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Developing a Theory of Two Latent Soft Skills Progress Variables using the BEAR Assessment System: Validity Evidence for the Internal Structure of the Social Evaluative in the Workplace Instrument
Journal of Psychoeducational Assessment ( IF 1.5 ) Pub Date : 2022-01-21 , DOI: 10.1177/07342829211057641
Jerred Jolin 1 , Mark Wilson 2
Affiliation  

In this article, we report on the development of two latent soft skills progress variables using the Berkeley Evaluation and Assessment Research (BEAR) Assessment System (BAS). The Social Evaluative Reasoning in the Workplace (SER-W) instrument uses comic strip scenarios to depict interactions between employees and customers in entry-level workplace settings. We designed items to elicit evidence of student ability to: (a) identify salient customer social cues, which we term the social cue detection (SPU) variable, and, (b) justify an evaluation on the outcome of the situation depicted in the scenarios. We refer to this as the evaluative inference (EI) variable. Research from the field of autism spectrum disorder was used to develop a theory for building social complexity into the SER-W comic strip scenarios, by manipulating the type, frequency, and co-occurrence of the social cues presented in the scenarios. A unidimensional and multidimensional extension of the Rasch partial credit model were fit to the data. Model comparisons provide empirical support for our hypothesized two-dimensional structure, in which the SPU and EI variables are modeled as separate dimensions. These results are considered in terms of the evidence for the validity of the internal structure of the SER-W dimensions they provide. The article concludes with examples of the practical implications that progress variable research can have on soft skills curriculum development and assessment in the field of special education.



中文翻译:

使用 BEAR 评估系统开发两个潜在软技能进步变量的理论:工作场所工具中社会评估内部结构的有效性证据

在本文中,我们使用伯克利评估和评估研究 (BEAR) 评估系统 (BAS) 报告了两个潜在软技能进步变量的发展。工作场所的社会评价推理 (SER-W) 工具使用漫画场景来描述员工和客户在入门级工作场所环境中的互动。我们设计了一些项目来获得学生以下能力的证据:(a) 识别显着的客户社交线索,我们将其称为社交线索检测 (SPU) 变量,以及 (b) 证明对场景中描述的情况的结果进行评估是合理的. 我们将其称为评估推理 (EI) 变量。自闭症谱系障碍领域的研究被用来开发一种理论,通过操纵类型、频率、以及场景中呈现的社会线索的共同出现。Rasch 部分信用模型的一维和多维扩展适用于数据。模型比较为我们假设的二维结构提供了经验支持,其中 SPU 和 EI 变量被建模为单独的维度。这些结果是根据它们提供的 SER-W 维度的内部结构的有效性的证据来考虑的。本文最后举例说明了进展变量研究对特殊教育领域的软技能课程开发和评估可能产生的实际影响。模型比较为我们假设的二维结构提供了经验支持,其中 SPU 和 EI 变量被建模为单独的维度。这些结果是根据它们提供的 SER-W 维度的内部结构的有效性的证据来考虑的。本文最后举例说明了进展变量研究对特殊教育领域软技能课程开发和评估的实际影响。模型比较为我们假设的二维结构提供了经验支持,其中 SPU 和 EI 变量被建模为单独的维度。这些结果是根据它们提供的 SER-W 维度的内部结构的有效性的证据来考虑的。本文最后举例说明了进展变量研究对特殊教育领域软技能课程开发和评估的实际影响。

更新日期:2022-01-21
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