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 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…