This report characterizes forms of dialogic support that a sixth-grade teacher generated during whole-class and small-group conversations to help students develop a practice of statistical modeling. During four weeks of instruction, students constructed and revised models to account for variability and uncertainty across a variety of random…

This study focuses on the construction of the learner-centered teaching college English teaching mode under big data technology. Traditional college English teaching has issues, such as standardized teaching ignoring individual differences and lagging feedback. However, the development of big data technology offers opportunities for teaching…

College English teaching should give full play to the important role of network resources, implement the student-centered network autonomous learning model, and give full play to learners' autonomous learning potential. At present, although some universities have tried this new model, its application in college English lacks practical research.…

Data science is a highly interdisciplinary field that comprises various principles, methodologies, and guidelines for the analysis of data. The creation of appropriate curricula that use computational tools and teaching activities is necessary for building skills and knowledge in data science. However, much of the literature about data science…

Evidence-based and student-centered instructional methods hold the promise of transforming undergraduate STEM education and simultaneously solving the dual challenge of STEM workforce needs and inequities within STEM. The Learning Assistant (LA) Model was created to reform curriculum, recruit teachers, and inform discipline-based education…

This study explores learner engagement with Advanced Computational Thinking (ACT) in the New Zealand digital curriculum. "Advanced" in ACT refers to an expansive, transdisciplinary, and future-looking understanding of computational thinking (CT). ACT promotes CT beyond narrow modes of problem-solving (abstraction, algorithmic thinking,…

The poor level of engagement in learning mathematics is primarily caused by ineffective methods of instruction. Therefore, the purpose of this study was to investigate how context-based problem-posing and solving instructional approaches influence students' engagement in learning data handling using a concurrent embedded quasi-experimental…

The increasing prevalence of learner-centred forms of learning as well as an increase in the number of learners actively participating on a wide range of digital platforms and devices give rise to an ever-increasing stream of learning data. Learning analytics (LA) can enable learners, teachers, and their institutions to better understand and…

Purpose: The purpose of this article is to examine the data conversation moves enacted by leaders and to bridge organizational leadership for equity and data-informed decision making to practice. I argue that data discussion moves with the purpose of improving equity and learning must reflect core tenets of organizational leadership for…

This book provides a comprehensive introduction by an extraordinary range of experts to the recent and rapidly developing field of learning analytics. Some of the finest current thinkers about ways to interpret and benefit from the increasing amount of evidence from learners' experiences have taken time to explain their methods, describe examples,…

The unforeseen school closures in response to COVID-19 have brought unique challenges to teachers, who were required to not only flexibly shift between on- and off-line learning but also safely promote student-centered and collaborative learning in socially distanced remote and on-campus classrooms. Teachers in South Korea, one of the first…

The main challenges commonly associated with acquiring practical network engineering skills are the requirements for access to specialised and up-to-date network equipment, as well as the high costs associated with obtaining and maintaining this equipment. The PT Anywhere initiative addresses these challenges by offering a mobile environment for…

We examine the impact of the Thompson Scholars Learning Community (TSLC), a comprehensive college transition program serving students with a variety of majors, on students' science, technology, engineering, and math (STEM)-related outcomes. We use an explanatory mixed-methods design, which prioritizes the quantitative analyses and uses qualitative…

Learning Analytics (LA) and adaptive learning are inextricably linked since they both foster technology-supported learner-centred education. This study identifies developments focusing on their interplay and emphasises insufficiently investigated directions which display a higher innovation potential. Twenty-one peer-reviewed studies are…

The purpose of this research is to propose how we can encourage non-computing major first-generation-college-bound students to be actively involved in learning data analytics. Non-computing major students have limited opportunities to take a data analytics related course. The computing major programs have the resource limit for offering none-major…