评价的有效性:基于论证的方法将走向何方?

Karla Karina Ruiz Mendoza, Luis Horacio Pedroza Zúñiga, Alma Yadhira López García
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引用次数: 0

摘要

在将生成式人工智能与伦理立场以及知情决策相结合的背景下,对有效性概念的演变进行了研究。所使用的方法包括科塞勒克所阐述的概念史,分析有效性概念是如何成为一个基本概念的。采用的方法是文献综述,分析历史和当代观点以及梅西克和凯恩等有影响力的作者的论点。这一概念之旅使我们认识到,有效性不是一个单一的实体,而是由多种理论和实践线索组成的复杂结构,从评价的内在逻辑到其在社会中的应用所产生的影响,不一而足。此外,有效性被认为是一个复杂的概念,不能被简化为测试或评价的单一方面或特征,从而区分了有效性和验证。文献中区分的五个历史时期反映了对有效性理解的范式变化:酝酿期、结晶期、分裂期、统一期、解构期,最后是传播期。最相关的结论是,有效性不是静态的,而是动态的,随着环境和应用的变化而变化。它还强调了持续验证的必要性,以适应新出现的挑战,如生成式人工智能(GenAI),其目标是在量子计算理念日益增长的趋势下,确保评估的准确性和公平性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Validity in evaluation: where is the argument-based approach heading?
The evolution of the concept of validity is examined in the context of the integration of Generative Artificial Intelligence and ethical stances, and with it, informed decision-making. The methodology used includes the history of concepts as laid out by Koselleck, analyzing how the concept of validity is a fundamental concept. The method used is a literature review, analyzing historical and contemporary perspectives and arguments from influential authors such as Messick and Kane. This conceptual journey leads us to recognize that validity is not a monolithic entity, but a complex fabric of multiple theoretical and practical threads, ranging from the internal logic of evaluations to the repercussions of their application in society. Furthermore, validity is recognized as a complex construct that cannot be simplified to a single aspect or characteristic of a test or evaluation, differentiating between validity and validation. The five historical periods distinguished in the literature that reflect paradigmatic changes in the understanding of validity were: gestational, crystallization, fragmentation, reunification, deconstruction, culminating with the period of diffusion. The most relevant conclusion is that validity is not static but dynamic, evolving with context and application. It also emphasizes the need for continuous validation adapted to emerging challenges, such as Generative Artificial Intelligence (GenAI), with the goal of ensuring that evaluations are accurate and fair amid a growing trend on ideas of quantum computing.
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