Few data-driven approaches are available to estimate the risk of conclusion change in systematic review updates. We developed a rule-based approach to automatically extract information from reviews and updates to be used as features for modelling conclusion change risk. Rules were developed to extract relevant information from published Cochrane…

Classification and Regression Tree (CART) analysis is a statistical modeling approach that uses quantitative data to predict future outcomes by generating decision trees. CART analysis can be useful for educators to inform their decision-making. For example, educators can use a decision tree from a CART analysis to identify students who are most…

Statistical analysis of categorical data often relies on multiway contingency tables; yet, as the number of categories and/or variables increases, the number of table cells with few (or zero) observations also increases. Unfortunately, sparse contingency tables invalidate the use of standard goodness-of-fit statistics. Limited-information fit…

Multiple imputation (MI) is a popular method for handling missing data. In education research, it can be challenging to use MI because the data often have a clustered structure that need to be accommodated during MI. Although much research has considered applications of MI in hierarchical data, little is known about its use in cross-classified…

In this study, we report on a Systematic Mapping Study (SMS) for the application of technology acceptance models to Moodle under the prism of latent variable modeling. Based on an automatic search including primary studies from journals, conferences, and book chapters during 2001 to 2019, 41 primary were selected. We aim to contribute to a better…

Cluster randomized control trials often incorporate a longitudinal component where, for example, students are followed over time and student outcomes are measured repeatedly. Besides examining how intervention effects induce changes in outcomes, researchers are sometimes also interested in exploring whether intervention effects on outcomes are…

In the past two decades, the interdisciplinary push to denaturalise the concept of society has historicised the very object of social history. In this paper, I propose a way of studying the social history of education that eludes the presupposition of the social as a transcendental or pre-discursive object. My central claim is that it is possible…

The present study illustrates how select data can be organized to guide researchers to HSIs proficient at graduating Hispanics with STEM bachelor's degrees to investigate best practices that less proficient HSIs can adopt for program improvement. The Integrated Postsecondary Education Data System (IPEDS) from the National Center for Education…

This quantitative study investigated the relationship between teacher self-efficacy, maximizing decision-making tendencies, and utilization of educational technology resources. The study utilized the Teacher Sense of Self-Efficacy Scale (TSES), the Maximizing Tendency Scale (MTS-7), and teacher use of educational technology surveys to determine if…

Quality assessment systems have recently expanded, serving as indicators for the assessment and ranking of higher education institutions worldwide. The growing development of new educational methodologies, like Blended Learning, requires the design and validation of tools that allow for their assessment. The objective of this article is to…

Cluster randomized trials (CRTs) are commonly used to evaluate educational interventions, particularly their effectiveness. Recently there has been greater emphasis on using these trials to explore cost-effectiveness. However, methods for establishing the power of cluster randomized cost-effectiveness trials (CRCETs) are limited. This study…

The last series of Raven's standard progressive matrices (SPM-LS) test was studied with respect to its psychometric properties in a series of recent papers. In this paper, the SPM-LS dataset is analyzed with regularized latent class models (RLCMs). For dichotomous item response data, an alternative estimation approach based on fused regularization…

In this meta-study, we analyzed 2442 effect sizes from 131 meta-analyses in intelligence research, published from 1984 to 2014, to estimate the average effect size, median power, and evidence for bias. We found that the average effect size in intelligence research was a Pearson's correlation of 0.26, and the median sample size was 60. Furthermore,…

Meta-studies are often conducted on empirical findings obtained from overlapping samples. Sample overlap is common in research fields that strongly rely on aggregated observational data (eg, economics and finance), where the same set of data may be used in several studies. More generally, sample overlap tends to occur whenever multiple estimates…

We present the R package and web app "statcheck" to automatically detect statistical reporting inconsistencies in primary studies and meta-analyses. Previous research has shown a high prevalence of reported p-values that are inconsistent--meaning a re-calculated p-value, based on the reported test statistic and degrees of freedom, does…