Journal of Learning Disabilities最新文献

School context can shape relative intervention response in myriad ways due to factors, such as instructional quality, resource allocation, peer effects, and correlations between the school context and characteristics of enrolled students (e.g., higher-poverty students attending higher-poverty schools). In the current study, we used data from 16,000 U.S. Grade 3 students in a community-based supplemental reading intervention program to investigate the degree to which school context factors (percentage eligible for free/reduced-price lunch [FRPL], school-level achievement) relate to the differences in triannual reading fluency growth rates between students actively receiving supplemental intervention (active recipients) and those that formerly received intervention (and therefore only received general class instruction at this time; former recipients). Using Bayesian multilevel modeling, our findings indicate that school-level FRPL eligibility played a more prominent factor in growth rate differences between these two groups than school-level reading achievement. However, school-level reading achievement was much more strongly related to reading fluency differences between active and former intervention recipients at the beginning of the school year (when controlling for FRPL). Implications for investigating school-level heterogeneity in intervention response and sustainability are discussed.

Children with developmental dyslexia (DD) display partially preserved morphology skills which they rely upon for reading and spelling. Therefore, we conducted explicit and intensive training of derivational morphology in French and Swiss individuals with DD, ages 9 to 14 years, in order to assess its effect on: morphological awareness, reading (speed and accuracy), and spelling. Our pre-posttest design included a group trained in derivational morphology and a group of children who continued their business-as-usual rehabilitation program with their speech-language therapist. Results showed effects on morphological awareness and on the spelling of complex words, with a large between-group effect size for trained items and a large to moderate effect size for untrained items. All these gains tended to be maintained over time on the delayed posttest, 2 months later. For reading, the results were more contrasted, with large between-group effect sizes for accuracy and speed for trained items, reducing to a small effect for accuracy on the delayed posttest. For untrained items, small effects were observed on accuracy (at both posttests) but not on speed. These results are very promising and argue in favor of using derivational morphology as a medium to improve literacy skills in French-speaking children and adolescents with DD.

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.

Data-based instruction (DBI) is a process in which teachers use progress data to make ongoing instructional decisions for students with learning disabilities. Curriculum-based measurement (CBM) is a common form of progress monitoring, and CBM data are placed on a graph to guide decision-making. Despite the central role that graph interpretation plays in the successful implementation of DBI, relatively little attention has been devoted to investigating this skill among special education teachers. In the present study, we examined the data decisions of 32 U.S. pre-service special education teachers (29 females and 3 males). Participants viewed data presented sequentially on CBM progress graphs and used a think-aloud procedure to explain their reasoning each time they indicated they would make instructional changes. We also asked participants to make the same type of decisions in response to static CBM progress graphs depicting 10 weeks of data. Overall, there was inconsistency in pre-service teachers' responses related to when or why they would make an instructional change. Decisions were often influenced by graph-related features, such as variability in the data. Furthermore, responses suggested misunderstandings that led to premature instructional change decisions and reliance on individual data points.

In a multiyear, multisite, randomized control trial, we examined the effects of comprehensive professional development designed to support teachers' data-based instruction (DBI) for students with intensive early writing needs. Teachers (N = 154; primarily special educators or intervention specialists) were assigned randomly to a treatment group (n = 76), in which they received tools, learning, and coaching to support their DBI implementation over 20 weeks, or to a control group (n = 78). Students either received DBI in early writing (n = 155) from treatment teachers or their usual writing instruction (n = 154) from control teachers. Treatment teachers outperformed controls on measures of DBI knowledge and skills (d = 1.57) and self-efficacy for writing instruction (d = .94), and treatment students outperformed controls on proximal and distal writing outcomes (ds = .14-.29). Student characteristics (grade, special education status, English learner status, and race/ethnicity) did not moderate intervention effects. We discuss findings in terms of the importance of supporting students with intensive learning needs, the efficacy and feasibility of implementing DBI-TLC, and implications for pre- and in-service teacher training and support.

Word problem-solving (WPS) poses a significant challenge for many students, particularly those with mathematics difficulties (MD), hindering their overall mathematical development. To improve WPS proficiency, providing individualized and intensive interventions is critical. This umbrella review examined 11 medium- to high-quality meta-analyses to identify intervention and participant characteristics, informed by the Taxonomy of Intervention Intensity (TII) framework, that consistently moderate WPS outcomes for students with MD. Our analysis identified four characteristics with consistent moderating effects: intervention model, number of treatment sessions, group size, and academic risk area. This result suggests that these variables are potential considerations when customizing and intensifying WPS interventions to maximize their effectiveness for students with MD. We discuss the implications of these findings for practice and research and acknowledge the limitations of our review.