In recent years, educators, administrators, policymakers, and measurement experts have called for assessments that support educators in making better instructional decisions. One promising approach to measurement to support instructional decision-making is diagnostic classification models (DCMs). DCMs are flexible psychometric models that…

In this study, the accuracy of the artificial neural network (ANN) was assessed considering the uncertainties associated with the randomness of the data and the lack of learning. The Monte-Carlo algorithm was applied to simulate the randomness of the input variables and evaluate the output distribution. It has been shown that under certain…

Rigor evaluation in mixed methods research is a growing need. Linking rigor to Hong and Pluye's (2019) concepts of methodological and reporting quality, the purpose of this article is to operationalize and expand Harrison et al.'s (2020) Rigorous Mixed Methods Framework. Drawing from a systematic methodological review of 66 inclusive education…

Assessment is usually considered as an afterthought in the instructional design process. Given the many challenges of assessment design--and the lack of ready solutions--teachers may fall back on familiar forms of assessments and hope for the best. As a result, the problem is not a lack of will on the part of teachers. Instead, it is the lack of…

Predicting learner performance with precision is critical within educational systems, offering a basis for tailored interventions and instruction. The advent of big data analytics presents an opportunity to employ Machine Learning (ML) techniques to this end. Real-world data availability is often hampered by privacy concerns, prompting a shift…

This paper aims to characterize critical events noticed by novice mathematics teacher-educators (NMTEs) while they facilitate teacher education sessions. Twenty-four NMTEs enrolled in a university course on teaching teachers were asked to facilitate a series of three sessions with preservice teachers, identify critical events from those sessions…

Enzymes are nature's catalysts, mediating chemical processes in living systems. The study of enzyme function and mechanism includes defining the maximum catalytic rate and affinity for substrate/s (among other factors), referred to as enzyme kinetics. Enzyme kinetics is a staple of biochemistry curricula and other disciplines, from molecular and…

Generalized structured component analysis (GSCA) is a multivariate method for specifying and examining interrelationships between observed variables and components. Despite its data-analytic flexibility honed over the decade, GSCA always defines every component as a linear function of observed variables, which can be less optimal when observed…

This research investigates the linkage between training evaluation, learning design and training transfer. A new training evaluation model, (i.e., learning-transfer evaluation model [LTEM]), was used to examine its ability to provide evaluative evidence through robust assessments in pre-, post- and delayed assessments. The model was used to…

Factor analysis is often used to model scales created to measure latent constructs, and internal structure validity evidence is commonly assessed with indices like SRMR, RMSEA, and CFI. These indices are essentially effect size measures and definitive benchmarks regarding which values connote reasonable fit have been elusive. Simulations from the…

There are many important and interesting academic competitions that attract an increasing number of students. However, traditional student team building methods usually have strong randomness or involve only some first-class students. To choose more suitable students to compose a team and improve students' abilities overall, a competition-oriented…

The purpose of this study was to evaluate the degree of classification quality in the basic latent class model when covariates are either included or are not included in the model. To accomplish this task, Monte Carlo simulations were conducted in which the results of models with and without a covariate were compared. Based on these simulations,…

Purpose: This study aims to describe the fundamentals of teaching risk management in a classroom setting, with an emphasis on the learning interface between higher education and the workplace environment for business management students. Design/methodology/approach: The study reviews literature that uses spreadsheets to visualize and model risk…

Teaching leadership in today's world requires a combination of introducing theory and best practices, as well as allowing moments that are happening in real-time, both current events and interactions from the "laboratory" of the classroom, to affect the teaching agenda. Instructors can lean into the model of Intentional Emergence (IE) to…

Abstract This study proposes a new Bayesian differential item functioning (DIF) detection method using posterior predictive model checking (PPMC). Item fit measures including infit, outfit, observed score distribution (OSD), and Q1 were considered as discrepancy statistics for the PPMC DIF methods. The performance of the PPMC DIF method was…