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Prediction of course grades in computer science higher education program via a combination of loss functions in lstm model

In the realm of education, the timely identification of potential challenges, such as learning difficulties leading to dropout risks, and the facilitation of personalized learning, emphasizes the crucial importance of early grade prediction. This study seeks to connect predictive modeling with edu...

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書誌詳細
主要な著者:	Ghazvini, Anahita, Mohd Sharef, Nurfadhlina, Sidi, Fatimah
フォーマット:	論文
言語:	English
出版事項:	Institute of Electrical and Electronics Engineers 2024
オンライン･アクセス:	http://psasir.upm.edu.my/id/eprint/105763/1/Prediction_of_Course_Grades_in_Computer_Science_Higher_Education_Program_via_a_Combination_of_Loss_Functions_in_LSTM_Model.pdf
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