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Building a job component validity model using job analysis data from the Occupational Information Network.

机译:使用来自职业信息网的工作分析数据建立工作成分有效性模型。

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摘要

Job component validation is an effective methodology for identifying tests for selection when local criterion related validation studies are not feasible due to small samples and other organizational constraints. The goal of this study was to assess the usefulness of job information from the Occupational Information Network (O*NET), which replaces the Dictionary of Occupational Titles (DOT), in a job component validation procedure. Specifically, two O*NET domains, Skills and Generalized Work Activities, were examined. Analyses were conducted with several commercially-available selection instruments, including the Employment Aptitude Survey tests, the Hogan Personality Inventory, and Workplace Literacy Tests. The results provided support for the conclusion that the O*NET job database can be used successfully in a job component validation model. The average multiple Rs when predicting mean test scores were .56 and .70 for the Skills and Generalized Work Activity domains, respectively. The average multiple Rs when predicting validity coefficients were .39 and .52 for the Skills and Generalized Work Activity domains, respectively. Results related to cognitive abilities were stronger than were those for personality constructs.
机译:当由于小样本和其他组织限制而无法进行与本地标准相关的验证研究时,工作组成部分验证是一种有效的方法,可用于识别可供选择的测试。这项研究的目的是评估职业信息网络(O * NET)中的职业信息的有用性,该信息网络在职业组成部分验证过程中取代了职业名称词典(DOT)。具体来说,检查了两个O * NET域,即技能和广义工作活动。使用几种商业上可用的选择工具进行了分析,包括就业能力调查测试,霍根个性量表和工作场所素养测试。结果为以下结论提供了支持:O * NET作业数据库可以在作业组件验证模型中成功使用。技能和广义工作活动领域的平均平均得分在预测平均考试成绩时分别为0.56和.70。技能和广义工作活动领域的预测有效性系数时的平均多重Rs分别为.39和.52。与认知能力有关的结果比对人格建构的结果更强。

著录项

  • 作者

    D'Egidio, Erika Lynn.;

  • 作者单位

    University of Houston.;

  • 授予单位 University of Houston.;
  • 学科 Psychology Industrial.
  • 学位 Ph.D.
  • 年度 2001
  • 页码 196 p.
  • 总页数 196
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 工业心理学;
  • 关键词

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