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Assessing Potential Predictors of Rater Fit Measures in the Establishment of Performance Standards.

機(jī)譯：在建立績效標(biāo)準(zhǔn)時評估評估者適合度的潛在預(yù)測指標(biāo)。

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The purpose of this study was to determine to what extent two rater background-related variables (i.e., a rater's gender and content domain expertise) and two item characteristic-related variables (i.e., an item's difficulty classification and content domain classification) could account for variance in rater fit indices in the context of a standard setting for a certification examination. Licensing and certification organizations convene groups of subject matter experts in the field (i.e., raters) and engage them in a standard-setting process to recommend a cut score (performance standard) to classify proficient, knowledgeable, and competent individuals. During a standard setting, it is common practice for raters to examine individual items and then provide an estimate of the proportion of minimally qualified candidates that the rater believes would answer each item correctly. Rater fit refers to the level of accuracy or precision that an individual rater attains when providing these estimates. In this study, the fit indices were based on the variance of raters' proportion correct estimates of the performance of minimally qualified candidates on a 200-item certification examination and empiric data gathered on the performance of another group of minimally qualified candidates who took the same items. The 24 raters who participated in the 2011 standard setting were faculty members who had taught in U.S. colleges and schools of pharmacy. The researcher used a hierarchical linear model to conduct a two-level (items nested within raters) analysis. The outcome variable was the rater fit indices. The two item characteristic-related variables accounted for 91% of the variance in the rater fit indices, suggesting that the ability to provide accurate proportion correct estimates for minimally qualified candidates was related to an item's difficulty level and content domain classification. By contrast, the ability to provide accurate proportion correct estimates for minimally qualified candidates was not related to a rater's gender or content domain expertise. The study's findings support the standard-setting experts' view that rater training which includes multiple practice rounds, discussions, interactions, and feedback can be influential in decreasing the variance in raters' proportion correct estimates.
機(jī)譯：這項研究的目的是確定兩個與評估者背景相關(guān)的變量（即評估者的性別和內(nèi)容領(lǐng)域的專業(yè)知識）和兩個與項目特征相關(guān)的變量（即項目的難度分類和內(nèi)容域分類）在多大程度上可以解釋在認(rèn)證檢查的標(biāo)準(zhǔn)設(shè)置范圍內(nèi)，評估者適合指數(shù)的差異。許可和認(rèn)證組織召集該領(lǐng)域的主題專家小組（即評估者），并讓他們參與標(biāo)準(zhǔn)制定過程，以推薦分?jǐn)?shù)（績效標(biāo)準(zhǔn)）以對熟練，知識淵博且能勝任的個人進(jìn)行分類。在標(biāo)準(zhǔn)設(shè)置過程中，評估者通常會檢查單個項目，然后提供評估者認(rèn)為可以正確回答每個項目的最低合格候選人比例的估計值。評估者擬合度是指各個評估者在提供這些估算值時所達(dá)到的準(zhǔn)確性或精密度。在這項研究中，擬合指數(shù)基于對200個項目的認(rèn)證考試中最低合格候選人的評分者比例正確估計的方差，以及對另一組采用相同資格的最低合格候選人的表現(xiàn)收集的經(jīng)驗數(shù)據(jù)項目。參加2011年標(biāo)準(zhǔn)制定的24位評估者是在美國大學(xué)和藥學(xué)院任教的教職員工。研究人員使用分層線性模型進(jìn)行了兩級（嵌套在評估者中的項目）分析。結(jié)果變量是評分者擬合指數(shù)。這兩個與項目特征相關(guān)的變量占評估者擬合指數(shù)方差的91％，這表明為最低合格候選人提供準(zhǔn)確比例正確估計的能力與該項目的難度水平和內(nèi)容域分類有關(guān)。相比之下，為最低資格的候選人提供準(zhǔn)確比例正確估計的能力與評估者的性別或內(nèi)容領(lǐng)域?qū)I(yè)知識無關(guān)。該研究結(jié)果支持標(biāo)準(zhǔn)制定專家的觀點，即評估者培訓(xùn)（包括多個實踐回合，討論，互動和反饋）可以降低評估者比例正確估計的方差。

著錄項

  • 作者

    Incrocci, Maria.;

  • 作者單位

    University of Illinois at Chicago.;

  • 授予單位 University of Illinois at Chicago.;
  • 學(xué)科 Educational psychology.
  • 學(xué)位 Ph.D.
  • 年度 2015
  • 頁碼 76 p.
  • 總頁數(shù) 76
  • 原文格式 PDF
  • 正文語種 eng
  • 中圖分類 遙感技術(shù);
  • 關(guān)鍵詞

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