English(EN) Automatic Item Generation for Personality Situational Judgment Tests with Large Language Models

大型语言模型在自动化个性化测试生成方面展现出潜力

作者 PulseAugur 编辑部 · [1 个来源] · 2026-09-02 04:00

研究人员开发了一个使用大型语言模型（LLMs）自动生成个性情境判断测试（SJTs）的框架。使用GPT-4和ChatGPT-5进行的研究表明，优化提示和特定的温度设置可以生成具有良好内容效度的项目。该方法显示出跨模型泛化能力，并为“大五”人格特质生成了心理测量学上可靠的SJTs，为传统方法提供了一种高效的替代方案。 AI

影响这项研究展示了大型语言模型在简化心理评估工具创建方面的潜力，提高了效率和可及性。

排序理由学术论文，详细介绍了一种新的AI应用方法。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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报道来源 [1]

arXiv cs.AI TIER_1 English(EN) · Chang-Jin Li, Jiyuan Zhang, Yun Tang, Jian Li · 2026-09-02 04:00

使用大型语言模型为个性情境判断测试自动生成项目

arXiv:2412.12144v5 Announce Type: replace-cross Abstract: Personality assessment through situational judgment tests (SJTs) offers unique advantages over traditional Likert-type self-report scales, yet their development remains labor-intensive, time-consuming, and heavily dependen…

本文如何被排名

报道来源 [1]

使用大型语言模型为个性情境判断测试自动生成项目

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