E-learning Systems Evaluation with Data Envelopment Analysis and Bayesian Networks
H.-Y. Kao, Mujie Liu, Chenya Huang, Y.-C. Chang · 2009
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.