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Journals / Journal of Engineering and Technology / 2019 / Cilt: 3 - Sayı: 1

Predicting Factors Affecting PISA 2015 Mathematics Literacy via Radial Based Artificial Neural Network

Özlem BEZEK GÜRE
Murat KAYRİ
Fevzi ERDOĞAN
Pages
1–11
Publication Date
2019-05-23
DOI
—
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

According to the results of the study, the correct classification rate of mathematics achievement in the radial based artificial neural network model was found to be 85.2%.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:In this study, using Radial Based Artificial Neural Networks (RBANN) method, one of the methods of data mining, it is aimed to determine the factors affecting PISA 2015 Mathematics literacy.
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Key Findings & Data:Mathematics literacy scores, which were made in categorical form with three level dependent variables, and 25 independent variables, considered to have affected the dependent variables, were used in the study.
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Conclusion & Impact:According to the results of the study, the correct classification rate of mathematics achievement in the radial based artificial neural network model was found to be 85.2%.
🔬Design:Modeling & Simulation
📍Scope:2015 Verileri
⚙️Variables:PISA · Data Mining · Radial Based Artificial Neural Networks

Abstract

In this study, using Radial Based Artificial Neural Networks (RBANN) method, one of the methods of data mining, it is aimed to determine the factors affecting PISA 2015 Mathematics literacy. Mathematics literacy scores, which were made in categorical form with three level dependent variables, and 25 independent variables, considered to have affected the dependent variables, were used in the study. Also, in order to determine factors affecting PISA 2015 Mathematics literacy, information obtained from a total of 4422 students, 2165 (49%) of whom were males and 2257 (51%) of whom were females, participating in the exam was used in this study. According to the results of the study, the correct classification rate of mathematics achievement in the radial based artificial neural network model was found to be 85.2%. In addition, it is seen that the most important factor affecting Mathematics literacy was Turkish language success status, and that the other variables setting significance, respectively, are targeted point in school life, father education level and mother education level.

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Cite This Article

GÜRE, Ö. B., KAYRİ, M., ERDOĞAN, F. (2019). Predicting Factors Affecting PISA 2015 Mathematics Literacy via Radial Based Artificial Neural Network. Journal of Engineering and Technology, Cilt: 3 - Sayı: 1, 1–11. https://ajindex.com/articles/835593

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