At the school level statistics begins with exploratory data analysis, or EDA. Statistical learning goes on to include statistical inference, which will be discussed in the second part of this article. In this article, the author will talk about EDA and CODAP. EDA can be thought of as looking for patterns in data using graphs and simple statistics…

This article introduces the evolution of themes and ideas related to the history, theory, and practice of learning analytics within the learning, design, and technology field through four eras. This review provides researchers with a fundamental understanding of the origin of learning analytics from a historical perspective and distinguishes…

Conceptualizing and understanding global, physical systems like Earth's ocean is challenging. Data visualizations on touch-based technology allow learners to explore systems and facilitate embodied experiences, promoting deeper understanding. We investigated how direct manipulation of data visualizations on a touchscreen table affords meaningful…

Schools, teaching, and learning environments have long been understood and idealised as places of care. Within feminist studies and Science and Technology Studies (STS), scholars have proposed a shift to include non-humans in what we propose to conceive as care arrangements. Drawing on Tronto's feminist ethics of care [1993. "Moral…

Students now have readily available and powerful tools to access, manipulate, combine, and visualize data. Acquiring data and visual literacy requires more than knowledge of how to use these tools. Students need to engage with assignments that challenge them to make relatively complex visualizations, interpret them, and explain why these…

Curriculum Analytics (CA) emerged as a sub-field of Learning Analytics, aiming to use large amounts of educational data to drive curriculum decision-making and program improvement. However, it is still an open question how the use of CA tools impacts student learning and program quality. To advance this field, this paper describes the lessons…

There is increasing attention on study abroad programmes in higher education. However, there is little evidence on how participation might impact students' academic performance on return. Using administrative data from Ireland and a range of regression models and matching estimators, we find no independent association between study abroad and…

With the availability of educational digital data acquisition systems, it has also become possible in physics education to generate 'big' data sets by (a) measuring multiple variables simultaneously, (b) increasing the sample rate, (c) extending the measurement duration, or (d) choosing a combination among these three options. In the context of…

Recognizing learners' engagement during learning processes is important for providing personalized pedagogical support and preventing dropouts. As learning processes shift from traditional offline classrooms to distance learning, methods for automatically identifying engagement levels should be developed. This article aims to present a literature…

Many higher education institutions have responded to the significant shortage of professionals with strong analytical expertise by offering graduate programs in business analytics and data science. These programs are typically designed to be practitioner focused and many of them offer a Capstone course that gives students the opportunity to…

This article conceptualizes the notion of magic(al)ing in relation to post-pandemic ways of thinking about data production and analyses. Revisiting old data produced pre-COVID-19 and engaging with new data produced during COVID-19, we consider the possibilities and potential of magic(al)ing as a theoretical concept. We think with several ideas…

This study compared three approaches for handling a fourth level of nesting when analyzing cluster-randomized trial (CRT) data. Although CRT data analyses may include repeated measures, individual, and cluster levels, there may be an additional fourth level that is typically ignored. This study examined the impact of ignoring this fourth level,…

Item Response Theory (IRT) models are a popular analytic method for self report data. We show how traditional IRT models can be vulnerable to specific kinds of asymmetric measurement error (AME) in self-report data, because the models spread the error to all estimates -- even those of items that do not contribute error. We quantify the impact of…

Higher education institutions in the United States are under intense scrutiny to engage in data-driven decision-making to address systemic deficiencies. An innovative strategy to increase the use of data in higher education is through interactive data visualization whereby users are more involved in the creation of knowledge. The problem that was…

This case study reflects upon a mixed-methods exploratory study utilized by the Leadership in Times of Crisis Framework within the paradigm of pragmatism to survey 976 Minnesota teachers in April of 2020 to determine the demographic profile of teachers in Minnesota who were facing the COVID-19 pandemic and the greatest challenges in their…