ABSTRACT

Written expression curriculum-based measurement (WE-CBM) is a formative assessment approach for screening and progress monitoring. To extend evaluation of WE-CBM, we compared hand-calculated and automated scoring approaches in relation to the number of screening samples needed per student for valid scores, the long-term predictive validity and diagnostic accuracy of scores, and predictive and diagnostic bias for underrepresented student groups. Second- to fifth-grade students (n = 609) completed five WE-CBM tasks during one academic year and a standardised writing test in fourth and seventh grade. Averaging WE-CBM scores across multiple samples improved validity. Complex hand-calculated metrics and automated tools outperformed simpler metrics for the long-term prediction of writing performance. No evidence of bias was observed between African American and Hispanic students. The study will illustrate the absence of test bias as necessary condition for fair and equitable screening procedures and the importance of future research to include comparisons with majority groups.

摘要

基于书面表达课程的测量（WE-CBM）是一种用于筛选和进度监测的形成性评估方法。为了扩展对 WE-CBM 的评估，我们比较了手动计算和自动评分方法，与每个学生有效分数所需的筛选样本数量、分数的长期预测有效性和诊断准确性以及预测和诊断偏差有关代表性不足的学生群体。二至五年级学生（n= 609）在一学年内完成了五项 WE-CBM 任务，并在四年级和七年级完成了标准化写作测试。跨多个样本平均 WE-CBM 分数提高了有效性。复杂的手工计算指标和自动化工具在长期预测写作表现方面优于简单的指标。在非裔美国人和西班牙裔学生之间没有观察到偏见的证据。该研究将说明不存在测试偏倚作为公平和公正筛查程序的必要条件，以及未来研究包括与多数群体比较的重要性。