scholarly journals Language Sample Analysis of Writing in Children and Adolescents

2020 ◽  
Vol 40 (2) ◽  
pp. 202-220
Author(s):  
Cheryl M. Scott
Keyword(s):  
Children And Adolescents ◽  
Sample Analysis ◽  
Language Sample Analysis ◽  
Language Sample

Assessing Functional Language in School-Aged Children Using Language Sample Analysis

2020 ◽  
Vol 5 (3) ◽  
pp. 622-636
Author(s):  
John Heilmann ◽  
Alexander Tucci ◽  
Elena Plante ◽  
Jon F. Miller
Keyword(s):  
Computer Hardware ◽  
School Age Children ◽  
Functional Language ◽  
School Age ◽  
Clinical Use ◽  
Sample Analysis ◽  
Validity And Reliability ◽  
Language Sample Analysis ◽  
Accuracy And Repeatability ◽  
Language Sample

Purpose The goal of this clinical focus article is to illustrate how speech-language pathologists can document the functional language of school-age children using language sample analysis (LSA). Advances in computer hardware and software are detailed making LSA more accessible for clinical use. Method This clinical focus article illustrates how documenting school-age student's communicative functioning is central to comprehensive assessment and how using LSA can meet multiple needs within this assessment. LSA can document students' meaningful participation in their daily life through assessment of their language used during everyday tasks. The many advances in computerized LSA are detailed with a primary focus on the Systematic Analysis of Language Transcripts (Miller & Iglesias, 2019). The LSA process is reviewed detailing the steps necessary for computers to calculate word, morpheme, utterance, and discourse features of functional language. Conclusion These advances in computer technology and software development have made LSA clinically feasible through standardized elicitation and transcription methods that improve accuracy and repeatability. In addition to improved accuracy, validity, and reliability of LSA, databases of typical speakers to document status and automated report writing more than justify the time required. Software now provides many innovations that make LSA simpler and more accessible for clinical use. Supplemental Material https://doi.org/10.23641/asha.12456719

Issues in Language Sample Collection and Analysis With Children Using AAC

2014 ◽  
Vol 23 (2) ◽  
pp. 65-74 ◽  
Author(s):  
Gail Van Tatenhove
Keyword(s):  
Clinical Practice ◽  
Augmentative And Alternative Communication ◽  
Language Production ◽  
Expressive Language ◽  
Sample Analysis ◽  
Alternative Communication ◽  
Sample Collection ◽  
Speech Language Pathologists ◽  
Language Sample Analysis ◽  
Language Sample

Language sample analysis is considered one of the best methods of evaluating expressive language production in speaking children. However, the practice of language sample collection and analysis is complicated for speech-language pathologists working with children who use augmentative and alternative communication (AAC) devices. This article identifies six issues regarding use of language sample collection and analysis in clinical practice with children who use AAC devices. The purpose of this article is to encourage speech-language pathologists practicing in the area of AAC to utilize language sample collection and analysis as part of ongoing AAC assessment.

The Clinical Utility of Language Samples

2010 ◽  
Vol 17 (1) ◽  
pp. 9-15 ◽  
Author(s):  
Amy Costanza-Smith
Keyword(s):  
Standardized Tests ◽  
Clinical Utility ◽  
Language Disorders ◽  
Standardized Assessments ◽  
School Age ◽  
Sample Analysis ◽  
Speech Language Pathologists ◽  
Language Sample Analysis ◽  
Language Sample

Abstract Speech-language pathologists typically use standardized assessments to diagnose language disorders. Although standardized tests are important in diagnosing school-age language disorders, the use of language sample analysis should not be ignored. This article summarizes the benefits of language sample analysis and introduces considerations for collecting and analyzing language samples.

Language Sample Analysis and Elicitation Technique Effects in Bilingual Children With and Without Language Impairment

2017 ◽  
Vol 60 (10) ◽  
pp. 2852-2864 ◽  
Author(s):  
Maria Kapantzoglou ◽  
Gerasimos Fergadiotis ◽  
M. Adelaida Restrepo
Keyword(s):  
Language Impairment ◽  
Classification Accuracy ◽  
Sentence Length ◽  
Primary Language ◽  
Sample Analysis ◽  
Story Retelling ◽  
Language Sample Analysis ◽  
English Speaking ◽  
Primary Language Impairment ◽  
Language Sample

Purpose This study examined whether the language sample elicitation technique (i.e., storytelling and story-retelling tasks with pictorial support) affects lexical diversity (D), grammaticality (grammatical errors per communication unit [GE/CU]), sentence length (mean length of utterance in words [MLUw]), and sentence complexity (subordination index [SI]), which are commonly used indices for diagnosing primary language impairment in Spanish–English-speaking children in the United States. Method Twenty bilingual Spanish–English-speaking children with typical language development and 20 with primary language impairment participated in the study. Four analyses of variance were conducted to evaluate the effect of language elicitation technique and group on D, GE/CU, MLUw, and SI. Also, 2 discriminant analyses were conducted to assess which indices were more effective for story retelling and storytelling and their classification accuracy across elicitation techniques. Results D, MLUw, and SI were influenced by the type of elicitation technique, but GE/CU was not. The classification accuracy of language sample analysis was greater in story retelling than in storytelling, with GE/CU and D being useful indicators of language abilities in story retelling and GE/CU and SI in storytelling. Conclusion Two indices in language sample analysis may be sufficient for diagnosis in 4- to 5-year-old bilingual Spanish–English-speaking children.

Use of Language Sample Analysis by School-Based SLPs: Results of a Nationwide Survey

2016 ◽  
Vol 47 (3) ◽  
pp. 246-258 ◽  
Author(s):  
Stacey L. Pavelko ◽  
Robert E. Owens ◽  
Marie Ireland ◽  
Debbie L. Hahs-Vaughn
Keyword(s):  
High School Students ◽  
Real Time ◽  
Nationwide Survey ◽  
Sample Analysis ◽  
School Students ◽  
Factors Affecting ◽  
School Based ◽  
Language Sample Analysis ◽  
Evidenced Based ◽  
Language Sample

Purpose This article examines use of language sample analysis (LSA) by school-based speech-language pathologists (SLPs), including characteristics of language samples, methods of transcription and analysis, barriers to LSA use, and factors affecting LSA use, such as American Speech-Language-Hearing Association certification, number of years' experience, and caseload characteristics. Method School-based SLPs responded to an invitation to complete an electronic survey related to LSA. Results One third of respondents indicated they did not use LSA during the 2012–2013 school year. SLPs who served middle and high school students were less likely to use LSA. Most respondents reported using conversation to analyze fewer than 10 samples and transcribing in real time. Additional analyses revealed that SLPs who had 3 or fewer years of experience and who analyzed fewer than 20 language samples per year were statistically less likely to report using real-time transcription. The most frequently cited barrier to using LSA was “LSA is too time-consuming.” Conclusion Many school-based SLPs do not routinely use LSA. Further, many did not report engaging in evidence-based practices, such as recording samples, using established protocols, or using tasks designed to elicit complex syntax. These results indicate a continued need for professional development regarding evidenced-based practices relative to LSA use.

scholarly journals Expressive Language in Preschoolers Born Preterm: Results of Language Sample Analysis and Standardized Assessment

2019 ◽  
Vol 62 (4) ◽  
pp. 884-895 ◽  
Author(s):  
Caitlin M. Imgrund ◽  
Diane F. Loeb ◽  
Steven M. Barlow
Keyword(s):  
Language Skills ◽  
Expressive Language ◽  
Full Term ◽  
Language Skill ◽  
Standardized Assessment ◽  
Group Differences ◽  
Sample Analysis ◽  
Assessment Scores ◽  
Language Sample Analysis ◽  
Language Sample

Purpose Preschoolers born preterm are at an increased risk for the development of language impairments. The primary objective of this study was to document the expressive language skills of preschoolers born preterm through 2 assessment procedures, language sample analysis, and standardized assessment. A secondary objective was to investigate the role of nonlinguistic factors in standardized assessment scores. Method The language skills of 29 children born preterm (mean gestational age of 31 weeks) were compared to a group of 29 preschoolers born full term. Language samples were collected during free play and objective measures of semantic and grammatical skills were calculated. Likewise, grammatical and semantic measures of language were obtained from a standardized assessment. Information on nonlinguistic factors, including attention, hyperactivity, and nonverbal intelligence quotient, was also collected. Results The results of analyses of variance indicated that the children in the PT group had significantly poorer performance than the children born full term on all of the measures of language skill obtained from the language sample analysis. Group differences were found for only 1 measure of language skill obtained from the standardized assessments. Nonverbal factors were not found to account for group differences in assessment scores. Conclusions Generally, the children born preterm performed more poorly when language skill was measured via language sample analysis than standardized assessment. These findings underscore the importance of using language sample analysis in conjunction with standardized assessment in the evaluation of children's developing language skills.

Sampling Utterances and Grammatical Analysis Revised (SUGAR): Quantitative Values for Language Sample Analysis Measures in 7- to 11-Year-Old Children

2020 ◽  
Vol 51 (3) ◽  
pp. 734-744
Author(s):  
Robert E. Owens ◽  
Stacey L. Pavelko
Keyword(s):  
Typically Developing ◽  
Sample Analysis ◽  
Grammatical Analysis ◽  
Age Related ◽  
Final Sample ◽  
Language Sampling ◽  
Language Sample Analysis ◽  
Conversational Language ◽  
Mean Length Of Utterance ◽  
Language Sample

Purpose The purpose of this study was to document whether mean length of utterance SUGAR (MLU S ), total number of words (TNW), clauses per sentence (CPS), and/or words per sentence (WPS) demonstrated age-related changes in children with typically developing language, aged 7;0–10;11 (years;months). Method Participants were 132 typically developing children (aged 7;0–10;11), with a final sample size of 112 participants (57 boys and 55 girls). Fifty utterance conversational language samples were collected using a language sampling protocol. Four language sample analysis metrics (i.e., MLU S , TNW, CPS, and WPS) were calculated from the samples. Results Results indicated statistically significant age-related increases in three (MLU S , TNW, and WPS) of the four metrics. Conclusions MLU S , TNW, CPS, and WPS may be used with other assessment data to document age-related language changes in children aged 7;0–10;11. When combined with previous data from younger (aged 3;0–7;11) children (Pavelko & Owens, 2017), the data suggest that these metrics offer a set of measures that can be used to assess children's conversational language skills from preschool through late elementary school.

Sign in / Sign up

Export Citation Format

Share Document