Research in education and behavioral sciences often involves the use of latent variable models that are related to indicators, as well as related to covariates or outcomes. Such models are subject to interpretational confounding, which occurs when fitting the model with covariates or outcomes alters the results for the measurement model. This has…

Research on computing in higher education research has been dominated by studies on "things that work" (or not). While useful, the field now needs more research on authentic tech-related problems of practice and viable solutions that resolve them. This article describes one such approach: Educational Design Research (EDR). It begins with…

A linear model is often used to find the effect of a binary treatment D on a noncontinuous outcome Y with covariates X. Particularly, a binary Y gives the popular "linear probability model (LPM)," but the linear model is untenable if X contains a continuous regressor. This raises the question: what kind of treatment effect does the…

In this study, which focuses on selecting the material and predicting its mechanical behaviors in materials science, an Artificial Neural Network (ANN) was used to predict and simulate the low-speed impact effects of hybrid nano-doped aramid composites. There are not enough studies about open education practices in this field. Since error values…

Generative artificial intelligence (AI) is increasingly presented as a potential substitute for humans, including as research subjects. However, there is no scientific consensus on how closely these in silico clones can emulate survey respondents. While some defend the use of these "synthetic users," others point toward social biases in…

This paper proposes a conceptual framework enabling the development and adoption of descriptive, diagnostic, predictive and recommendatory data analytics in teacher professional learning by harnessing some of the affordances of digital technologies to convert data into actionable insights. The paper argues for a technology-enhanced approach that…

Being able to notice that a cause-effect relation is getting stronger or weaker is important for adapting to one's environment and deciding how to use the cause in the future. We conducted an experiment in which participants learned about a cause-effect relation that either got stronger or weaker over time. The experiment was conducted with a…

This article links the connection between music and leadership, exploring ways to connect musical icons to teaching leadership theory and concepts. The authors utilize the relationship leadership model (RLM) and the leadership identity development (LID) model through case studies of Beyoncé Knowles-Carter and Taylor Swift. We provide questions to…

Learning is a multimodal process, and learning analytics (LA) researchers can readily access rich learning process data from multiple modalities, including audio-video recordings or transcripts of in-person interactions; logfiles and messages from online activities; and biometric measurements such as eye-tracking, movement, and galvanic skin…

We adapt the Lanchester combat model to represent conflict between vampires and humans. It is assumed that vampires attack humans during the hours of darkness whilst humans attack vampires during the hours of light. The right-hand side of the differential equation model therefore depends upon the hour of the day. A key insight is that to answer…

Understanding software modelers' difficulties and evaluating their performance is crucial to Model-Driven Engineering (MDE) education. The software modeling process contains fine-grained information about the modelers' analysis and thought processes. However, existing research primarily focuses on identifying obvious issues in the software…

Partially automated assessment is implemented via the 'Printable worksheet' mode in the Numbas e-assessment system to create a mathematical modelling worksheet which is individualised with random parameters but completed and marked as if it were a non-automated piece of coursework, preserving validity while reducing the risk of academic misconduct…

This paper presents a systematic literature review of using Machine Learning (ML) techniques in higher education career recommendation. Despite the growing interest in leveraging Artificial Intelligence (AI) for personalized academic guidance, no previous reviews have synthesized the diverse methodologies in this field. Following the Kitchenham…

The purpose of this paper is to propose a framework to guide the study of classroom factors that promote student functioning and development within classroom settings. First, we describe a new framework, "Classroom Carrying Capacity," to categorize factors in the classroom as limiting or resource factors across four domains: external,…

We propose a novel approach for modeling judgment accuracy that, for the first time, allows for simultaneously considering the rank, level, and differentiation component, the predominantly applied operationalization of teacher judgment accuracy. These components are conceptualized as latent, unobserved individual abilities. The model is introduced…