Evidence map›Paper›PMID 40328816›Full record

ArticleScientific reports2025

The analysis of English language teaching with machine translation based on virtual reality technology.

Tao Su, Lynette P Rue

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Tao SuSchool of Foreign Studies, Anhui Polytechnic University, Wuhu, 241000, China.
Lynette P RueEducation Program Supervision in Mathematics in the Department of Education, Trece Martirez City, 4109, Cavite, Philippines. philipwuhu@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study focuses on the application of virtual reality (VR) technology in English language teaching (ELT), and discusses the effect of combining VR with machine translation (MT) technology. VR technology is introduced into the study to provide innovative teaching methods for English teachers and create an immersive learning environment for students. Based on the latest development of deep learning (DL), a new MT model is proposed in this study, and it is successfully integrated with VR technology to optimize the quality of ELT. The experimental results show that the translation accuracy of the MT model designed in this study reaches 98.5%, the F1 score is stable at around 93%, and the semantic information recall rate is as high as 92%, all of which are better than the traditional model. In the preliminary test, the comparative experiment of 40 English majors further verified the effectiveness of the model in improving translation efficiency and quality. This study shows the great potential of the integration of VR and MT technology in ELT, and also proves its advantages by using experimental data, which provides technical support for ELT and provides reference for future practice.

Indexed as

English language teachingInnovative applicationsMachine translationVR technology

Identifiers

PMID40328816
PMCPMC12056001

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.