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Cheating on online assessment tests: Prevelance and impact on validity.

机译:在网上评估测试中作弊:普遍性及其对有效性的影响。

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摘要

Online tests are a relatively efficient way to assess large numbers of job candidates and are becoming increasingly popular with organizations. Due to their unproctored nature, however, online selection tests provide the potential for candidates to cheat, which may undermine the validity of these tests for selecting qualified candidates. The purpose of this study was to test the appropriateness of utility theory as a framework for understanding decision-making in regard to cheating on an online cognitive ability test (CAT) by manipulating the probability of passing the test with cheating, the probability of being caught cheating, and the value of being caught cheating in two samples: 518 adults recruited through Amazon mTurk, and 384 undergraduate students. The probability of being caught cheating significantly affected performance on the CAT for the mTurk sample, but not for the student sample, and significantly moderated the relationship between CAT score during session one and CAT score during session two for the student sample. Neither the probability of being caught cheating nor the value of being caught cheating significantly affected CAT performance or validity in either sample. Findings regarding the prevalence and effectiveness of cheating are discussed.
机译:在线测试是评估大量求职者的一种相对有效的方法,并且在组织中越来越受欢迎。但是,由于在线甄选考试具有非监督性质,因此它为候选人提供了作弊的可能,这可能会破坏这些考试选拔合格候选人的有效性。这项研究的目的是通过操纵通过作弊测试的可能性,被抓住的可能性,来检验效用理论是否适合作为理解关于在线认知能力测验(CAT)作弊的决策的框架。作弊以及被欺骗的价值有两个样本:通过Amazon mTurk招募的518名成年人和384名大学生。被捕获作弊的概率显着影响了mTurk样本的CAT性能,但没有影响学生样本的CAT性能,并且显着缓和了学生样本的第一阶段的CAT得分与第二阶段的CAT得分之间的关​​系。被骗的可能性或被骗的价值均未显着影响任一样品的CAT性能或有效性。讨论了关于作弊行为的普遍性和有效性的发现。

著录项

  • 作者

    Cavanagh, Thomas M.;

  • 作者单位

    Colorado State University.;

  • 授予单位 Colorado State University.;
  • 学科 Education Educational Psychology.;Web Studies.;Sociology Organizational.;Psychology Industrial.
  • 学位 Ph.D.
  • 年度 2014
  • 页码 181 p.
  • 总页数 181
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

  • 入库时间 2022-08-17 11:53:57

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