ABSTRACT
Given the growing usage of e-learning systems during COVID-19 epidemic and expansion of internet-based infrastructure, a resilient approach for e-learning systems is highly required. This paper proposes an Adaptive Neuro-Fuzzy Inference System (ANFIS) to evaluate e-learning resilience. In the ANFIS model, five substantial factors including individual, technology, content, agility, and assessment/support factors are considered as fuzzy inputs, while e-learning resilience is considered as a single output. The proposed ANFIS model has been successfully implemented for e-learning resilience measurement during COVID-19 epidemic in virtual Iranian university. Statistical analysis demonstrated that there was no meaningful difference between experts’ opinions and our proposed procedure for e-learning resilience measurement. Sensitivity analysis via the proposed model on changing the different factors showed significant sensitivity to changes in the agility factor. The proposed model can be used in all educational institutions to evaluate the improvement of resilience in e-learning systems. To implement the model for an organization, the values of the designed ANFIS model should be defined specifically for the organization and the corresponding model need to be simulated by examining the involved components and relationships. © 2021, Success Culture Press. All rights reserved.