Artificial intelligence-powered evaluation model #worldresearchaward #analyze #quality
Assessing students’ learning outcomes and abilities has always been a key link for English translation education in universities. However, traditional evaluation methods often face problems such as strong subjectivity and long time consumption , and it is difficult to meet the needs of large-scale classroom environments. To address these issues, this paper proposes and verifies a translation teaching quality evaluation model based on artificial intelligence (AI), aiming to improve the objectivity, consistency and efficiency of the evaluation. A mixed-methods design with data triangulation is employed to analyze data through a combination of qualitative and quantitative approaches. The quantitative part collects assessment feedback data from 796 English-related majors through questionnaire surveys, and the qualitative part uses focus group discussions to deeply analyze students’ acceptance and trust in the AI evaluation system and the impact of AI evaluation on the development of ...