The consequence of a change in school leadership (e.g., principal turnover) on student achievement has important implications for education policy. The impact of such an event can be estimated via the popular Difference in Difference (DiD) estimator, where those schools with a turnover event are compared to a selected set of schools that did not…

Algorithmic bias is a pressing concern in educational data mining (EDM), as it risks amplifying inequities in learning outcomes. The Area Between ROC Curves (ABROCA) metric is frequently used to measure discrepancies in model performance across demographic groups to quantify overall model fairness. However, its skewed distribution--especially when…

The term "rigor" in education often evokes resistance due to its inconsistent definitions and widespread misconceptions. This study introduces and validates the RIGOR Walk framework, a research- and practitioner-informed tool designed to define, observe, and enhance rigorous learning environments across classrooms. The framework is…

Notwithstanding the neuromyth controversy, the malleability of learning style preferences impacts the validity of the measurement instrument and the effectiveness of the associated model of learning. This study investigates the test-retest reliability and underlying dynamics of Kolb's Learning Style Inventory (KLSI). It surveys 245 college-level…

A slowdown or a speedup in response times across experimental conditions can be taken as evidence of online deployment of knowledge. However, response-time difference measures are rarely evaluated on their reliability, and there is no standard practice to estimate it. In this article, we used three open data sets to explore an approach to…

Numerous methods exist to determine the optimal number of classes when using latent profile analysis (LPA), but none are consistently correct. Recently, the likelihood incremental percentage per parameter (LI3P) was proposed as a model effect-size measure. To evaluate the LI3P more thoroughly, we simulated 50,000 datasets, manipulating factors…

Background: For decades, education researchers have relied on the work of Campbell, Cook, and Shadish to help guide their thinking about valid impact estimates in the social sciences (Campbell & Stanley, 1963; Shadish et al., 2002). The foundation of this work is the "validity typology" and its associated "threats to…

Within the frequentist structural equation modeling (SEM) framework, adjudicating model quality through measures of fit has been an active area of methodological research. Complicating this conversation is research revealing that a higher quality measurement portion of a SEM can result in poorer estimates of overall model fit than lower quality…

Online and distance learning technology with the learning management system (LMS) is an example of the application of online learning models at universities, which is the impact of technological developments. However, advances in LMS technology still need to be implemented in universities, the problem of university readiness being the main factor.…

Simulation is a powerful approach that plays a significant role in science and technology. Computational models that simulate learner interactions and data hold great promise for educational technology as well. Amongst others, simulated learners can be used for teacher training, for generating and evaluating hypotheses on human learning, for…

This paper details how to effectively share three-dimensional geological models using data conversion between two mainstream mining software, Micromine and Surpac. It also discusses the impact of this conversion method on geological integrated exploration decision-making guidance. The current situation primarily manifests in the fact that both…

In the context of virtual learning communities (VLCs), where the participants may not know each other, it is necessary to have a mechanism to help when deciding who to work with and what reliable contents and information sources are. This study aims to design a generic trust model, named T-VLC, applicable to VLCs, which can be adapted to different…

Value added models (VAMs) attempt to estimate the causal effects of teachers and schools on student test scores. We apply Generalizability Theory to show how estimated VA effects depend upon the selection of test items. Standard VAMs estimate causal effects on the items that are included on the test. Generalizability demands consideration of how…

While large language models (LLMs) continue to grow in scale and gain new zero-shot capabilities, their performance for languages beyond English increasingly lags behind. This gap is due to the "curse of multilinguality," where multilingual language models perform worse on individual languages than a monolingual model trained on that…

Background: Peer assessment has played an important role in large-scale online learning, as it helps promote the effectiveness of learners' online learning. However, with the emergence of numerical grades and textual feedback generated by peers, it is necessary to detect the reliability of the large amount of peer assessment data, and then develop…