比例(比率)
计算机科学
动力学(音乐)
开发(拓扑)
生成语法
人工智能
领域(数学)
钥匙(锁)
度量(数据仓库)
数据科学
数据挖掘
系统工程
生成模型
机器学习
工程类
可靠性(半导体)
标识
DOI:10.1080/10447318.2026.2623216
摘要
This study develops and validates two psychometric scales, namely Human-AI Collaboration Dynamics (HACD) and Generative AI-Research Augmentation (GAI-RA), and examines the role of human-AI collaboration in scale development itself. Data were collected from university staff, doctoral students, master’s students, and research-active undergraduates from 16 English Medium Instruction (EMI) universities in Mainland China, Hong Kong, and Macau. Exploratory factor analysis on one subsample (NA1 = 344) identified underlying dimensions, followed by confirmatory factor analysis on two independent subsamples (NA2 = 344; NB = 447). The HACD scales produced four versions, from a core two-factor to an expanded five-factor structure, providing a flexible measurement toolkit. The GAI-RA scale emerged as a concise, single-factor, five-item measure of GenAI research augmentation. These validated instruments, with excellent psychometric properties, advance the study of human-AI collaboration in academic research and demonstrate that GenAI can be integrated into a psychometrically rigorous scale development and validation process.
科研通智能强力驱动
Strongly Powered by AbleSci AI