Learning interpreting in virtual reality: a scoping review

ABSTRACT

Virtual reality (VR) has sparked substantial interest in language education, but its application in interpreting training is still in its early stages. This review provides the first comprehensive analysis of this emerging field by investigating research trends, study designs, methodological features, key research themes, and major findings. The results indicate a notable rise in research interest, with an increase in publications and a growing diversity of VR platforms being involved. The analysis reveals a shift from design-oriented papers to empirical investigations. The empirical studies primarily employed quantitative or mixed methods analysis, and gathered data through questionnaires, tests, and interviews. Thematic analysis identified four research themes: functionality evaluation and user experience, learning outcomes, platform design and features, and pedagogical and theoretical exploration. Prior studies revealed generally favorable attitudes among users towards the functionality, usability, and immersive learning experiences within VR environments. Additionally, these studies indicated the potential effectiveness of VR in promoting interpreting learning outcomes, as evidenced by self-reported evaluations or comparisons of test results. However, concerns remain regarding technical limitations and learning efficiency. This review highlights the potential for increased use of VR in interpreting training and the need for additional empirical data gathered through enhanced study designs.

KEYWORDS:

• Virtual reality (VR)
• interpreting training
• scoping review
• computer-assisted interpreter training (CAIT)

Data availability statement

The data that support the findings of this study are available on request.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This research is supported by the Zhejiang Province’s Offline First Class Course “Business English Interpreting” at Wenzhou Business College [grant number: SJ2020YLKC10], Chongqing University of Posts and Telecommunications [grant number: K2023-140].

Notes on contributors

Pingping Hu

Pingping Hu is a PhD candidate at University of International Business and Economics, Beijing, China and also a lecturer at Wenzhou Business College, Zhejiang, China. Her research interests include computer assisted interpreting, computer assisted interpreter training, and cognitive interpreting studies. As a language educator, she has taught Business Translation, Business Interpreting and English Listening.

Bin Gao

Bin Gao is a professor of translation and interpreting studies at School of English and International Studies, Beijing Foreign Studies University, Beijing, China. Her research interests include interpreter education and translation pedagogy. As a language educator, she has taught Simultaneous Interpreting, Consecutive Interpreting and Conference Interpreting.

Ke Li

Ke Li is currently teaching at Chongqing University of Posts and Telecommunications, China. Her primary research interests are computer-assisted language learning, digital game-based language learning, language learning beyond the classroom, and autonomous learning. As a language educator, she has taught Chinese, English, and interpretation.