A Meta-Analysis of Single-Case Research on Word-Problem Instruction for Students With Learning Disabilities

Shin, Mikyung; Bryant, Diane Pedrotty; Powell, Sarah R.; Pyung-gang, Jung; Ok, Min Wook; Hou, Fangjuan

doi:10.1177/0741932520964918

Cited by 17 publications

(15 citation statements)

References 61 publications

(169 reference statements)

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“…Because these two mathematics topics have consistently been a building block for successful mathematics in elementary and secondary mathematics (National Center for Education Statistics, 2019 ), it is assumed that researchers have been trying to investigate how to tackle these mathematical difficulties. Furthermore, since the release of the National Mathematics Advisory Panel’s report ( 2008 ) on highlighting the importance of teaching fractions as being a critical foundation of algebra and emphasizing students’ conceptual knowledge for understanding and solving mathematical word problems across topics, there have been an increasing number of intervention and review studies (Ennis & Losinki, 2019 ; Morano et al, 2020 ; Shin et al, 2021a ).…”

Section: Discussionmentioning

confidence: 99%

A content analysis of research on technology use for teaching mathematics to students with disabilities: word networks and topic modeling

Shin

Choo

et al. 2023

IJ STEM Ed

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The purpose of this study was to conduct a content analysis of research on technology use for teaching mathematics to students with disabilities. We applied word networks and structural topic modeling of 488 studies published from 1980 to 2021. Results showed that the words “computer” and “computer-assisted instruction” had the highest degree of centrality in the 1980s and 1990s, and “learning disability” was another central word in the 2000s and 2010s. The associated word probability for 15 topics also represented technology use within different instructional practices, tools, and students with either high- or low-incidence disabilities. A piecewise linear regression with knots in 1990, 2000, and 2010 demonstrated decreasing trends for the topics of computer-assisted instruction, software, mathematics achievement, calculators, and testing. Despite some fluctuations in the prevalence in the 1980s, the support for visual materials, learning disabilities, robotics, self-monitoring tools, and word problem-solving instruction topics showed increasing trends, particularly after 1990. Some research topics, including apps and auditory support, have gradually increased in topic proportions since 1980. Topics including fraction instruction, visual-based technology, and instructional sequence have shown increasing prevalence since 2010; this increase was statistically significant for the instructional sequence topic over the past decade.

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Section: Discussionmentioning

confidence: 99%

A content analysis of research on technology use for teaching mathematics to students with disabilities: word networks and topic modeling

Shin

Choo

et al. 2023

IJ STEM Ed

Self Cite

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show abstract

“…Methods used to detect asymmetry and publication bias are routinely employed in meta-analyses of group-design research. Although used less often in behavior analysis research compared to other fields, these methods are used in metaanalyses of behavioral research (see e.g., Amlung et al, 2016;McCormack et al, 2019) and meta-analyses of SCED studies (see e.g., Babb et al, 2020;Bowman-Perrot et al, 2014;Garwood et al, 2021;Shin et al, 2020). When attempting to aggregate behavior science research using frequentist statistical analysis, heterogeneity should be accounted for in the model minimally at the participant level (level 1) and the study level (level 2), referred to as a multilevellevel model meta-analysis (Becraft et al, 2020;Moeyaert et al, 2020).…”

Section: Meta-analytic Publication Bias Methods and Behavior Sciencementioning

confidence: 99%

Meta-Analytic Methods to Detect Publication Bias in Behavior Science Research

et al. 2021

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Publication bias is an issue of great concern across a range of scientific fields. Although less documented in the behavior science fields, there is a need to explore viable methods for evaluating publication bias, in particular for studies based on single-case experimental design logic. Although publication bias is often detected by examining differences between meta-analytic effect sizes for published and grey studies, difficulties identifying the extent of grey studies within a particular research corpus present several challenges. We describe in this article several meta-analytic techniques for examining publication bias when published and grey literature are available as well as alternative meta-analytic techniques when grey literature is inaccessible. Although the majority of these methods have primarily been applied to meta-analyses of group design studies, our aim is to provide preliminary guidance for behavior scientists who might use or adapt these techniques for evaluating publication bias. We provide sample data sets and R scripts to follow along with the statistical analysis in hope that an increased understanding of publication bias and respective techniques will help researchers understand the extent to which it is a problem in behavior science research.Keywords publication bias . meta-analysis . single-case experimental design . behavior science . research-synthesis . evidence-based behavior analysis In behavior science utopia, all published studies show that a chosen independent variable has an unambiguous and strong functional relation with the chosen dependent variable. Whether one chooses a visual or quantitative analysis of their pristine data, the

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“…Ledford and Gast (2018) suggested that moderator analysis logic in SCED research could help uncover the boundaries of treatment. For example, Shin et al (2020) conducted a meta-analysis to evaluate the effects of word problem solving interventions for students with a learning disability that used single-case research design. The authors used meta-regression to investigate multiple variables of interest (i.e., study quality, content domain of word problems, mathematical practice standards embedded in intervention) and identified whether effects varied.…”

Section: Benefits Of Meta-analyses In Appliedmentioning

confidence: 99%

Meta‐analyses and effect sizes in applied behavior analysis: A review and discussion

Dowdy¹,

Peltier

Tincani³

et al. 2021

J of App Behav Analysis

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For more than four decades, researchers have used meta-analyses to synthesize data from multiple experimental studies often to draw conclusions that are not supported by individual studies. More recently, single-case experimental design (SCED) researchers have adopted meta-analysis techniques to answer research questions with data gleaned from SCED experiments. Metaanalyses enable researchers to answer questions regarding intervention efficacy, generality, and condition boundaries. Here we discuss meta-analysis techniques, the rationale for their adaptation with SCED studies, and current indices used to quantify the effect of SCED data in applied behavior analysis.

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A Meta-Analysis of Single-Case Research on Word-Problem Instruction for Students With Learning Disabilities

Cited by 17 publications

References 61 publications

A content analysis of research on technology use for teaching mathematics to students with disabilities: word networks and topic modeling

A content analysis of research on technology use for teaching mathematics to students with disabilities: word networks and topic modeling

Meta-Analytic Methods to Detect Publication Bias in Behavior Science Research

Meta‐analyses and effect sizes in applied behavior analysis: A review and discussion

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