Identifying Academically Gifted English-Language Learners Using Nonverbal Tests

Author:

Lohman David F.1,Korb Katrina A.2,Lakin Joni M.2

Affiliation:

1. University of Iowa,

2. University of Iowa

Abstract

In this study, the authors compare the validity of three nonverbal tests for the purpose of identifying academically gifted English-language learners (ELLs). Participants were 1,198 elementary children (approximately 40% ELLs). All were administered the Raven Standard Progressive Matrices (Raven), the Naglieri Nonverbal Ability Test (NNAT), and Form 6 of the Cognitive Abilities Test (CogAT). Results show that the U.S. national norms for the Raven substantially overestimate the number of high-scoring children; that because of errors in norming, the NNAT overestimates the number of both high-scoring and low-scoring children; that primary-level ELL children score especially poorly on the NNAT; that the standard error of measurement was twice as large for the NNAT as for the Raven or the CogAT; that ELL children scored .5 to .67 standard deviations lower than non-ELL children on the three nonverbal tests; and that none of the nonverbal tests predict achievement for ELL students very well. Putting Research to Use: Do nonverbal reasoning tests level the field for ELL children? Many practitioners have assumed that they do. However ELL children in this study scored 8 to 10 points lower than non-ELL children on the three nonverbal tests. The study also shows that practitioners cannot assume that national norms on the tests are of comparable quality. When put on the same scale as CogAT, Raven scores averaged 10 points higher than CogAT and NNAT scores. For NNAT, the mean is correct but the variability was up to 40% too large. Thus, when using national norms, both the Raven and NNAT will substantially overestimate the number of high-scoring children.

Publisher

SAGE Publications

Subject

Developmental and Educational Psychology,Education

Cited by 71 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3