Classification of Students’ Mathematical Literacy Score Using Educational Data Mining: PISA 2015 Turkey Application

Hasan Aykut Karaboğa; Serkan Akogul; İbrahim Demir

doi:10.17776/csj.1136733

EN

Classification of Students’ Mathematical Literacy Score Using Educational Data Mining: PISA 2015 Turkey Application

Abstract

PISA 2015 mathematical literacy score of Turkey is 420 while the average score of all countries is 461. It is understood that; Turkish students’ PISA 2015 mathematical literacy score was lower than the average. The basic reasons for the below average score need to be truly examined and developmental activities should be revealed. The aim of this study is to classify students according to the factors affecting their mathematical literacy score and to reveal the effects of these factors in classification.The data of the study is obtained from 5895 students who participated in PISA 2015. In this study, we used Random Forest, Naïve Bayes Classifier, Logistic Regression, Decision Tree Algorithm and Discriminant Analysis as classifiers. According to the results, Random Forest method produced more accurate scores than other methods with 76.32% accuracy. We also calculated the correct classification rate and determined the factors that positively and negatively affect the classification with discriminant analysis. According to the discriminant analysis home possessions, information and computer technology resources at home and students' expected occupational status were the most positive effective variables on mathematical literacy score. On the other hand, family wealth possessions, student-related factors affecting school climate and anxiety have negative effect on mathematical literacy score.

Keywords

References

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Details

Primary Language

English

Subjects

Statistics

Journal Section

Research Article

Authors

Hasan Aykut Karaboğa
0000-0001-8877-3267
Türkiye

Serkan Akogul ^*
0000-0002-0346-4308
Türkiye

İbrahim Demir
0000-0002-2734-4116
Türkiye

Publication Date

September 30, 2022

Submission Date

June 27, 2022

Acceptance Date

September 12, 2022

Published in Issue

Year 2022 Volume: 43 Number: 3

DOI

https://doi.org/10.17776/csj.1136733

IZ

https://izlik.org/JA26BR47FS

Cite

RIS / Bibtex

APA

Karaboğa, H. A., Akogul, S., & Demir, İ. (2022). Classification of Students’ Mathematical Literacy Score Using Educational Data Mining: PISA 2015 Turkey Application. Cumhuriyet Science Journal, 43(3), 543-549. https://doi.org/10.17776/csj.1136733

Cited By

Teaching Strategies and Student Performance in Combining Mathematics Teaching and Data Mining Techniques in Higher Education

Applied Mathematics and Nonlinear Sciences

https://doi.org/10.2478/amns-2024-2431

Comparison of the Performance of Gradient Boosting and Extreme Gradient Boosting Methods in Classifying Timms Science Achievement

Bitlis Eren Üniversitesi Fen Bilimleri Dergisi

https://doi.org/10.17798/bitlisfen.1636812

Öz

Classification of Students’ Mathematical Literacy Score Using Educational Data Mining: PISA 2015 Turkey Application

Abstract

Keywords

References

Details

Primary Language

Subjects

Journal Section

Authors

Publication Date

Submission Date

Acceptance Date

Published in Issue

DOI

IZ

Cite

Cited By

Teaching Strategies and Student Performance in Combining Mathematics Teaching and Data Mining Techniques in Higher Education

Comparison of the Performance of Gradient Boosting and Extreme Gradient Boosting Methods in Classifying Timms Science Achievement