Selection of Optimal E-Learning Tool with Type-2 Intuitionistic Fuzzy Einstein Interactive Weighted Aggregation Operator

Abstract

Not only are daily life activities being disrupted by the COVID-19 pandemic, but so are educational systems. To some extent, encouraging the use of e-learning technology has helped to stabilize the situation. The suitable selection of the appropriate e-learning platform for the institution depends upon different criteria with uncertain information. As type 2 intuitionistic fuzzy (T2IF) sets are conceptually intriguing and they provide a lot of expressive potential for dealing with uncertainty in expert knowledge, this work investigates the best e-learning tool for higher education in a type 2 intuitionistic fuzzy environment. A type-2 intuitionistic fuzzy einstein interactive weighted averaging (T2IFEIWA) operator is proposed for this purpose. The desirable properties of the proposed aggregation operator are validated, and the operator is used to choose the best e-learning tool.