Factor analysis is widely utilized to identify latent factors underlying the observed variables. This paper presents a comprehensive comparative study of two widely used methods for determining the optimal number of factors in factor analysis, the K1 rule, and parallel analysis, along with a more recently developed method, the bass-ackward method.…

To meet accreditation expectations, teacher preparation programs must demonstrate their candidates are evaluated using summative assessment tools that yield sound, reliable, and valid data. These tools are primarily used by the clinical experience team -- university supervisors and mentor teachers. Institutional beliefs regarding best practices…

This paper proposes an online learning platform learner DM method based on the improved fuzzy C clustering (FCM) algorithm, constructs a learner feature database, and combines clustering analysis and SPSS statistical methods to statistically summarize the big data of law, thus improving the deficiencies of static and absolute classification of…

Most methods for structural equation modeling (SEM) focused on the analysis of covariance matrices. However, "Historically, interesting psychological theories have been phrased in terms of correlation coefficients." This might be because data in social and behavioral sciences typically do not have predefined metrics. While proper methods…

Parallel analysis has been considered one of the most accurate methods for determining the number of factors in factor analysis. One major advantage of parallel analysis over traditional factor retention methods (e.g., Kaiser's rule) is that it addresses the sampling variability of eigenvalues obtained from the identity matrix, representing the…

In recent years, the growing incidence of blended and online learning has highlighted instructional design concerns, especially STEM instructional design. Existing studies have often adopted observations, questionnaires, or interviews to evaluate STEM instructional design plans. However, there is still a lack of quantitative, measurable, and…

Qualitative thematic analysis is a commonly used and widely applicable form of qualitative analysis, though it can be challenging to implement. Due to its use across research questions, qualitative traditions, and fields, thematic analysis is also prevalent in mixed methods studies. Despite its widespread use, the term "thematic…

Discrete-time survival analysis (DTSA) models are a popular way of modeling events in the social sciences. However, the analysis of discrete-time survival data is challenged by missing data in one or more covariates. Negative consequences of missing covariate data include efficiency losses and possible bias. A popular approach to circumventing…

Purpose: As new technologies such as immersive and augmented platforms emerge, training approaches are also transforming. The virtual reality (VR) platform provides a completely immersive learning experience for simulated training. Despite increased prevalence of these technologies, the extent literature is lagging behind in terms of evaluating…

Conditional process models, including moderated mediation models and mediated moderation models, are widely used in behavioral science research. However, few studies have examined approaches to conduct statistical power analysis for such models and there is also a lack of software packages that provide such power analysis functionalities. In this…

In a 1984 essay, Benjamin Bloom, an educational psychologist at the University of Chicago, asserted that tutoring offered "the best learning conditions we can devise" and that tutors could raise student achievement by two full standard deviations--or, in statistical parlance, two "sigmas." The influence of Bloom's two-sigma…

Economic efficiency demands accurate assessment of individual ability for selection purposes. This study investigates Classical Test Theory (CTT) and Item Response Theory (IRT) for estimating true ability and ranking individuals. Two Monte Carlo simulations and real data analyses were conducted. Results suggest a slight advantage for IRT, but…

Multisite cluster randomized trials (MCRTs), in which, the intermediate-level clusters (e.g., classrooms) are randomly assigned to the treatment or control condition within each site (e.g., school), are among the most commonly used experimental designs across a broad range of disciplines. MCRTs often align with the theory that programs are…

Comparative interrupted time series (CITS) designs evaluate impact by modeling the relative deviation from trends among a treatment and comparison group after an intervention. The broad applicability of the design means it is widely used in education research. Like all non-experimental evaluation methods however, the internal validity of a given…

Several marginal effect size (ES) statistics suitable for quantifying the magnitude of differential item functioning (DIF) have been proposed in the area of item response theory; for instance, the Differential Functioning of Items and Tests (DFIT) statistics, signed and unsigned item difference in the sample statistics (SIDS, UIDS, NSIDS, and…