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Examining Recall Memory in Infancy and Early Childhood Using the Elicited Imitation Paradigm
Published on: April 28, 2016
Novel Approaches to Language Assessment Part 2: Evaluating Measures of Effort in a Sentence Recall Task for
Tracy Preza1, Dancheng Liu2, Carol A Miller3
1Department of Speech and Hearing Science, University of Illinois Urbana-Champaign.
Purpose:
Children with developmental language disorder (DLD) produce more speech disruptions and have a slower speech rate than their peers. This study validated measures of effortful sentence production by examining their association with general language ability and differences between groups of children with DLD and typical language development (TLD). Measures of effort were expected to be related to general language ability, and children with DLD were expected to produce more stall-type disruptions (i.e., repetitions, filled pauses, and unfilled pauses) and use fewer words per minute (WPM) than their peers with TLD.
Method:
Audio-recorded responses to the Redmond Sentence Recall task for 139 children with TLD (Mage = 86.85 months) and 58 children with DLD (Mage = 90.64 months) were transcribed, aligned to the audio, and coded for sentence disruptions using the Codes for the Human Analysis of Transcripts form from TalkBank. A custom-made Python script computed measures of stall rate, nondisrupted rate (e.g., the percentage of utterances with no disruptions), and WPM and were examined relative to child performance on the Clinical Evaluation of Language Fundamentals-Fourth Edition.
Results:
When controlling for age, stall rate and nondisrupted rate were moderately correlated with general language ability, and WPM was strongly correlated with general language ability. The DLD group used significantly more stalls and fewer WPM and nondisrupted utterances than did the TLD group.
Conclusions:
The findings demonstrate that measures of effortful sentence production are systematically associated with language ability. Future directions for leveraging artificial intelligence to automate these measures and exploring their utility as value-added indicators of DLD are discussed.
