Analysis of AI Immersive Interpretation Teaching Evaluation Based on Data Mining

Siying He

2022

Abstract

The rapid development of China has led to an urgent demand for qualified English interpreters. However, the interpretation classes in universities fail to build immersive teaching spaces as well as corresponding teaching resources and evaluation systems, which makes it difficult to meet the demand. Upon the trend of intelligentization of foreign language education. This study introduces the operating mechanism and characteristics of AR and VR, constructs an AI immersive interpretation teaching evaluation model, and uses data mining technology to mine and analyze teaching-related data. Based on the theory of embodied and immersive teaching, five- dimensional evaluation index is established to accurately reflect the learning effect of students. This paper focuses on the application of data mining technology in AI immersive interpretation teaching evaluation, which can promote the quality of school teaching and has great significance for AI immersive interpretation teaching evaluation.

Paper Citation

in Harvard Style

He S. (2022). Analysis of AI Immersive Interpretation Teaching Evaluation Based on Data Mining. In Proceedings of the 2nd International Conference on New Media Development and Modernized Education - Volume 1: NMDME; ISBN 978-989-758-630-9, SciTePress, pages 192-196. DOI: 10.5220/0011908900003613

in Bibtex Style

@conference{nmdme22,
author={Siying He},
title={Analysis of AI Immersive Interpretation Teaching Evaluation Based on Data Mining},
booktitle={Proceedings of the 2nd International Conference on New Media Development and Modernized Education - Volume 1: NMDME},
year={2022},
pages={192-196},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011908900003613},
isbn={978-989-758-630-9},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 2nd International Conference on New Media Development and Modernized Education - Volume 1: NMDME
TI - Analysis of AI Immersive Interpretation Teaching Evaluation Based on Data Mining
SN - 978-989-758-630-9
AU - He S.
PY - 2022
SP - 192
EP - 196
DO - 10.5220/0011908900003613
PB - SciTePress