Examining Measures and Methods for Determining Students’ Responsiveness to Data-Based Early Writing Instruction

ABSTRACT Purpose We examined approaches to determining students’ responsiveness to data-based instruction (DBI) in early writing across methods (final status and growth) and measures (proximal writing curriculum-based measures and a distal standardized writing measure), as well as student- and teacher-level predictors of responsiveness. Method The analytic sample included 57 teachers and their 131 students (2.5 mean grade-level, 33.6% female, 61.0% White) who (a) were identified as having intensive early writing needs, (b) were enrolled in the treatment condition of a larger randomized control trial and thus participated in early writing DBI, and (c) had available screening, pre- and post-test, and progress monitoring data. We compared the number and percentage of students identified as more or less responsive to 20 weeks of DBI across methods and measures. Then, we examined whether students’ responsiveness could be predicted by different student- or teacher-level factors using hierarchical logistic regression. Results Findings suggested that initial performance was the most consistently significant predictor of students’ responsiveness to DBI across the models, and that student factors (special education/English language learner eligibility) and one teacher factor (self-efficacy) sometimes appeared to play a role. Conclusion Overall, the proportion of more versus less responsive students varied depending on the methods and measures used to determine responsiveness, as did predictors of responsiveness. Implications for selecting measures and methods to identify students’ responsiveness to DBI in early writing for further research and practice are discussed.