Standardized Versus Naturalized: An Evaluation of Child Morphological and Syntactic Assessments

Jaclyn Shurman, Dorothy Leone
2015 International Journal of Undergraduate Research and Creative Activities  
This work has undergone a double-blind review by a minimum of two faculty members from institutions of higher learning from around the world. The faculty reviewers have expertise in disciplines closely related to those represented by this work. If possible, the work was also reviewed by undergraduates in collaboration with the faculty reviewers. Abstract Speech-language pathologists may choose to evaluate children's language using standardized or naturalized assessments. This study investigated
more » ... study investigated if the Clinical Evaluation of Language Fundamentals-Preschool 2 (CELF-P 2), a standardized assessment, and language sampling, a naturalized assessment, reveal the same information about children's linguistic competence and performance. Children ages 3.0-7.0 were assessed with specific focus on morphology and syntax. The participants completed four morphosyntactic-based subtests of the CELF-P 2. Additionally, play-based interactions, used to elicit natural language, were video-recorded. The CELF-P 2 was scored and language samples were transcribed and analyzed. Mean length of utterance (MLU) scores showed a slightly more variable trend around the mean than CELF-P 2 scores and there were no significant correlations between the two assessments. Furthermore, the two forms of assessment produced incongruous age equivalents for 66% of the participants (four out of six) and participants produced different morphosyntactic structures during each type of assessment. Thus, results indicated limitations and successes of the different assessment approaches. When used alone, either form of assessment did not provide a completely accurate representation of children's language acquisition. However, when used in conjunction, the two assessments may represent the linguistic competence and performance of children more accurately.
doi:10.7710/2168-0620.1046 fatcat:7fwi53af2bg7bieofmjqhjx2ta