Work

Prediction of e-Learning Efficiency by Neural Networks

Year: 2012

Type: article

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.

Source: Cybernetics and Information Technologies

DOI: 10.2478/cait-2012-0015

Author: Petar Halachev

Institutions: Bulgarian Academy of Sciences, Institute of Information and Communication Technologies

Language: English

Topic: Online Learning and Analytics

Subfield: Computer Science Applications

Field: Computer Science

Domain: Physical Sciences

SDG: Quality education

Open Access status: diamond

OpenAlex ID: W2052805932

FWCI: 1.137

Cites: 18

Cited by: 10

Related to: 10