Artificial Intelligence in Education Predicting College Plans of High School Students

Authors

  • AWS ABU EID Arab Apen University-JORDAN
  • Wahida A. Mansouri
  • Achraf Ben Miled https://orcid.org/0000-0003-1256-2900
  • Majid A. Nawaz Majid A. Nawaz
  • Ahlem_Fatnassi f
  • Ashraf F. A. Mahmoud A. Mahmoud
  • Faroug A. Abdalla
  • Chams Jabnoun
  • Aida Dhibi
  • Firas M. Allan
  • Mohammed Ahmed Elhossiny
  • Salem Belhaj Belhaj
  • Imen Ben Mohamed
  • Marwa A. I. Elghazawy

Abstract

This study presents a predictive model to forecast high school students' college plans using artificial intelligence. The model, known as AIRPCP (Artificial Intelligence for Educational Planning of College Pursuits), achieves promising performance in predicting students' intentions to pursue college education. Key steps in the model development process, such as data preprocessing, feature engineering, and hyperparameter tuning, are discussed. Advanced techniques using scikit-learn's GridSearchCV for hyperparameter optimization are highlighted. The study emphasizes the importance of these techniques in enhancing the model's predictive accuracy and relevance.

Furthermore, the model demonstrates promising predictive performance, achieving an accuracy rate of 84.88%. Notably, advanced techniques involving scikit-learn's GridSearchCV for hyperparameter optimization are showcased, emphasizing their pivotal role in enhancing the model's predictive precision and relevance. The results underscore the effectiveness of hyperparameter tuning in elevating the model's accuracy, precision, recall, and F1 scores, especially concerning students with college plans. Furthermore, we present visualizations encompassing performance metrics and confusion matrices, facilitating the comprehensive interpretation of the model's outcomes. These visual aids are poised to support educators, policymakers, and researchers make well-informed decisions about high school students' educational aspirations. The AIRPCP model exhibits substantial potential for forecasting high school student's college plans.

Furthermore, the AIRPCP model holds significant implications for the educational sector, offering educators, policymakers, and researchers a means to gain profound insights into high school students' college plans. These insights can lay the foundation for informed decisions to support and nurture students' educational aspirations, thus contributing to educational planning and policy development.

 

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Published

2024-04-02

Issue

Vol. 2 No. 1 (2024): Journal of Intelligent Systems and applied data science (JISADS)

Section

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