Restructuring vocational English testing with Artificial Intelligence: A study on the validity and washback effect of communicative language testing theory
人工智能赋能中职英语测试模式重构：基于交际语言测试理论的效度与反拨效应研究

摘要

基于交际语言测试理论，融合人工智能前沿技术，针对广西地区中职学校学生，运用混合研究方法重构中职英语测试模式。通过量化问卷调查、质性访谈及实验数据分析，对比传统与新型 AI-CLT 测试模式下学生成绩、教学反馈及专业词汇掌握情况。研究证实，新型测试模式在听力、口语、阅读、写作等维度与学生综合语言能力显著正相关。智能评分系统提升评估客观性与效率，个性化反馈系统增强学生专业词汇掌握度，激发学习动力与自我反思能力。该模式借由情境化任务设计与多模态数据分析，有效解决“学用分离”问题，为职业教育英语测评改革提供理论与实践参考。

Abstract

This study restructures the English testing model for secondary vocational schools in Guangxi, combining Communicative Language Testing (CLT) theory with cutting - edge AI tech. It uses a mixed - methods approach, including quantitative questionnaires, qualitative interviews, and experimental data analysis, to compare the CLT - based AI - powered model with the traditional one. The focus is on student performance, teaching feedback, and grasp of specialized vocabulary. The study shows a significant positive link between the new model and students' all - round language skills in listening, speaking, reading, and writing. The AI scoring system makes assessment more objective and efficient. The personalized feedback system helps students better learn professional vocabulary and promotes their motivation and self - reflection. Through scenario - based tasks and multimodal data analysis, the model effectively bridges the gap between learning and practical use, offering useful references for vocational English assessment reform.