能力(人力资源)
课程
知识管理
实证研究
计算机科学
新兴技术
翻译
数据科学
心理学
教育学
人工智能
社会心理学
认识论
哲学
程序设计语言
标识
DOI:10.1080/1750399x.2022.2101850
摘要
This study constructs a competence framework that covers the most popular interpreting technologies. It adopts an empirical design and uses mainly quantitative methods based on a large-scale survey, comprising 647 questionnaires and 10 interviews. According to the analysis of questionnaire and interview data, the authors identify the main types of interpreting technologies, and the challenges in their application. From the survey data, the authors extracted factors that influence interpreters’ technological competence, and found a high probability that these factors (awareness, learning, and skills and knowledge) govern the application of specific technologies. The authors, therefore, put forward a three-dimensional competence framework for interpreting technologies, and investigate their roles and relevance in different aspects of interpreting education, including curriculum design, and teaching and assessment methods.
科研通智能强力驱动
Strongly Powered by AbleSci AI