Abstract
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.
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Kalyani, B.S., Harisha, D., RamyaKrishna, V., Manne, S. (2020). Evaluation of Students Performance Using Neural Networks. In: Pandian, A., Ntalianis, K., Palanisamy, R. (eds) Intelligent Computing, Information and Control Systems. ICICCS 2019. Advances in Intelligent Systems and Computing, vol 1039. Springer, Cham. https://doi.org/10.1007/978-3-030-30465-2_55
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DOI: https://doi.org/10.1007/978-3-030-30465-2_55
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