Early Math Interventions in Informal Learning Settings Coding Protocol

The purpose of document is to provide readers with the coding protocol that authors used to code experimental and quasi-experimental early mathematics intervention studies conducted in informal learning environments. The studies were conducted in homes and in museums with caregivers as intervention agents and included children between the ages of 3,0 and 8,11 years. The coding protocol includes more than 200 variables related to basic study information, participant sample size and demographics, methodological information, intervention information, mathematics content information, the control/comparison condition, outcome measures, and results and effect sizes. The coding protocol was developed for the purpose of conducting a meta-analysis; results of the meta-analysis is pending. The data set associated with this coding protocol will be available to the public at the conclusion of the grant (early 2024).

Investigating the Effects of Tablet-Based Math Interventions: A Meta-Analysis

There is debate over the effectiveness of using touch-screen tablet technology on overall student learning gains. This article provides a meta-analysis of studies that used tablets for the delivery of math interventions, programs, or apps to increase student math achievement. A total of 20 group design studies with 2,805 participants were included in the meta-analysis. Overall, tablet-based math interventions provided moderate positive effects for student math gains. Significant moderator variables included participant ethnicity, and socio-economic status, selecting a specific app for use, minutes in intervention, dependent variable, and type of control group. Discussion focuses on the need for more rigorous methodology and reporting of participant and design variables in future studies and the implications for researchers and practitioners when using tablets as a delivery method for math interventions.

A Systematic Review of Student Mediated Math Interventions for Students with Emotional or Behavior Disorders

Students identified with emotional or behavioral disorders (EBD) display deficits across academic content areas, most notably in mathematics. We reviewed research on student-mediated math interventions for students with EBD. A total of 19 studies published between 1968 and 2019 met inclusion criteria, with 24 of 32 cases meeting the What Works Clearinghouse Pilot Single-Case Design Standards (Version 4.0) with or without reservations. Participants included 51 students identified with EBD, ages 8 to 16 years old. Results from visual analysis revealed 0 cases demonstrated strong evidence, 11 cases demonstrated moderate evidence, and 21 cases demonstrated weak evidence of intervention effects. The omnibus Tau-U was 74.35% (CI95 = 64.2% to 84.4%), representing data from 17 studies including 46 students. Implications for research and practice are discussed.

Toward a Causally Informative Fit Index of Longitudinal Models: A Within-Study Design Approach

In structural equation modeling, plausible competing theories can imply similar or equivalent covariance matrices and thus show similar or identical model fit indices, despite making very different causal predictions. We propose a method for selecting among longitudinal models on the basis of causal information. We use a within-study design approach and present an index of causal fit for choosing among models on the basis of their fit with causally informative estimates, in cases in which research designs allow for strong causal estimates. We test for the usefulness and validity of the approach by applying it to data from three randomized controlled trials of early math interventions with longitudinal follow-up assessments. We find that, across datasets, some models consistently outperform other models at forecasting later experimental impacts, traditional fit indices are not strongly related to our index of causal fit, and models show consistent patterns of similarity and discrepancy between statistical fit and causal fit. A simulation study finds that when assumptions are met, the index of causal fit can recover the generating model at rates higher than those of statistical fit indices, and is less redundant with statistical fit indices than they are with each other. Results support the validity of our proposed approach and suggest that it can be useful for choosing among models.

Special Education Math Interventions

The purpose of document is to provide readers with the coding protocol that authors used to code 22 mathematics intervention meta-analyses focused on participants with or at-risk of disabilities. The author drafted this coding protocol based on the meta-analysis quality indicators recommended by Talbott et al. (2018, pp. 248–249); specifically, the author considered the variables presented in Table 1 of Talbott et al. and supplemented the information so that the variables and definitions were specific to the purpose of this systematic review. We coded each meta-analysis for 53 variables across eight categories, including: Quality of Clear Research Questions, Quality of Eligibility Criteria, Quality of Search Procedures, Quality of Screening Criteria, Quality of Coding Procedures, Quality of Research Participants and Contexts, Quality of Data Analysis Plan, and Quality of Reporting Results. The mean interrater reliability across all codes using this protocol was 87.8% (range across categories = 74% –100%).

Brief Experimental Analysis of Math Interventions: A Synthesis of Evidence

Brief experimental analysis (BEA) is a quick method used to identify the function of student learning difficulties and match effective interventions to students’ needs. Extensive work has been done to explore the use of this methodology to determine effective reading interventions; however, a smaller number of published studies have examined the use of BEAs in math. The purpose of the current review was to identify all studies that have used BEA methodology in math. Fifteen studies that included 63 participants and used BEA methodology to identify the most effective math intervention for students were located. Results of the synthesis indicate that the majority of BEAs compared skill and performance interventions on computational fluency; however, the methodology across the included studies varied. Strengths and limitations of the research, in addition to implications for research and practice, are discussed.

A Meta-Analysis Examining the Evidence-Base of Mathematical Interventions for Students With Emotional Disturbances

Math outcomes for students with disabilities, in particular students with emotional disturbance (ED), are bleak, warranting intervention strategies that have research to support their utility. The purpose of this meta-analysis was to examine the literature of math interventions used with students with ED to improve math outcome variables. Our statistical analysis included 17 studies, categorized as addressing fractions, number sense, geometry and measurement, algebra, word problems, and “other.” Although only four of the included studies met all of the CEC-EBP (Council for Exceptional Children’s Standards for Evidence-Based of Practices in Special Education) quality indicators, results of effect size calculations suggest large effects for all interventions. Results of publication bias analyses were mixed. Limitations, directions for future research in this field, and implications for practice are discussed.