Author

Sanika Gupta

ORCID Identifier(s)

0000-0002-0403-0042

Graduation Semester and Year

2016

Language

English

Document Type

Thesis

Degree Name

Master of Science in Computer Science

Department

Computer Science and Engineering

First Advisor

Fillia Makedon

Abstract

One of the methods of learning a new language, or Second-Language Acquisition (SLA), is immersion, seen today as one of the most effective learning methods. Using this method, the learner relocates to a new place where the target language is the dominant language and tries to learn the language my immersing themselves in the local environment. However, it isn’t a feasible option for all, thus, traditional, less effective learning methods are used. As an alternative solution, we use virtual reality (VR) as a new method to learn a new language. VR is an immersive technology that allows the user to wear a head-mounted display to be immersed in a life-like virtual environment. Ogma, an immersive virtual reality (VR) language learning environment is introduced and compared to traditional methods of language learning. For this study, teaching a foreign vocabulary was focused only. Participants were given a set of ten Swedish words and learn them either by using a traditional list-and-flash-cards method or by using Ogma. They then return one week later to give feedback and be tested on their vocabulary-training success. Results indicated that percentage retention using our VR method was significantly higher than that of the traditional method. In addition, the effectiveness and enjoyability ratings are given by users were significantly higher for the VR method. This proves that our system has a potential impact on SLA by using VR technology and that Immersive Virtual reality technique is better than traditional methods of learning a new language.

Keywords

Virtual reality, Language acquisition, Learning

Disciplines

Computer Sciences | Physical Sciences and Mathematics

Comments

Degree granted by The University of Texas at Arlington

25799-2.zip (1626 kB)

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