Incorporating Computer-Aided Language Sample Analysis Into Clinical Practice

2010 ◽  
Vol 41 (2) ◽  
pp. 206-222 ◽  
Author(s):  
Lisa Hammett Price ◽  
Sean Hendricks ◽  
Colleen Cook
Keyword(s):  
Clinical Practice ◽  
Sample Analysis ◽  
Language Sample Analysis ◽  
Computer Aided ◽  
Language Sample

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.

Myths and Realities of Language Sample Analysis

2010 ◽  
Vol 17 (1) ◽  
pp. 4-8 ◽  
Author(s):  
John J. Heilmann
Keyword(s):  
Clinical Practice ◽  
Language Skills ◽  
Clinical Use ◽  
Sample Analysis ◽  
Speech Language Pathologists ◽  
Language Sample Analysis ◽  
Key Issues ◽  
Language Sample

Abstract While language sample analysis (LSA) is frequently recommended for assessing children’s language skills, many speech-language pathologists do not use it regularly. This article reviewed key issues surrounding clinical use of LSA to provide clinicians with a realistic overview of the process and encourage increased use of LSA in clinical practice.

scholarly journals Attitude of Korean Speech-Language Pathologists toward Usage of Language Sample Analysis and Computer-aided LSA

2020 ◽  
Vol 25 (3) ◽  
pp. 651-668
Author(s):  
YoonKyoung Lee ◽  
Jieun Choi ◽  
So Jung Oh ◽  
Ji Hye Yoon ◽  
Yu-Seop Kim
Keyword(s):  
Sample Analysis ◽  
Speech Language Pathologists ◽  
Language Sample Analysis ◽  
Computer Aided ◽  
Language Sample

The Many Things Language Sample Analysis Has Taught Me

2010 ◽  
Vol 17 (1) ◽  
pp. 32-37 ◽  
Author(s):  
C. Melanie Schuele
Keyword(s):  
Clinical Practice ◽  
Lessons Learned ◽  
Sample Analysis ◽  
Clinical Tool ◽  
Speech Language Pathologist ◽  
Research Activities ◽  
Language Sample Analysis ◽  
The Many ◽  
Language Sample

Abstract Although language sample analysis (LSA) has long been advocated as an important clinical tool, it is a time-consuming task. The time-consuming nature of LSA can reduce the likelihood of routine and extensive use of LSA in clinical practice. The purpose of this article is to advocate for routine and extensive use of LSA through consideration of lessons learned by one speech-language pathologist in her experience with LSA in clinical and research activities.

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

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.

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