Skill assessment method: A perspective from concept-cognitive learning

IF 3.2 1区 数学 Q2 COMPUTER SCIENCE, THEORY & METHODS
Yin-Feng Zhou , Hai-Long Yang , Jin-Jin Li , Da-Li Wang
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引用次数: 0

Abstract

Skills represent potential cognitive abilities that need to be reflected by observing external performances. In competence-based knowledge space theory, whether individuals solve items in a knowledge domain correctly can reflect whether they have mastered the relevant skills. Currently, skill function that reflects the relationship between skills and items has been extended to fuzzy skill function on polytomous items. However, existing skill assessment techniques are not suitable to assess response data that are noisy under the fuzzy skill function. Based on the fact that individuals' learning process of skills is consistent with the cognitive learning process, this paper provides a skill assessment method from a concept-cognitive learning perspective. A special fuzzy skill function, conjunctive fuzzy skill function, is converted into a fuzzy formal context. For facilitating skill assessment, the definitions of well-formed item-skill context and subsequent state are given. Based on a well-formed item-skill context and the idea of upper and lower approximations in rough set theory, the approximate concepts are learned by using response patterns as cues to provide a skill assessment method. The empirical application shows that the skill assessment method proposed in this paper is feasible and has practical applications.
技能评估方法:概念认知学习视角
技能代表潜在的认知能力,需要通过观察外部表现来反映。在基于能力的知识空间理论中,个体是否正确地解决了知识领域中的项目,可以反映个体是否掌握了相关的技能。目前,反映技能与物品之间关系的技能函数已经扩展为多同构物品上的模糊技能函数。然而,现有的技能评估技术并不适合在模糊技能函数下对带有噪声的响应数据进行评估。基于个体的技能学习过程与认知学习过程是一致的,本文提出了一种概念-认知学习视角下的技能评估方法。将一种特殊的模糊技能函数——连接模糊技能函数转化为模糊形式语境。为了便于技能评估,给出了格式良好的项目技能上下文和后续状态的定义。基于形成良好的项目技能语境和粗糙集理论中上下近似的思想,以反应模式为线索学习近似概念,从而提供一种技能评估方法。实证应用表明,本文提出的技能评估方法是可行的,具有实际应用价值。
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来源期刊
Fuzzy Sets and Systems
Fuzzy Sets and Systems 数学-计算机:理论方法
CiteScore
6.50
自引率
17.90%
发文量
321
审稿时长
6.1 months
期刊介绍: Since its launching in 1978, the journal Fuzzy Sets and Systems has been devoted to the international advancement of the theory and application of fuzzy sets and systems. The theory of fuzzy sets now encompasses a well organized corpus of basic notions including (and not restricted to) aggregation operations, a generalized theory of relations, specific measures of information content, a calculus of fuzzy numbers. Fuzzy sets are also the cornerstone of a non-additive uncertainty theory, namely possibility theory, and of a versatile tool for both linguistic and numerical modeling: fuzzy rule-based systems. Numerous works now combine fuzzy concepts with other scientific disciplines as well as modern technologies. In mathematics fuzzy sets have triggered new research topics in connection with category theory, topology, algebra, analysis. Fuzzy sets are also part of a recent trend in the study of generalized measures and integrals, and are combined with statistical methods. Furthermore, fuzzy sets have strong logical underpinnings in the tradition of many-valued logics.
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