Child-Level Predictors of Responsiveness to Evidence-Based Mathematics Intervention

Abstract

We identified child-level predictors of responsiveness to 2 types of mathematics (calculation and word-problem) intervention among 2nd-grade children with mathematics difficulty. Participants were 250 children in 107 classrooms in 23 schools pretested on mathematics and general cognitive measures and posttested on mathematics measures. We assigned classrooms randomly assigned to calculation intervention, word-problem intervention, or business-as-usual control. Intervention lasted 17 weeks. Path analyses indicated that scores on working memory and language comprehension assessments moderated responsiveness to calculation intervention. No moderators were identified for responsiveness to word-problem intervention. Across both intervention groups and the control group, attentive behavior predicted both outcomes. Initial calculation skill predicted the calculation outcome, and initial language comprehension predicted word-problem outcomes. These results indicate that screening for calculation intervention should include a focus on working memory, language comprehension, attentive behavior, and calculations. Screening for word-problem intervention should focus on attentive behavior and word problems.

Measuring the Quantity and Quality of Explicit Instructional Interactions in an Empirically Validated Tier 2 Kindergarten Mathematics Intervention

“…Relative to their typically achieving peers, students who begin their kindergarten year at risk of MLD often receive less support at home and in preschool to develop early number sense (Barnes et al, 2016). If initial mathematics achievement has important implications for students’ immediate and long-term mathematics outcomes (Clarke et al, 2019; Morgan et al, 2009; Powell, Cirino, & Malone, 2017), then it is plausible that where groups of students at risk of MLD begin their kindergarten year in mathematics is also a significant predictor of the quantity and quality of explicit instructional interactions they engage in during Tier 2 mathematics interventions to learn foundational mathematical content. An aim of this study was to address this hypothesis.…”

Conditional Process Analysis in Two-Instance Repeated-Measures Designs

“…For example, Manikandan et al (2016) surveyed women during two phases of their menstrual cycle and found that emotional regulation moderated the effect of menstrual phase on perceived control over anxiety-related events, but emotion regulation did not moderate the effect of phase on menstrual symptom severity. In another example, among students with math difficulties, those with higher working memory capacity benefited more from strategy training (pre-to-posttest) than those with lower working memory capacity (Powell, Cirino, & Malone, 2017).…”

Influence of initial mathematical competencies on the effectiveness of a classroom‐based intervention

“…We examined the combined results of two previous intervention research samples, one of which included students with mathematics learning difficulties (MLD) and attention deficit/hyperactivity disorder (ADHD), and the other comprising students without difficulties. Joint analysis of the data from these two samples allowed us to compare the different profiles of students which teachers work with in everyday classes, and also those of students who need specific interventions to avoid more severe difficulties in the future (Powell et al ., ). In this study, the diagnostic profile was deemed to be the covariant variable, especially considering that specific learning difficulties relating to mathematics have been labelled differently in the literature (e.g., ‘developmental dyscalculia’, ‘mathematical difficulties’, ‘mathematical learning difficulties/disabilities…’; Olsson, Östergren, & Träff, ).…”

“…() showed that students with a very low score in mathematics competencies at the age of 5 years (third year of kindergarten) also obtained a very low score at the age of 7 years (finishing first grade of primary education). This emphasizes the importance of adapting any interventions to an individual student's needs, especially in the face of possible learning difficulties, because these children are more at risk of developing severe mathematics deficits (Powell, Cirino, & Malone, ). Given that the acquirement of further knowledge is built upon the acquisition of previous knowledge (and that children present differences at this level) the efficacy of interventions may vary as a function of these initial competencies (Bailey et al ., ).…”

“…According to Powell et al . (), few if any interventions achieve universal responses, and little is known concerning child characteristics associated with inadequate responses. Thus, the purpose underlying this investigation was to analyse and characterize the improvement profiles of students with initially low, medium, and high mathematics competencies after completing a computer‐based intervention.…”