Crowdsourcing Used in Higher Education: An Empirical Study on a Sustainable Translation Teaching Mode Based on Crowdsourced Translation

Abstract

The language service industry needs more qualified translators. The training of qualified translators needs innovation of translation teaching mode. The combination of crowdsourcing and translation teaching can realize the innovation of translation teaching mode. This study developed an empirical study in which such quantitative and qualitative methods are conducted as classroom observation, case analysis, translation quality analysis, questionnaire survey, and email interviews. Participants in the study included university students registered in the English and Translation degrees in Chinese universities. Statistical analyses were carried out with IBM Statistical Package for Social Sciences (IBM SPSS 26). Validation of the survey instruments, descriptive statistics, and group comparisons were all accomplished. The results demonstrate that the integration of crowdsourcing with translation teaching worked well. The mode has positive significance for exploring learner autonomy, stimulating students’ motivation, improving students’ translation ability, and training qualified translators. The mode is of sustainable value, with the development of AI-driven machine translation technology, and the innovation of translation teaching mode is significant for professional translator training. This mode of translation teaching based on crowdsourcing has a certain reference value for the cultivation of high-quality language service talents and the construction of a new mode of personnel training in the language service industry.