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Erschienen in:
2009 | OriginalPaper | Buchkapitel
An Expedient Study on Back-Propagation (BPN) Neural Networks for Modeling Automated Evaluation of the Answers and Progress of Deaf Students’ That Possess Basic Knowledge of the English Language and Computer Skills
verfasst von : John Vrettaros, George Vouros, Athanasios S. Drigas
Erschienen in: Best Practices for the Knowledge Society. Knowledge, Learning, Development and Technology for All
Verlag: Springer Berlin Heidelberg
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This article studies the expediency of using neural networks technology and the development of back-propagation networks (BPN) models for modeling automated evaluation of the answers and progress of deaf students’ that possess basic knowledge of the English language and computer skills, within a virtual e-learning environment. The performance of the developed neural models is evaluated with the correlation factor between the neural networks’ response values and the real value data as well as the percentage measurement of the error between the neural networks’ estimate values and the real value data during its training process and afterwards with unknown data that weren’t used in the training process.