Predicting response to vocabulary intervention using dynamic assessment

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

Purpose: The purpose of this study was to examine how well students’ response to a morphological vocabulary intervention can be predicted before the start of the intervention from traditional static assessments and to determine whether a dynamic assessment with graduated prompts improves the prediction.
Method: A planned secondary analysis of a randomized trial of a morphological vocabulary intervention for fifth-grade students with limited vocabulary was conducted. Response to this intervention was examined for 111 participants based on their development in definitions of morphologically transparent words from pretest to posttest. Traditional static measures of vocabulary, knowledge of morphology, and morphological analysis as well as a dynamic assessment of morphological analysis were evaluated as predictors of students’ response to intervention.
Results: The static pretest measures predicted more than half of the overall variance in students’ response to intervention and provided a good classification of students with subsequent poor or good response to intervention. The single best static predictor was the static assessment of morphological analysis. Furthermore, the dynamic assessment added significantly to the prediction of the overall variance in students’ response to intervention as well as to the correct early classification of students as poor or good responders.
Conclusions: The results suggest that an acceptable level of prediction of students’ response to morphological vocabulary intervention can be obtained by means of a couple of static morphological measures. The present study also provides evidence for the added predictive value of a dynamic assessment of morphological analysis.
OriginalsprogEngelsk
TidsskriftLanguage, Speech and Hearing Services in Schools
Vol/bind51
Udgave nummer4
Sider (fra-til)1112-1123
Antal sider12
ISSN0161-1461
DOI
StatusUdgivet - okt. 2020

ID: 250379647