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Test Drivers of Candidate Pass Rates: A Predictive Model for Professional Certification Exams.

机译:合格率的测试驱动程序:专业认证考试的预测模型。

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摘要

Many candidates who take certification exams do not pass for various reasons. When groups of candidates are not successful, they are more likely to question the validity of the exam. Extensive research has been conducted on the relationships between nontest factors and candidate pass-fail rates, but research examining the interactions between test-related factors and pass-fail rates is sparse in two important areas: the results cannot be generalized across a specific population of certification exams, and theoretical models of candidate pass rates cannot be developed from the literature. A quantitative, non-experimental survey research study was conducted to explore and confirm the test development (TD) predictors of overall and first-time pass rates using chi-squared automatic interaction detector, categorical regression, and cluster analysis. Participants included 803 representatives from different Credentialing Organizations. Out of 71 TD variables evaluated, four (4) were confirmed as significant predictors of overall pass rates: eligibility requirements (p < .001), equating design (p < .001), computer-based test design (p < .001), and multiple item formats (p < .05). Eligibility requirements produced the greatest changes in overall pass rates. Two of the TD variables were confirmed as significant predictors of first-time pass rates: test purpose (p < .001) and multiple item formats (p < .05). Test purpose yielded the greatest changes in first-time pass rates. Multiple item formats also surfaced as the only predictor in both pass-rate models, providing strong evidence that candidate pass rates are higher when only one item format is used on exams. Using these significant TD predictors, theoretical models were also developed for overall and first-time pass rates as a framework for future research. To improve external validity, recommendations were made to researchers to empirically test these theoretical models or entirely replicate this study using a more representative sample of certification exams. Future research should also be conducted to understand why certain eligibility requirements, exam competency levels, equating and computer-based test designs, and exams with multiple item formats result in lower pass rates. To give candidates every opportunity to be successful, at a minimum, credentialing organizations should design their certification exams with one type of item format.
机译:许多参加认证考试的考生由于各种原因没有通过。当几组候选人均不成功时,他们更有可能质疑考试的有效性。已经对非测试因素与候选通过/未通过率之间的关系进行了广泛的研究,但是研究与测试相关的因素与通过/未通过率之间的相互作用的研究在两个重要领域中很少:结果不能在特定人群中进行概括。认证考试和候选人通过率的理论模型无法从文献中开发。进行了一项定量的非实验调查研究,以探索和确认使用卡方自动交互检测器,分类回归和聚类分析得出的总体和首次通过率的测试发展(TD)预测指标。参加者包括来自不同认证机构的803名代表。在评估的71个TD变量中,有四(4)个被确认为总体合格率的重要预测指标:资格要求(p <.001),等同设计(p <.001),基于计算机的测试设计(p <.001)以及多种项目格式(p <.05)。资格要求在总体合格率方面产生了最大的变化。已确认其中两个TD变量是首次通过率的重要预测指标:测试目的(p <.001)和多种项目格式(p <.05)。测试目的在首次通过率方面产生了最大的变化。在两种合格率模型中,多种项目格式也成为唯一的预测因素,这提供了有力的证据,证明在考试中仅使用一种项目格式时,候选合格率更高。使用这些重要的TD预测因子,还为总体和首次通过率开发了理论模型,作为未来研究的框架。为了提高外部有效性,建议研究人员以经验方式测试这些理论模型,或使用更具代表性的认证考试样本完全复制本研究。还应该进行进一步的研究,以了解为什么某些资格要求,考试能力水平,基于等分和基于计算机的测试设计以及具有多种项目格式的考试会导致较低的通过率。为了给应聘者提供一切成功的机会,认证组织至少应使用一种项目格式设计其认证考试。

著录项

  • 作者

    Rouse, Edrin W.;

  • 作者单位

    Northcentral University.;

  • 授予单位 Northcentral University.;
  • 学科 Business Administration General.;Statistics.;Psychology Psychometrics.
  • 学位 Ph.D.
  • 年度 2014
  • 页码 305 p.
  • 总页数 305
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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