摘要
本研究基于Coze平台,设计并实现一款面向大学英语四六级考试的智能教学助手系统。该系统采用项目反应理论(IRT)构建个性化评估模型,依托大语言模型的自然语言处理能力,实现个性化推荐、学习方案智能生成、作业自动批改等核心功能。该系统采用模块化设计,旨在解决传统英语教学中存在的个性化指导不足、学习效果评估方式单一等问题。实践表明,该教育智能体能够根据学生能力水平精准推荐学习内容,有效减轻教师教学负担,显著提升大学英语四六级备考效率与学生的英语综合水平。
Based on the Coze platform,this study designs and implements an intelligent teaching assistant for the College English Test(CET-4 and CET-6).The system adopts Item Response Theory(IRT)to construct a personalized assessment model,and relies on the natural language processing capabilities of large language models to realize core functions such as personalized recommendation,intelligent learning plan generation,and automatic homework grading.Adopting a modular design,the system aims to address the problems existing in traditional English teaching,including insufficient personalized guidance and single-method evaluation of learning effectiveness.Practical results show that this educational agent can accurately recommend learning content according to students'proficiency levels,effectively reduce the teaching burden on teachers,and significantly improve the efficiency of CET-4 and CET-6 preparation as well as students'overall English proficiency.
作者
陈嘉咏
张斌
Chen Jiayong;Zhang Bin(Zhejiang Yuexiu University of Foreign Languages,Shaoxing,Zhejiang 312000,China)
出处
《计算机时代》
2026年第3期84-89,95,共7页
Computer Era
基金
浙江越秀外国语学院大学生创新创业训练计划项目资助“基于ai大模型的教学助手的开发与科研评估”(编号:2025127920055)。
