Sampling Utterances and Grammatical Analysis Revised (SUGAR): New Normative Values for Language Sample Analysis Measures Purpose The purpose of this study was to document whether mean length of utterance (MLUS), total number of words (TNW), clauses per sentence (CPS), and/or words per sentence (WPS) demonstrated age-related changes in children with typical language and to document the average time to collect, transcribe, and analyze conversational language ... Research Article
Research Article  |   July 26, 2017
Sampling Utterances and Grammatical Analysis Revised (SUGAR): New Normative Values for Language Sample Analysis Measures
 
Author Affiliations & Notes
  • Stacey L. Pavelko
    James Madison University, Harrisonburg, VA
  • Robert E. Owens, Jr.
    The College of Saint Rose, Albany, NY
  • Correspondence Stacey L. Pavelko: pavelksl@jmu.edu
  • Disclosure: The authors have declared that no competing interests existed at the time of publication.
    Disclosure: The authors have declared that no competing interests existed at the time of publication.×
  • Editor-in-Chief: Shelley Gray
    Editor-in-Chief: Shelley Gray×
  • Editor: Kerry Ebert
    Editor: Kerry Ebert×
Article Information
School-Based Settings / Research Issues, Methods & Evidence-Based Practice / Normal Language Processing / Research Articles
Research Article   |   July 26, 2017
Sampling Utterances and Grammatical Analysis Revised (SUGAR): New Normative Values for Language Sample Analysis Measures
Language, Speech, and Hearing Services in Schools, July 2017, Vol. 48, 197-215. doi:10.1044/2017_LSHSS-17-0022
History: Received February 15, 2017 , Revised March 20, 2017 , Accepted May 22, 2017
 
Language, Speech, and Hearing Services in Schools, July 2017, Vol. 48, 197-215. doi:10.1044/2017_LSHSS-17-0022
History: Received February 15, 2017; Revised March 20, 2017; Accepted May 22, 2017

Purpose The purpose of this study was to document whether mean length of utterance (MLUS), total number of words (TNW), clauses per sentence (CPS), and/or words per sentence (WPS) demonstrated age-related changes in children with typical language and to document the average time to collect, transcribe, and analyze conversational language samples.

Method Participants were 385 typically developing children (ages 3;0–7;11 [years;months]), with a final sample size of 270 participants (133 males and 137 females). Fifty-utterance conversational language samples were collected using a language sampling protocol. Four language sample analysis (LSA) metrics (i.e., MLUS, TNW, CPS, WPS) were calculated from the samples.

Results Results indicated statistically significant age-related increases in the four metrics. The average time to collect, transcribe, and analyze each sample was 20.91 min (SD = 3.97; range = 10.55–33.37).

Conclusion MLUS, TNW, CPS, and WPS may be used with other assessment data to document age-related changes in children's language. When used as part of an assessment, the results from all of the metrics should be considered. Considering results from only 1 individual metric is not encouraged. These results suggest LSA may be completed in approximately 20 min, which is less than the average time to administer a standardized, norm-referenced language assessment.

Acknowledgments
The authors would like to thank all the various personnel from the schools, preschools, and day cares who graciously allowed us to conduct the research study at their respective facilities. We thank the families who participated in this research study. We would also like to thank Marie Ireland, who carefully reviewed several drafts of the manuscript and offered constructive feedback that significantly improved the clarity and quality of the writing. Finally, we would like to thank the following individuals for their assistance: Katherine Allen, Sara Carver, Amanda Cassaro, Alyssa Cavallari, Mary Coble, Katherine Davies, Kristin DiDonato, Alanna Egan, Lynda Feenaughty, Anne Feldman, Karen Figliotti, Erin Filippini, Melissa Galvin, Holly Garrison, Jessica Gormley, Anne Halstead, Stephanie Halvax, Samantha Hartnett, Kelsey Hogel, Katelynn Imagna, Elizabeth Johnson, Marc Johnson, Andrew Kanuck, Nicole Kenney, Sara Korman, Katie Kreidler, Amy LaFleur, Zhaleh Lavasani, Nicole LeFever, Stephanie Loccisano, Katherine Lyle, Carolyn Mahon, Catherine Manoni, Dani Mansi, Alexis Mazzeo, Kerry McTiernan, Leanne Meidenbauer, Hetal Patel, Jordan Nieto, Kaitlyn Raffe, Jessica Raes, Kaitlyn Risberg, Jyl Ristau, Catherine Sligar, Lauren Smith, Andrea Sorber, Sara Starowicz, Kristen Stewart, Mary-Clare Stokes, Lauren Szpakowski, Eric Tyler, Margaret Wayne, Kristina Whelpley, Kathryn Wind, and Sara Young.
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