The cognitive purpose of the research presented in the article is to identify the propensity for pro-social and altruistic behavior among first-year military students (of basic training) in three simulated situations of need for help to other people. It raised the question contained in the main research problem: to what extent do military students…

We conducted a study of predictive analytics (PA) applied to state data on post-school outcomes (PSO) of exited high-school students with disabilities (SWD). Data analyses with machine learning Random Forest algorithm and multilevel Bayesian ordered logistic regression produced two key findings. One, Random Forest models were accurate in…

Meta-analyses of clinical trials targeting rare events face particular challenges when the data lack adequate numbers of events for all treatment arms. Especially when the number of studies is low, standard random-effects meta-analysis methods can lead to serious distortions because of such data sparsity. To overcome this, we suggest the use of…

This study explores the epistemic considerations that seemed to govern thirty-one Indian teachers' beliefs while teaching certain concepts of probability, especially using random generators. It focuses on knowing how these teachers make transitions between the different interpretations of probability, namely, Logical (sometimes also known as…

Meta-analyses of treatment effects in randomized control trials are often faced with the problem of missing information required to calculate effect sizes and their sampling variances. Particularly, correlations between pre- and posttest scores are frequently not available. As an ad-hoc solution, researchers impute a constant value for the missing…

Purpose: To compare the effectiveness of blocked and random practice schedules of balance training in dynamic balance abilities of older adults using Wii Fit balance game tasks. Method: Forty-one participants who were not receiving hospice care or living in a nursing home participated. Three Wii Fit balance tasks (tasks A, B, and C) were selected…

The part of responses that is absent in the nonequivalent groups with anchor test (NEAT) design can be managed to a planned missing scenario. In the context of small sample sizes, we present a machine learning (ML)-based imputation technique called chaining random forests (CRF) to perform equating tasks within the NEAT design. Specifically, seven…

Prompting students to generate constructed responses as they read provides a window into the processes and strategies that they use to make sense of complex text. In this study, Markov models examined the extent to which: (1) patterns of strategies; and (2) strategy combinations could be used to inform computational models of students' text…

Conventional random-effects models in meta-analysis rely on large sample approximations instead of exact small sample results. While random-effects methods produce efficient estimates and confidence intervals for the summary effect have correct coverage when the number of studies is sufficiently large, we demonstrate that conventional methods…

Single-case comparative studies could help identify efficient instructional procedures for individuals with disabilities. However, previous literature reported inconsistent efficiency results if multiple comparisons were conducted, indicating that within-participant replication was uncommon. In this review, we examined single-case comparative…

In this exercise, participants create a fictional business based on a set of randomly generated words. This challenge requires participants to exercise creativity, while reinforcing the business concepts learned in class. The exercise has four steps: (1) generating a prompt of three random words, (2) designing a fictional business based on this…

Experimental studies of educational interventions are rarely based on representative samples of the target population. This simulation study tests two formal sampling strategies for selecting districts and schools from within strata when they may not agree to participate if selected: (1) balanced selection of the most typical district or school…

Imputation or likelihood-based approaches to handle missing data assume the data are missing completely at random (MCAR) or missing at random (MAR). However, little research has examined the missingness pattern before using these imputation/likelihood methods. Three missingness mechanisms -- MCAR, MAR, and not missing at random (NMAR) -- can be…

Based on the framework of testlet models, the current study suggests the Bayesian random block item response theory (BRB IRT) model to fit forced-choice formats where an item block is composed of three or more items. To account for local dependence among items within a block, the BRB IRT model incorporated a random block effect into the response…

When selecting a multilevel model to fit to a dataset, it is important to choose both a model that best matches characteristics of the data's structure, but also to include the appropriate fixed and random effects parameters. For example, when researchers analyze clustered data (e.g., students nested within schools), the multilevel model can be…