Evaluation of E-Learning Websites Using Additive Rank Probability Method: Case Study of C Programming Website

E-learning is conducted by using electronic media and resources for learning activities. Recently, e-learning platforms have received more attention than traditional learning methods. Advances in information and communication systems have resulted in e-learning websites becoming interactive and flexible. However, the rapid increase in the use of e-learning websites leads to the problem of e-learning website evaluation and selection. In this study, e-learning websites were evaluated by adopting multi-criteria decision-making (MCDM). A new MCDM method, namely additive rank probability (ARP), was developed in this study to select the best e-learning website. To verify the effectiveness of the ARP method, the best C programming website was selected using five alternatives and ten criteria. The ranking of the C programming websites exactly matched those derived by other MCDM methods. However, there was a difference in the ranking by the ARP method with the weighted Euclidean distance-based approximation (WEDBA) method. ARP was proven as a simple and efficient method for identifying the best e-learning website for an effective learning process.