Journal of Educational & Psychological Research(JEPR)

Department of Electrical Engineering, College of Engineering, Al Neelain University, Sudan

Publications

• Research Article   
  Predicting Student Achievement: Exploring Non-Cognitive Feature Interactions Using Machine Learning Models
  Author(s): Khalid Abd El Mageed Elamin*, Bakri Altyeb Musa, Nada Elnasry and Sawsan Al Mekawi
  
  This research investigates how non-cognitive skills can predict student achievement, as measured by GPA. Non-cognitive traits like self-control, goal attainment, interpersonal connections, and leadership skills develop in students at various stages and are influenced, whether positively or negatively, by their environment and social circle. Because non-cognitive features alone are complex and intertwined, feature engineering is needed to create new features that combine these non-cognitive traits with each other or with cognitive features, in order to better predict student success by Analyzing their impact on academic performance at the end of the year. Various machine learning models including linear regression, gradient boosted regression model, random forest and XGBoost were employed and developed to assess the impact of these features. An important part of our approach includes f.. Read More»
  

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