Research and Practice of Hybrid Teaching Based on AI technology for Foreign Language Translation

Ting Liu, Eunyoung Kim, Xiaoyan Li, Takaya Yuizono, Yukari Nagai, Yifen Lu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

In the context of AI technology, it is necessary to reform the education by adopting information technology and intelligent teaching tools. The hybrid teaching and learning based on AI technology integrates online teaching with offline classroom teaching, by taking advantage of both informatic teaching and traditional teaching. This study takes an example of Japanese translation course of junior students majoring in Japanese language in higher education institutions, and conducts the AI-based Japanese translation hybrid teaching practice. The results indicate that the AI-based hybrid teaching mode may motivate students' activity and self-discipline in learning, and increase their capability and motif of autonomous learning.

Original languageEnglish
Title of host publicationProceedings - 2020 International Conference on Computer Engineering and Application, ICCEA 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages664-668
Number of pages5
ISBN (Electronic)9781728159041
DOIs
Publication statusPublished - Mar 2020
Event2020 International Conference on Computer Engineering and Application, ICCEA 2020 - Guangzhou, China
Duration: Mar 27 2020Mar 29 2020

Publication series

NameProceedings - 2020 International Conference on Computer Engineering and Application, ICCEA 2020

Conference

Conference2020 International Conference on Computer Engineering and Application, ICCEA 2020
Country/TerritoryChina
CityGuangzhou
Period3/27/203/29/20

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Science Applications
  • Hardware and Architecture
  • Information Systems and Management
  • Electrical and Electronic Engineering
  • Safety, Risk, Reliability and Quality

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