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…

Evidence-based programs and grassroots programs are often adapted during implementation. Adaptations are often hidden, ignored, or punished. Although some adaptations stem from lack of organizational capacity, evaluators report other adaptations happen in good faith or are efforts to better fit the local context. Program implementers, facilitators…

When reevaluating the educational landscape and aiming to incorporate movement into the day, remember that all exercise is not created equal. We recommend creating a model to evaluate the level of student exercise within an organization. The four-level framework discussed in this column can be used to evaluate exercise and sedentariness within an…

We review common situations in Bayesian latent variable models where the prior distribution that a researcher specifies differs from the prior distribution used during estimation. These situations can arise from the positive definite requirement on correlation matrices, from sign indeterminacy of factor loadings, and from order constraints on…

This article is about making correction in Tarray, Singh, and Zaizai model and further improving it when stratified random sampling is necessary. This is done by using optional randomized response technique in stratified sampling using a combination of Mangat and Singh, Mangat, and Greenberg et al. models. The suggested model has been studied…

Confirmatory factor analyses (CFA) are often used in psychological research when developing measurement models for psychological constructs. Evaluating CFA model fit can be quite challenging, as tests for exact model fit may focus on negligible deviances, while fit indices cannot be interpreted absolutely without specifying thresholds or cutoffs.…

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…

With the budding interests of structural and functional network characteristics as potential parameters for abnormal brains, an essential and thus simpler representation and evaluations have become necessary. Eigenvector centrality measure of functional magnetic resonance imaging ("fMRI") offer region wise network representations through…

Despite the increasing adaption of automated text analysis in communication studies, its strengths and weaknesses in framing analysis are so far unknown. Fewer efforts have been made to automatic detection of networked frames. Drawing on the recent developments in this field, we harness a comparative exploration, using Latent Dirichlet Allocation…

Educational research outcomes frequently rely on an assumption that measurement metrics have interval-level properties. While most investigators know enough to be suspicious of interval-level claims, and in some cases even question their findings given such doubts, there is a lack of understanding regarding the measurement conditions that create…

Given the rapid adoption of machine learning methods by education researchers, and the growing acknowledgment of their inherent risks, there is an urgent need for tailored methodological guidance on how to improve and evaluate the validity of inferences drawn from these methods. Drawing on an integrative literature review and extending a…

Agent-based models (ABMs) often rely on psychometric constructs such as 'opinions', 'stubbornness', 'happiness', etc. The measurement process for these constructs is quite different from the one used in physics as there is no standardized unit of measurement for opinion or happiness. Consequently, measurements are usually affected by 'psychometric…

This article aims to clarify fundamental aspects of the process of assigning fuzzy scores to conditions based on family resemblance (FR) structures by considering prototype and set theories. Prototype theory and set theory consider FR structures from two different angles. Specifically, set theory links the conceptualization of FR to the idea of…

Multicriteria decision-making (MCDM) techniques have been widely adopted to evaluate the effectiveness of e-learning. However, the literature review has not kept pace with the rapid accumulation of knowledge in this field. This study systematically reviews the MCDM techniques applied in e-learning issues. In total, we reviewed 77 published studies…

Knowledge Tracing (KT) is a task to model students' knowledge based on their coursework interactions within an Intelligent Tutoring System (ITS). Recently, Deep Neural Networks (DNN) showed superb performance over classical methods on multiple dataset benchmarks. While most Deep Learning based Knowledge Tracing (DLKT) models are optimized for…