Prediction and Comparative Analysis of Factors Affecting the Mathematical Achievement of Gifted Students With Machine Learning Models

This study aims to determine the factors affecting the mathematical achievement of gifted students studying at science and art centers in Bursa province and to predict this achievement using various machine learning models. In the study, variables, such as demographic information, family structure, study habits, motivation level, technology use, and social activities were analyzed in line with the data collected from 151 students. Methods, such as decision trees, support vector machines, and artificial neural networks, were used by utilizing the fields of educational data mining and learning analytics. The results obtained showed that some variables significantly affected the mathematical achievement of students. The study provides important findings in terms of developing educational policies and individualized teaching strategies.

• Publication year

  2025

• Venue

  International Journal of Adult Education and Technology

• Publication date

  2025-07-07

• Fields of study

  Not labeled

• Identifiers
  DOI 10.4018/ijaet.383672
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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