An examination of the relationship of sample size and mean length of utterance for children with developmental language impairment

Author:

Casby Michael W1

Affiliation:

1. Michigan State University, USA,

Abstract

Mean length of utterance (MLU) is a frequently used measure of the expressive language of young children. The suggested conventional, contemporary, clinical practice is to calculate it from a language sample of a minimum of 50 to100 contiguous intelligible utterances. This practice places considerable strain on professionals working with young children with language disorders, for it is often impractical to devote the time needed to collect, transcribe, and analyse the recommended number of utterances. This research investigated the consistency of MLU calculated across language samples of different sizes for the same children. Transcripts of expressive language samples of research participants with developmental language impairment were analysed, with MLU being calculated on samples of varying sizes. The language samples ranged from 10 to 150 utterances. Measures of statistical differences and consistency of MLU across the various language samples were examined. Results demonstrate that, on the whole, one can reliably and efficiently determine MLU on much smaller language samples than that typically recommended, although, not surprisingly, there may be notable individual differences attesting to the vicissitudes of MLU.

Publisher

SAGE Publications

Subject

Speech and Hearing,Linguistics and Language,Clinical Psychology,Developmental and Educational Psychology,Language and Linguistics,Education

Cited by 29 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