心理科学进展2026，Vol.34Issue(3)：404-423,20.DOI:10.3724/SP.J.1042.2026.0404
生成式大语言模型赋能心理测量学:优势、挑战与应用
Empowering psychometrics with generative large language models:Advantages,challenges,and applications
摘要
Abstract
Generative Large Language Models(LLMs),a class of artificial intelligence models pre-trained on vast corpora of textual data,present unprecedented opportunities and challenges for the field of psychometrics.This paper synthesizes the developmental trajectory of interdisciplinary research between AI and psychology to summarize the significant advantages of LLMs in empowering psychometrics,identify key challenges in their application,and propose future research directions.Specifically,LLMs'ability to generate coherent,context-aware natural language text has the potential to transform traditional assessment interaction paradigms.Their advanced capabilities in processing extensive texts and multimodal data allow for the comprehensive capture and analysis of participants'psychological information.Furthermore,LLMs facilitate real-time analysis and personalized feedback,promoting a shift from outcome-based to process-oriented evaluation.Despite facing practical challenges related to stability,creativity,and scalability,LLMs demonstrate substantial promise in applications such as Situational Judgment Test generation,collaborative problem-solving assessment,intelligent mental health diagnostics,and test item quality analysis.关键词
生成式大语言模型/心理测量学/人工智能/自动化评估/交互式测验Key words
large language models/psychometrics/artificial intelligence/automated assessment/interactive testing分类
社会科学引用本文复制引用
田雪涛,周文杰,骆方,乔志宏,丰怡..生成式大语言模型赋能心理测量学:优势、挑战与应用[J].心理科学进展,2026,34(3):404-423,20.基金项目
北京市教育科学规划青年专项课题(CCFA24122)资助. （CCFA24122）
