The need to make evidence and implications of educational research widely available has prompted a burgeoning interest in knowledge mobilisation, which is a set of strategies supporting the active and intentional dissemination of research knowledge. For this, it is important to consider who might be the intended audience and end-users of this…

The term Latinx has received increasing levels of pushback from different entities outside and within higher education. Despite the term's wide popularity in academic spaces, higher education practitioners often utilize it without understanding whom it simultaneously includes and excludes, and whom the term refers to. Such practice perpetuates the…

Background and Context: Computational thinking (CT) has been increasingly added to K-12 curricula, prompting teachers to grade more and more CT artifacts. This has led to a rise in automated CT assessment tools. Objective: This study examines the scope and characteristics of publications that use machine learning (ML) approaches to assess…

Gamification has gained an increasing attention from researchers and practitioners in various domains including education as it can increase learners' engagement and motivation. However, little is known about how educational gamification experiences can be influenced by learners' characteristics. Therefore, this study provides a systematic…

In the era defined by the fourth paradigm of science research, the burgeoning volume of science data poses a formidable challenge. The established data-related requisites within science literacy now fall short of addressing the evolving needs of researchers and STEM students. Consequently, the emergence of science data literacy becomes imperative.…

Leadership programs for college students have significantly expanded over the past decades. However, there remains a lack of systematic synthesis regarding pedagogical practices employed in these programs. This article aims to fill this research gap by presenting a systematic review of empirical studies examining pedagogies in formal leadership…

This article reports on our experience of collecting language data from informants in video-conferencing settings under a research design originally developed with face-to-face interactions in mind. We had set out to investigate whether individual stylistic features persist in different modes of textual production and designed a complex set of…

In using large language models (LLMs) for education, such as distractors in multiple-choice questions and learning by teaching, error-containing content is used. Prompt tuning and retraining LLMs are possible ways of having LLMs generate error-containing sentences in the learning content. However, there needs to be more discussion on how to tune…

Scale errors are intriguing phenomena in which a child tries to perform an object-specific action on a tiny object. Several viewpoints explaining the developmental mechanisms underlying scale errors exist; however, there is no unified account of how different factors interact and affect scale errors, and the statistical approaches used in the…

The National Youth in Transition Database (NYTD) snapshots offer a glimpse of National and State trends for young people who are receiving Independent Living Services through state child welfare programs. This Outcomes Data Snapshot shows statistical trends about who those young people are, their experiences and outcomes for those both in care and…

The multistage testing (MST) design has been gaining attention and popularity in educational assessments. For testing programs that have small test-taker samples, it is challenging to calibrate new items to replenish the item pool. In the current research, we used the item pools from an operational MST program to illustrate how research studies…

This quantitative study investigates the predictive power of machine learning (ML) models on degree completion among adult learners in higher education, emphasizing the enhancement of data-driven decision-making (DDDM). By analyzing three ML models - Random Forest, Gradient-Boosting machine (GBM), and CART Decision Tree - within a not-for-profit,…

Machine learning (ML) techniques have been successfully applied to a wide array of applications. This dissertation aims to take application data handling into account when developing ML-based solutions for real-world problems through a holistic framework. To demonstrate the generality of our framework, we consider two real-world applications: spam…

In this dissertation, I engage in three analytic cuts to think about/with a relational ontological orientation to data and data literacies/science education. The analysis focuses on the following question: What possibilities for teaching and learning about data are made possible when we attune to the relational, noisy, liminal, and material…

The last decade witnessed a spectacular rise in the volume of available textual data. With this new abundance came the question of how to analyze it. In the social sciences, scholars mostly resorted to two well-established approaches, human annotation on sampled data on the one hand (either performed by the researcher, or outsourced to…