Mathematics Interventions for Adolescents with Mathematics Difficulties: A Meta‐Analysis

2021 ◽  
Author(s):  
Jonté A. Myers ◽  
Mary T. Brownell ◽  
Cynthia C. Griffin ◽  
Elizabeth M. Hughes ◽  
Bradley S. Witzel ◽  
...  
Keyword(s):  
Meta Analysis ◽  
Mathematics Interventions ◽  
Mathematics Difficulties

The Effects of Tier 2 Mathematics Interventions for Students With Mathematics Difficulties: A Meta-Analysis

2020 ◽  
pp. 001440292096918
Author(s):  
Asha K. Jitendra ◽  
Ahmed Alghamdi ◽  
Rebecca Edmunds ◽  
Nicole M. McKevett ◽  
John Mouanoutoua ◽  
...  
Keyword(s):  
Variance Estimation ◽  
Meta Analysis ◽  
Experimental Studies ◽  
Future Research ◽  
Tier 2 ◽  
Mathematics Interventions ◽  
Treatment Groups ◽  
Tier 2 Interventions ◽  
Mathematics Difficulties ◽  
Quasi Experimental

This meta-analysis examined the effectiveness of supplemental Tier-2 mathematics interventions for students with mathematics difficulties (MD). We reviewed 39 experimental and quasi-experimental studies that included 40 independent samples, with 61 treatment groups. Utilizing robust variance estimation (RVE), results revealed a treatment effect of 0.41. Mixed-effects meta-regression analyses revealed that Tier-2 interventions were moderated by intervention model type, group size, and type of measure. We present recommendations for future research and implementation of mathematics practices.

Mathematics Interventions for Upper Elementary and Secondary Students: A Meta-Analysis of Research

2017 ◽  
Vol 39 (6) ◽  
pp. 327-340 ◽  
Author(s):  
Elizabeth A. Stevens ◽  
Melissa A. Rodgers ◽  
Sarah R. Powell
Keyword(s):  
Secondary Students ◽  
Variance Estimation ◽  
Meta Analysis ◽  
Upper Elementary ◽  
Mathematics Interventions ◽  
Final Model ◽  
Information Research ◽  
Comparison Groups ◽  
Extreme Variability ◽  
Robust Variance Estimation

The purpose of this review was to conduct a meta-analysis of 25 years of mathematics interventions for students with mathematics difficulty or disability in Grades 4 through 12. A search of the literature yielded 25 studies that met the inclusion criteria. Studies were coded to extract important study information (e.g., participant information, research design, description of treatment, and comparison groups) and data needed to calculate Hedge’s g. We used robust variance estimation (RVE) to address dependence resulting from multiple outcomes per study. The RVE random-effects model estimated a treatment effect of 0.85. After adjusting for small-study effects, the final model estimated an underlying, moderate effect of 0.49 with a large amount of unexplained heterogeneity between studies. Studies with more than 15 hr of treatment and those focused on fraction content significantly moderated mathematics outcomes. Findings are limited by extreme variability across study estimates, the lack of standardized mathematics measures, and a limited number of studies across 25 years of research.

Mathematical Interventions for Secondary Students With Learning Disabilities and Mathematics Difficulties: A Meta-Analysis

2017 ◽  
Vol 84 (2) ◽  
pp. 177-196 ◽  
Author(s):  
Asha K. Jitendra ◽  
Amy E. Lein ◽  
Soo-hyun Im ◽  
Ahmed A. Alghamdi ◽  
Scott B. Hefte ◽  
...  
Keyword(s):  
Learning Disabilities ◽  
Secondary Students ◽  
Meta Analysis ◽  
Experimental Studies ◽  
Control Group ◽  
Students With Learning Disabilities ◽  
Control Group Design ◽  
Mathematics Difficulties ◽  
Quasi Experimental ◽  
And Mathematics

This meta-analysis is the first to provide a quantitative synthesis of empirical evaluations of mathematical intervention programs implemented in secondary schools for students with learning disabilities and mathematics difficulties. Included studies used a treatment-control group design. A total of 19 experimental and quasi-experimental studies containing 20 independent samples met study inclusion criteria. Results of a random effects model analysis indicated that mathematical interventions influence mathematics outcomes ( g = 0.37, 95% confidence interval [0.18, 0.56]) for students with learning disabilities and mathematics difficulties. In addition, instructional time moderated the relation between mathematics interventions and student learning. Limitations of the study, future directions for research, and implications for practice are discussed.

Ecological and Population Validity of Mathematics Interventions for Diverse Students With Low Mathematics Achievement: A Meta-Analysis

2021 ◽  
pp. 073194872110103
Author(s):  
Minyi Shih Dennis ◽  
Audrey M. Sorrells ◽  
Jacquelyn Chovanes ◽  
Elisheba W. Kiru
Keyword(s):  
Mathematics Achievement ◽  
External Validity ◽  
Intervention Studies ◽  
Meta Analysis ◽  
Intervention Research ◽  
Diverse Students ◽  
Mathematics Interventions ◽  
Cultural Contexts

This meta-analysis examined the ecological and population validity of intervention research for students with low mathematics achievement (SWLMA). Forty-four studies published between 2005 and 2019 that met the inclusionary criterion were included in this analysis. Our findings suggest, to improve the external validity and generalizability of research, more detailed descriptions of participants and the socio-cultural contexts of the intervention studies are warranted.

Understanding and Accessing Standards-Based Mathematics for Students With Mathematics Difficulties

2012 ◽  
Vol 36 (1) ◽  
pp. 4-8 ◽  
Author(s):  
Asha K. Jitendra
Keyword(s):  
At Risk ◽  
Learning Disabilities ◽  
Instructional Practices ◽  
Student Outcomes ◽  
Special Issue ◽  
Students With Learning Disabilities ◽  
Mathematics Interventions ◽  
Mathematics Difficulties

In this introduction to the special issue, the author provides a brief overview of (a) standards-based mathematics and implications for students with learning disabilities and those at risk for mathematics difficulties and (b) research on mathematics interventions/instructional practices and student outcomes. Furthermore, the author highlights how the articles in this special issue address these areas. The article concludes with a description of the purposes of this special issue.

scholarly journals A Systematic Review of the Quality of Reporting in Mathematics Meta-Analyses for Students with or at Risk of Disabilities Coding Protocol

2021 ◽  
Author(s):  
Gena Nelson
Keyword(s):  
Systematic Review ◽  
At Risk ◽  
Special Education ◽  
Meta Analysis ◽  
Grey Literature ◽  
Outcome Variable ◽  
Quality Of Reporting ◽  
Mathematics Interventions ◽  
Screening Process ◽  
Meta Analyses

The purpose of this document is to provide readers with the coding protocol that authors used to code 22 meta-analyses focused on mathematics interventions for students with or at-risk of disabilities. The purpose of the systematic review was to evaluate reporting quality in meta-analyses focused on mathematics interventions for students with or at risk of disabilities. To identify meta-analyses for inclusion, we considered peer-reviewed literature published between 2000 and 2020; we searched five education-focused electronic databases, scanned the table of contents of six special education journals, reviewed the curriculum vitae of researchers who frequently publish meta-analyses in mathematics and special education, and scanned the reference lists of meta-analyses that met inclusion criteria. To be included in this systematic review, meta-analyses must have reported on the effectiveness of mathematics-focused interventions, provided a summary effect for a mathematics outcome variable, and included school-aged participants with or at risk of having a disability. We identified 22 meta-analyses for inclusion. We coded each meta-analysis for 53 quality indicators (QIs) across eight categories based on recommendations from Talbott et al. (2018). Overall, the meta-analyses met 61% of QIs and results indicated that meta-analyses most frequently met QIs related to providing a clear purpose (95%) and data analysis plan (77%), whereas meta-analyses typically met fewer QIs related to describing participants (39%) and explaining the abstract screening process (48%). We discuss the variation in QI scores within and across the quality categories and provide recommendations for future researchers so that reporting in meta-analyses may be enhanced. Limitations of the current study are that grey literature was not considered for inclusion and that only meta-analyses were included; this limits the generalizability of the results to other research syntheses (e.g., narrative reviews, systematic reviews) and publication types (e.g., dissertations).

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