专业推荐评级对教师绩效的预测效果如何?

IF 1.7 3区 教育学 Q2 ECONOMICS
Dan Goldhaber, Cyrus Grout, Malcolm Wolff
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引用次数: 0

摘要

虽然从申请人的专业推荐信中收集信息的做法很普遍,但将推荐信对申请人的评估与随后的表现联系起来的研究却很少。在本文中,我们检验了一种特定类型的推荐信息的预测有效性:从专业推荐中收集的教师申请人的分类评级-这是一种在招聘过程中增强申请人信息可用性的潜在低成本手段。我们发现参考评分与教师绩效之间的整体显著关系,通过观察性评价评分和教师数学增值来衡量,但这种关系受到两个因素的调节。首先,虽然推荐人对有教学经验的申请人的评分可以预测其表现,但对新手申请人的评分却不能。其次,参考评分的预测效度根据评分者的类型而有所不同:来自申请人的主要/其他主管,教学教练/系主任或同事的推荐评分显着预测绩效,而来自其他类型评分者的推荐评分则没有。总的来说,我们的研究结果表明,有意义的信息可以以分类评级的形式从申请人的推荐信中获得,但也显示出这种信息为招聘决策提供信息的潜力存在一些局限性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
How Well Do Professional Reference Ratings Predict Teacher Performance?
While the practice of collecting information from applicants' professional references is widespread, there is a paucity of research linking references' assessments of applicants to subsequent performance. In this paper, we examine the predictive validity of a specific type of reference-provided information: categorical ratings of teacher applicants collected from their professional references – a potentially low cost means of enhancing the applicant information available during the hiring process. We find an overall significant relationship between reference ratings and teacher performance as measured by observational evaluation ratings and teacher value-added in math, but that this relationship is moderated by two factors. First, while references' ratings of applicants with prior teaching experience are predictive of performance, those of novice applicants are not. Second, the predictive validity of reference ratings varies according to rater type: ratings from references identified as the applicants' Principal/Other Supervisor, Instructional Coach/Department Chair, or Colleague are significantly predictive of performance while those from other types of raters are not. Overall, our findings show that meaningful information can be solicited from applicants' references in the form of categorical ratings but also demonstrate some limitations in the potential for this type of information to inform hiring decisions.
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来源期刊
CiteScore
3.00
自引率
4.80%
发文量
46
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