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

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.