规模开发和验证:方法和建议

K. Lamm, A. Lamm, Don W. Edgar
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引用次数: 22

摘要

有效和可靠的数据及其收集的重要性是实证研究的基础;然而,在创建能够捕获有效和可靠数据的强大量表方面,特别是在国际农业和推广教育背景下,仍然存在不一致的方法。稳健规模开发包括五个验证领域:内容、响应过程、内部结构、外部结构和结果性。本指南的目的是提供方法上的建议,以提高量表开发的严谨性和采用率,并提供一套功能原则,以帮助有兴趣通过开发或改编的量表获取数据的研究人员和实践者。此外,总结的信息为评估报告的量表结果的严谨性和有效性提供了一个基准。一个一致的框架应该提供一个通用的词典,在这个词典上检查量表和相关的结果。适当的规模开发和验证将有助于确保研究结果准确地描述预期的基本概念,特别是在国际农业和推广教育背景下。关键词:量表开发,效度,定量分析
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Scale Development and Validation: Methodology and Recommendations
The importance of valid and reliable data and its collection is fundamental to empirical research; however, there remain inconsistent approaches to creating robust scales capable of capturing both valid and reliable data, particularly within international agricultural and extension education contexts. Robust scale development consists of five areas for validation: content, response process, internal structure, external structure, and consequential. The purpose of this guide was to provide methodological recommendations to improve scale development rigor and adoption and to provide a set of functional principles to aid researchers and practitioners interested in capturing data through developed, or adapted, scales. Additionally, the information summarized provide a benchmark upon which to evaluate the rigor and validity of reported scale results. A consistent framework should provide a common lexicon upon which to examine scales and associated results. Proper scale development and validation will help ensure research findings accurately describe intended underlying concepts, particularly within an international agricultural and extension education context. Keywords: scale development, validity, quantitative analysis
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