生成式人工智能赋能高考数学考试评价研究OA
Research on the Empowerment of Generative Artificial Intelligence in the Evaluation of College Entrance Examination Mathematics Test
随着人工智能与教育评价的深度融合,高考数学考试评价的智能化转型已成为教育研究领域的重要课题.为探索生成式人工智能如何赋能高考数学考试评价,研究构建了一个基于 ECD 理论的生成式人工智能赋能高考数学考试评价实施框架,并以 2023年新高考全国1 卷第19题为例展示了应用过程.结果表明,生成式人工智能能够以解题步骤与典型错误等标注内容为训练语料,准确高效地对大样本学生答卷中的问题解决策略与解题错误归因等进行识别、检索、匹配与分析,在高考数学考试评价中具有广阔的应用前景.
With the deep integration of artificial intelligence and educational assessment,the intelligent transformation of the evaluation of the college entrance examination mathematics test has become an important topic in the field of educational research.To explore how generative artificial intelligence can empower the evaluation of the college entrance examination mathematics test,a framework for implementing the empowerment of the college entrance examination mathematics test evaluation by generative artificial intelligence based on the ECD theory was constructed,and the application process was demonstrated using the 19th from Paper I of the 2023 new college entrance examination national as an example.The results show that generative artificial intelligence can use the annotation contents such as problem-solving steps and typical errors as training data,accurately and efficiently identify,retrieve,match,and analyze the problem-solving strategies and error attribution in a large sample of student answer sheets,and has broad application prospects in the evaluation of the college entrance examination mathematics test.
苏洪雨;杨晓冰;李向明;王时舟
华南师范大学 数学科学学院,广东 广州 510631华南师范大学 数学科学学院,广东 广州 510631广东省教育考试院,广东 广州 510635汇隽可之(深圳)人工智能科技有限公司,广东 深圳 525024
社会科学
生成式人工智能高考数学考试评价问题解决策略解题错误归因
generative artificial intelligenceevaluation of the college entrance examination mathematics testproblem-solving strategiesattribution of problem-solving errors
《数学教育学报》 2026 (3)
66-73,8
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