Critical dimensions in strengthening education and instructor training using fuzzy based decision algorithm and CRITIC WASPAS method

TL;DR

This paper introduces a new fuzzy-based decision algorithm and CRITIC WASPAS method to improve education and instructor training by managing uncertainty and ranking preferences.

Contribution

The novelty lies in the development of circular pythagorean fuzzy set and aggregation operators for decision-making in education.

Findings

A novel circular pythagorean fuzzy set (Cr-PyFS) is introduced to handle uncertainty in real-life applications.

New aggregation operators like Cr-PyFFWA and Cr-PyFFWG are formulated for decision-making.

The CRITIC and WASPAS methods are combined to rank training institutes effectively.

Abstract

Quality education and instructor training are foundational to the development of any society, as they directly influence the effectiveness of learning and the overall performance of educational systems. Decision-making is crucial in enhancing quality education and instructor training by ensuring teaching policies. This article modifies some robust mathematical methodologies of the fuzzy framework and decision-making techniques to aggregate an authentic ranking of preferences. We also explore a novel approach to the circular pythagorean fuzzy set (Cr-PyFS) that is used to manage uncertainty and vagueness in complicated real-life applications. Some flexible operations of Frank t-norm and t-conorm are also formulated under the system of circular pythagorean fuzzy (Cr-PyF) information. Furthermore, we derive a list of mathematical aggregation operators such as circular pythagorean fuzzy frank weighted average (Cr-PyFFWA) and circular pythagorean fuzzy frank weighted geometric (Cr- PyFFWG) operators with prominent properties. Additionally, a decision-making approach to the criteria importance through the intercriteria correlation (CRITIC) method is adopted to investigate the weight of criteria by incorporating the Cr-PyF situations. Moreover, an optimization technique of the weighted aggregated sum product assessment (WASPAS) method is established to rank alternatives under different conflicting criteria. A numerical example is constructed to examine suitable training institutes to improve instructor skills and expertise. The comparative study is also established to demonstrate the superiority and validation of pioneering approaches with existing terminologies. Finally, a summary of the article is presented at the end of the manuscript.

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