. Since one of the main challenges in Iranian schools is, prediction of students’ academic performance and their success in university entrance exam, therefore, we applied different classification and prediction algorithms on students’ data for discovering the possibility of predicting students’ scores before examination. Our results show that, it is possible to predict students’ gender, marks with applying classification and prediction algorithms and verifying some factors which are mentioned in this paper.

Select Volume / Issues:

• Volume 5,Issue 3,May 2014

Year:

2014

Type of Publication:

Article

Keywords:

Academic Performance; Prediction; Data Mining; Pattern Recognition; Classification

Journal:

IJECCE

Volume:

5

Number:

3

Pages:

640-643

Month:

May