Neutrosophic Z-Rough Set Aggregation Operator for University English Immersive Teaching Effectiveness Evaluation Based on Virtual Reality Technology

Abstract

 Immersion language learning has revolutionary potential when Virtual Reality (VR) 
technology is used into university-level English education. This research assesses how well 
university students' English proficiency may be improved by VR-based immersive instruction. 
The study investigates how VR-supported learning environments enhance educational results by 
utilizing four primary criteria: cognitive load and usability, learning engagement, real-world 
communication simulation, and language competency enhancement. Eight different instructional 
methods, such as role-playing, virtual campus visits, and public speaking simulations, were 
evaluated.  A neutrosophic framework was used to examine the data. The neutrosophic set is 
used to overcome uncertainty. We use the Neutrosophic Z-Rough Set (NZRS) to evaluate the 
criteria and alternatives. The aggregation operators of NZRS is used to combine different 
numbers. Although usability and cognitive demands are still important factors, the results show 
that immersive VR experiences greatly increase engagement and real-world language 
application. For educators and organizations looking to implement immersive technology in 
language training, this review offers evidence-based ideas.

DOI: 10.5281/zenodo.16366076