Shanahan Emma, Choi Seohyeon, An Jechun, Casey-Wilke Bess, Birinci Seyma, Roberts Caroline, Reno Emily
The University of Texas-Austin, USA.
University of Minnesota Twin Cities, Minneapolis, USA.
J Learn Disabil. 2025 Jan-Feb;58(1):3-18. doi: 10.1177/00222194241271335. Epub 2024 Sep 5.
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 = 0.86 (95% confidence interval [CI] = [0.43, 1.28], < .001, = 83.74%, = 46) and = 0.31 for students (95% CI = [0.19, 0.42], < .001, = 61.38%, = 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.
尽管基于数据的个性化教学（DBI）对学习困难的学生的学习成果有积极影响，但由于其复杂性和情境障碍，教师实施该框架可能会有困难。本综述的首要目的是调查持续专业发展（PD）支持对教师的DBI知识、技能、信念、保真度以及学前至12年级学业困难学生成绩的影响。第二个目的是报告这种支持的特点，并探讨这些特点是否与效果相关。我们确定了26项研究，其中16项和22项分别考察了教师和学生的成果。荟萃分析表明，在持续支持下教师实施DBI的加权平均效应量为 = 0.86（95%置信区间[CI] = [0.43, 1.28]， <.001， = 83.74%， = 46），学生的加权平均效应量为 = 0.31（95% CI = [0.19, 0.42]， <.001， = 61.38%， = 103）。我们未发现治疗效果的调节因素。然而，对于针对基于数据的教学变革或包括协作解决问题的持续支持，描述性的子集效应更大。研究人员可以通过关注对教师教学变革的支持、更详细地描述支持实践以及推进技术支持来改进未来的DBI专业发展。
