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…

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…

Teacher classroom teaching behavior indicators serve as a crucial foundation for guiding instructional evaluation. Existing indicator system suffers from limitations such as strong subjectivity and weak contextual generalization capabilities. Generalized category discovery (GCD) enables automatic data clustering to identify known categories and…

The question of integrating learning content into a serious game is a recurring one, although no clear theoretical framework has yet been provided. It is often argued that integration should occur at the core mechanic level, but this simple statement conceals the complexity of serious game design. The authors therefore propose a theoretical…

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…

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,…

How can governments train thousands of teachers effectively and at scale? This implementation research shares evidence from Sierra Leone's nationwide initiative to train 12,500 Grade 1 teachers and headteachers in structured pedagogy. Drawing on test data from over 7,500 teachers, classroom observations, and feedback from more than 5,600…

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…

Fostering students' scientific literacy is a key goal of science education, with understanding the nature of scientific inquiry (NOSI) as a central component. Achieving this goal requires teachers to possess adequate knowledge in this area. However, assessments indicate that pre-service science teachers (PSTs) have not yet developed comprehensive…

Many large-scale assessments model proficiency with a latent regression on contextual variables. Item-response data are used to estimate the parameters of the latent variable model and are used in conjunction with the contextual data to generate plausible values of individuals' proficiency attributes. These models typically incorporate numerous…

We present an educational unit to teach computational modeling, a vital part of chemical engineering curricula, through the lens of synthetic biology. Lectures, code, and homework questions provide conceptual and practical introductions to each computational method involved in the model development process, along with perspectives on how methods…

Background: Adoption of the Whole School, Whole Community, Whole Child (WSCC) model has been slowed by a lack of available tools to support implementation. The Wellness School Assessment Tool (WellSAT) WSCC is an online assessment tool that allows schools to evaluate the alignment of their policies with the WSCC model. This study assesses the…

Methods of network meta-analysis (NMA) can be classified as arm-based and contrast-based approaches. There are several arm-based approaches, and some of these have been criticized because they recover inter-study information and hence do not obey the principle of concurrent control. Here, we point out that recovery of inter-study information in…