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Erschienen in:
Motion-Specialized Deep Convolutional Descriptor for Plant Water Stress Estimation Kapitel lesen Erstes Kapitel lesen

2017 | OriginalPaper | Buchkapitel

DSS-PSP - A Decision Support Software for Evaluating Students’ Performance

verfasst von : Ioannis E. Livieris, Konstantina Drakopoulou, Thodoris Kotsilieris, Vassilis Tampakas, Panagiotis Pintelas

Erschienen in: Engineering Applications of Neural Networks

Verlag: Springer International Publishing

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Abstract

Prediction, utilizing machine learning and data mining techniques is a significant tool, offering a first step and a helping hand for educators to early recognize those students who are likely to exhibit poor performance. In this work, we introduce a new decision support software for predicting the students’ performance at the final examinations. The proposed software is based on a novel 2-level classification technique which achieves better performance than any examined single learning algorithm. Furthermore, significant advantages of the presented tool are its simple and user-friendly interface and that it can be deployed in any platform under any operating system.

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Vorheriges Kapitel Memristor Based Chaotic Neural Network with Application in Nonlinear Cryptosystem
Nächstes Kapitel Predicting Student Performance in Distance Higher Education Using Active Learning
Fußnoten
1
The tool is available at http://​www.​math.​upatras.​gr/​~livieris/​DSSPSP.​zip. Notice that Java Virtual Machine (JVM) 1.2 or newer is needed for the execution of the program.
 
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Metadaten
Titel
DSS-PSP - A Decision Support Software for Evaluating Students’ Performance
verfasst von
Ioannis E. Livieris
Konstantina Drakopoulou
Thodoris Kotsilieris
Vassilis Tampakas
Panagiotis Pintelas
Copyright-Jahr
2017
Buch
Engineering Applications of Neural Networks

Print ISBN: 978-3-319-65171-2

Electronic ISBN: 978-3-319-65172-9

Copyright-Jahr: 2017

DOI
https://doi.org/10.1007/978-3-319-65172-9_6