Empirical indistinguishability: From the knowledge structure to the skills

IF 1.5 3区 心理学 Q3 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
Andrea Spoto, Luca Stefanutti
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引用次数: 1

Abstract

Recent literature has pointed out that the basic local independence model (BLIM) when applied to some specific instances of knowledge structures presents identifiability issues. Furthermore, it has been shown that for such instances the model presents a stronger form of unidentifiability named empirical indistinguishability, which leads to the fact that the existence of certain knowledge states in such structures cannot be empirically tested. In this article the notion of indistinguishability is extended to skill maps and, more generally, to the competence-based knowledge space theory. Theoretical results are provided showing that skill maps can be empirically indistinguishable from one another. The most relevant consequence of this is that for some skills there is no empirical evidence to establish their existence. This result is strictly related to the type of probabilistic model investigated, which is essentially the BLIM. Alternative models may exist or can be developed in knowledge space theory for which this indistinguishability problem disappears.

Abstract Image

经验不可区分:从知识结构到技能
近年来的文献指出,基本局部独立模型(BLIM)在应用于某些特定的知识结构实例时存在可识别性问题。此外,已经证明,对于这种情况,模型呈现出一种更强的不可识别性形式,称为经验不可区分性,这导致这样的结构中某些知识状态的存在无法经过经验检验。在本文中,不可区分性的概念扩展到技能图,更一般地说,扩展到基于能力的知识空间理论。理论结果表明,技能图可以在经验上彼此难以区分。最相关的结果是,对于某些技能,没有经验证据来证明它们的存在。这一结果与所研究的概率模型的类型严格相关,而概率模型本质上是blm。在知识空间理论中可能存在或可以开发替代模型,从而消除这种不可区分性问题。
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来源期刊
CiteScore
5.00
自引率
3.80%
发文量
34
审稿时长
>12 weeks
期刊介绍: The British Journal of Mathematical and Statistical Psychology publishes articles relating to areas of psychology which have a greater mathematical or statistical aspect of their argument than is usually acceptable to other journals including: • mathematical psychology • statistics • psychometrics • decision making • psychophysics • classification • relevant areas of mathematics, computing and computer software These include articles that address substantitive psychological issues or that develop and extend techniques useful to psychologists. New models for psychological processes, new approaches to existing data, critiques of existing models and improved algorithms for estimating the parameters of a model are examples of articles which may be favoured.
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