نوع مقاله : مقاله پژوهشی
نویسندگان
1 استادیار گروه علوم تربیتی، دانشگاه پیام نور مشهد، ایران
2 مدرس گروه علوم تربیتی،دانشگاه فرهنگیان ، مازندران،نوشهر
چکیده
کلیدواژهها
عنوان مقاله [English]
نویسندگان [English]
This study aims to evaluate the efficiency of artificial intelligence models in educational planning and predicting students' academic performance, as well as optimizing personalized learning. A comparison between Artificial Neural Networks (ANN) and Linear Regression (LR) was conducted to identify the optimal model for analyzing educational data.This quantitative research was conducted using an analytical-comparative method. Educational data were extracted from Learning Management Systems (LMS), and both Linear Regression (LR) and Artificial Neural Networks (ANN) were utilized for analysis. Indicators such as the coefficient of determination (R²), Mean Absolute Error (MAE), and Root Mean Square Error (RMSE) were examined to assess the accuracy and generalizability of the models.The findings revealed that the neural network, with a coefficient of determination (R² = 0.88) in the testing phase, exhibited higher accuracy compared to linear regression (R² = 0.75). The neural network was better at identifying complex relationships among educational variables, demonstrating its superior accuracy in predicting students' academic performance and optimizing educational planning.This study demonstrates that artificial neural networks are powerful analytical tools with significant potential for optimizing educational planning processes. However, effective utilization of these models requires sufficient data, optimal configurations, and appropriate computational infrastructure. It is recommended that universities and educational institutions leverage machine learning models for analyzing large-scale educational data and equip educational planning systems with AI-based technologies. Additionally, increasing awareness and training educators about the applications of AI in educational planning and personalized learning can enhance the quality of education and reduce academic dropout rates.
کلیدواژهها [English]
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