<abstract xmlns="http://www.w3.org/1999/xhtml"><p>A model for prediction of the outcome indicators of e-Learning, based on Balanced ScoreCard (BSC) by Neural Networks (NN) is proposed. In the development of NN models the problem of a small sample size of the data arises. In order to reduce the number of variables and increase the examples of the training sample, preprocessing of the data with the help of the methods Interpolation and Principal Component Analysis (PCA) is performed. A method for optimizing the structure of the neural network is applied over linear and nonlinear neural network architectures. The highest accuracy of prognosis is obtained applying the method of Optimal Brain Damage (OBD) over the nonlinear neural network. The efficiency and applicability of the method suggested is proved by numerical experiments on the basis of real data.</p></abstract>

A model for prediction of the outcome indicators of e-Learning, based on Balanced ScoreCard (BSC) by Neural Networks (NN) is proposed. In the development of NN models the problem of a small sample size of the data arises. In order to reduce the number of variables and increase the examples of the training sample, preprocessing of the data with the help of the methods Interpolation and Principal Component Analysis (PCA) is performed. A method for optimizing the structure of the neural network is applied over linear and nonlinear neural network architectures. The highest accuracy of prognosis is obtained applying the method of Optimal Brain Damage (OBD) over the nonlinear neural network. The efficiency and applicability of the method suggested is proved by numerical experiments on the basis of real data.

Prediction of e-Learning Efficiency by Neural Networks

Institute of Information and Communication Technologies, 1113 Sofia

Cybernetics and Information Technologies

{"article-title":"Prediction of e-Learning Efficiency by Neural Networks"}

A model for prediction of the outcome indicators of e-Learning, based on Balanced ScoreCard (BSC) by Neural Networks (NN) is proposed. In the development of NN...

Prediction of e-Learning Efficiency by Neural Networks

Online veröffentlicht: 16. März 2013

Seitenbereich: 98 - 108

DOI: https://doi.org/10.2478/cait-2012-0015

Schlüsselwörter
e-Learning efficiency, Balanced ScoreCard, Neural Networks

This content is open access.

Prediction of e-Learning Efficiency by Neural Networks

Online veröffentlicht: 16. März 2013

Seitenbereich: 98 - 108

DOI: https://doi.org/10.2478/cait-2012-0015

Schlüsselwörtere-Learning efficiency, Balanced ScoreCard, Neural Networks

This content is open access.

Schlüsselwörter
e-Learning efficiency, Balanced ScoreCard, Neural Networks