PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
July 10, 2024International Journal of Chinese and English Translation & Interpreting0 citations

Pedagogy in Legal Terminology Translation: A Corpus-based Approach

View Full Paper
CZChenjie Zeng

Key Points

Key points are not available for this paper at this time.

Abstract

This paper explores effective pedagogical practices to train high-end foreign legal professionals in China’s Greater Bay Area by answering two research questions. First, can corpus-based teaching be applied as a productive pedagogical method? Second, how can beginner professionals be cultivated in legal translation capabilities in the legal domain? The paper proposes a module entitled “Introduction to Legal Terminology Translation,” which includes sessions on legal systems and legalese, corpus approach, and group presentation. A sequential mixed-method survey was conducted using qualitative methods, such as focus groups and interviews, followed by quantitative research using a questionnaire. A preliminary pilot study involved a focus group, questionnaire, and interview. Two identical questionnaires were distributed to two groups of students: one control and one experimental. In the ten-student experiment group, an instructor taught legalese and distributed a follow-up questionnaire. In the twenty-two-student control group, the instructor (more knowledgeable other) did not teach legalese but used a corpus-based questionnaire to assess student entry into the zone of proximal development. In the questionnaire, entry-level Latin legalese examples were provided. During interviews, junior university students preferred a mixture of all three pedagogical methods, while senior university students preferred the corpus approach due to its enhanced efficiency and accuracy.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Chenjie Zeng (2024) studied this question.

synapsesocial.com/papers/68e60cdbb6db64358759fbedhttps://doi.org/10.56395/ijceti.v3i1.97
Ask AI
Helpful
Bookmark
Share
View Full Paper