The paper argues that learning analytics as a research field can benefit from a theory-informed shared language to describe sensemaking of learning and teaching data. To make the case for such shared language, first, I critically review prominent sensemaking theories to then demonstrate how studies in learning analytics do not use coherent…

In a ranking created by using data from multiple data sources, including CareerBuilder, GitHub, Google, Hacker News, the IEEE, Reddit, Stack Overflow, and Twitter, Python was shown to be the top programming language of 2023. Created in 1990, Python has seen a recent uptick in popularity driven primarily by its ability to sustain the use of…

Feedback on how students progress through completing subgoals can improve students' learning and motivation in programming. Detecting subgoal completion is a challenging task, and most learning environments do so either with "expert-authored" models or with "data-driven" models. Both models have advantages that are…

The growth of the data culture has led to calls for improving data literacy among primary and secondary students and their teachers. One approach to improving data literacy is to teach a course devoted to data science but, given the lack of consensus over the term "data science," just what should an introductory data science course…

Online education is an important component of education reform and one of the important learning modes in today's society, which can achieve the goal of learning anytime, anywhere and for everyone. Therefore, this paper constructs an analysis model of online education course emotional perception and course resource integration based on new media…

This paper examines and builds on an earlier contribution to this journal focusing on private supplementary tutoring -- widely known as shadow education -- in Francophone West and Central Africa. Drawing on wider literature about research methods in this domain, it examines the basis for the numerical estimates presented in the original article…

Maternal, neonatal, and child health play crucial roles in achieving the objectives of Sustainable Development Goal (SDG) 2030, particularly in promoting health and wellbeing. However, maternal, neonatal, and child services in Moroccan public hospitals face challenges, particularly concerning mortality rates and inefficient resource allocation,…

Research administrators (RA) at institutions of higher education (IHE) provide critical support to faculty throughout the lifecycle of research, which include developing research, applying to funding opportunities, managing awards through closeout, and maintaining compliance. Fulfilling these tasks requires well-developed RA processes and clear…

Real-time and traditional labor market information (LMI) should inform all facets of the state Career Technical Education (CTE) policymaking process. Subsequently, national LMI was the foundation of the process to update the modernized National Career Clusters® Framework. Intentionality when incorporating elements of LMI into supported CTE…

This article presents methods for using extant data to improve the properties of estimators of the standardized mean difference (SMD) effect size. Because samples recruited into education research studies are often more homogeneous than the populations of policy interest, the variation in educational outcomes can be smaller in these samples than…

Purpose: This study explored how the SchoolWeavers Tool could enhance South Africa's Whole-School Evaluation process and support South African school leaders in creating school learning ecosystems that facilitate learner success, offering a diagnostic assessment tool enabling educational leaders to assess school culture from multiple perspectives.…

This supplement contains additional information for the report, "Support for the Journey Home: An Impact Study of the Returning Citizens Stimulus Program." The Returning Citizens Stimulus (RCS) program was a pilot program for reentry cash support and aimed to help people quickly reach stability in their lives outside of prison and reduce…

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…

This study introduces an optimized ensemble deep neural network (Optimized Ensemble Deep-NN) to enhance the accuracy of predicting student grades. This model solves the problem of different and complicated student performance data by using deep neural networks, ensemble learning, and a number of optimization algorithms, such as Adam, SGD, and RMS…

The University of Arizona Libraries has conducted a pilot implementation of a year-long Digital Scholarship and Data Science Fellowship (DS[superscript 2]F) to address increasing interest in digital and data-intensive scholarship among graduate students. This article provides details regarding the model for the fellowship program; a description of…