E-learning Systems Evaluation with Data Envelopment Analysis and Bayesian Networks

Author

Kao, H.-Y. ; Liu, M.-C. ; Huang, C.-L. ; Chang, Y.-C.

Author_Institution

Inst. of Learning Technol., Nat. Dong Hwa Univ., Hualien, Taiwan

fYear

2009

fDate

25-27 Aug. 2009

Firstpage

1207

Lastpage

1210

Abstract

This study uses data envelopment analysis and Bayesian networks in e-learning systems evaluation and classification, respectively. By maximizing the weighted summed-outputs-to-weighted-summed-inputs ratio, we obtain the scores of individual as well as groups of reviewers from relative efficiency perspectives. The efficiencies are used as training data to construct the classification model for further decision and pre-evaluation in e-learning systems performance.

Keywords

belief networks; classification; computer based training; data envelopment analysis; learning systems; Bayesian networks; classification model; data envelopment analysis; e-learning systems classification; e-learning systems evaluation; training data; weighted summed-outputs-to-weighted-summed-inputs ratio; Bayesian methods; Computer industry; Data envelopment analysis; Decision making; Electronic learning; Industrial training; Laboratories; System performance; System testing; Training data; Bayesian networks; data envelopment analysis; elearning systems; evaluation;

fLanguage

English

Publisher

ieee

Conference_Titel

INC, IMS and IDC, 2009. NCM '09. Fifth International Joint Conference on

Conference_Location

Seoul

Print_ISBN

978-1-4244-5209-5

Electronic_ISBN

978-0-7695-3769-6

Type

conf

DOI

10.1109/NCM.2009.285

Filename

5331573