Ongoing Teacher Support for Data-Based Individualization: A Meta-Analysis and Synthesis.

Abstract

Although data-based individualization (DBI) has positive effects on learning outcomes for students with learning difficulties, this framework can be difficult for teachers to implement due to its complexity and contextual barriers. The first aim of this synthesis was to investigate the effects of ongoing professional development (PD) support for DBI on teachers' DBI knowledge, skills, beliefs, and fidelity and the achievement of preschool to Grade 12 students with academic difficulties. The second aim was to report on characteristics of this support and explore whether features were associated with effects. We identified 26 studies, 16 and 22 of which examined teacher and student outcomes, respectively. Meta-analyses indicated that the weighted mean effect size for DBI with ongoing support for teachers was g = 0.86 (95% confidence interval [CI] = [0.43, 1.28], p < .001, I² = 83.74%, k = 46) and g = 0.31 for students (95% CI = [0.19, 0.42], p < .001, I² = 61.38%, k = 103). We did not identify moderators of treatment effects. However, subset effects were descriptively larger for ongoing support that targeted data-based instructional changes or included collaborative problem-solving. Researchers may improve future DBI PD by focusing on support for teachers' instructional changes, describing support practices in greater detail, and advancing technological supports.