现代教育技术2026，Vol.36Issue(4)：83-91,9.DOI:10.3969/j.issn.1009-8097.2026.04.009
如何进行创造性思维大规模测评
How to Conduct Large-Scale Assessment of Creative Thinking?
摘要
Abstract
Creative thinking,as a key element in the cultivation of top-notch innovative talents,its scientific assessment is an important direction for the reform of educational evaluation.The PISA 2022 Creative Thinking Assessment Framework provides a mature reference for large-scale standardized evaluation.However,manual scoring has problems such as difficult standard unification,low efficiency and poor quality guarantee,which urgently needs technological empowerment.Based on this,the paper constructed a"human-in-the-loop"human-machine collaborative scoring mode supported by large language model,and explained the implementation mechanisms of applying this mode for creative thinking assessment from three aspects of theoretical basis,key technologies and practical paths.Subsequently,taking the Shanghai student creative thinking assessment project as a case study,this paper verified the effectiveness of this mode through comparative analysis of relevant data from both manual and human-machine collaborative scoring methods.It was found that both scoring methods were reliable,while the human-machine collaborative scoring showed higher factor loading values and discrimination values compared to manual scoring,and reduced the workload per human rate by approximately 66.7%in the human-machine collaborative scoring.The adaptability of human-computer collaborative assessment was influenced by the degree of task structuring,and expression-type questions required deeper human intervention.The research in this paper provided a human-machine collaborative pathway and empirical basis that can balance quality and efficiency for large-scale standardized assessment of creative thinking,and can also offer a reference for the standardized promotion of more extensive and higher-order thinking assessment enabled by artificial intelligence.关键词
创造性思维/大语言模型/"人在环路"/人机协同评阅Key words
creative thinking/large language model/"human-in-the-loop"/human-machine collaborative scoring分类
社会科学引用本文复制引用
章璐,陆璟,顾小清..如何进行创造性思维大规模测评[J].现代教育技术,2026,36(4):83-91,9.基金项目
本文为2023年度国家社会科学基金教育学一般项目"基于义务教育新课程的学生创造力评估研究"(项目编号:BHA230134)的阶段性研究成果. （项目编号:BHA230134）
