Evaluation of Students Performance Using Neural Networks

被引:3
|
作者
Kalyani, B. Sai [1 ]
Harisha, D. [1 ]
RamyaKrishna, V [1 ]
Manne, Suneetha [1 ]
机构
[1] Velagapudi Ramakrishna Siddhartha Engn Coll, Vijayawada, AP, India
关键词
Convolution neural networks; Academic performance; Predictions;
D O I
10.1007/978-3-030-30465-2_55
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
From Past decades, student performance is considered as an important factor for most of the educational institutions. The performance is evaluated based on various factors that plays a crucial part in the student career. In the recent years, students' performance prediction has become a significant challenge for all the institutions. Modern day educational institutions have adopted continuous evaluation to improve the performance. In the recent years, Neural Networks is used for predictions, which provides better results when compared to the classifiers. The data used for performance prediction will consists of the number of hours the student has spent for studying, his involvement in the academic activities and other contribution factors. These factors will play a crucial role in predicting the performance of the students. Thus, Neural Networks play a key role in predicting the students' performance. In particular, this paper uses Convolutional Neural Networks to predict the performance.
引用
收藏
页码:499 / 505
页数:7
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