The purpose of this quantitative study was to provide school district leaders and policymakers information of the impact grade configuration had on academic performance using math and ELA ILEARN scores over a three-year period. The study included data from 585 schools that were classified into four groups: Elementary Setting, Intermediate Setting,…

Preparing data-literate citizens and supporting future generations to effectively work with data is challenging. Engaging students in Knowledge Building (KB) may be a promising way to respond to this challenge because it requires students to reflect on and direct their inquiry with the support of data. Informed by previous studies, this research…

Purpose: In today's digital world, data-driven digital artefacts pose challenges for education, as many students lack an understanding of data and feel powerless when interacting with them. This paper aims to address these challenges and introduces the data awareness framework. It focuses on understanding data-driven technologies and reflecting on…

Purpose: This study aims to explore how network visualization provides opportunities for learners to explore data literacy concepts using locally and personally relevant data. Design/methodology/approach: The researchers designed six locally relevant network visualization activities to support students' data reasoning practices toward…

This case study evaluated the impact of science, technology, engineering, and mathematics initiatives in improving educational outcomes in the United Kingdom. Using secondary data in the form of official datasets approved by the national pupil database, Year 7 cohort was longitudinally followed from the beginning of Key Stage 3 till the end of Key…

Data-based decision making (DBDM) is presumed to improve student performance in elementary schools in all subjects. The majority of studies in which DBDM effects have been evaluated have focused on mathematics. A hierarchical multiple single-subject design was used to measure effects of a 2-year training, in which entire school teams learned how…

The Conover Solution is a nonparametric method used to analyze relative growth in students' achievement on state tests administered on two or more occasions. However, there has been very little research assessing the robustness of this method in the presence of missing data. Using vertically scaled and non-vertically scaled data from the math…

We explore 11-12-year-old students' emerging ideas of models and modelling as they engage in a data-modelling task involving inquiry based on data obtained from an experiment. We report on a design-based study in which students identified what and how to measure, decided how to structure and represent data, and made inferences and predictions…

The integration of artificial intelligence (AI) topics into K-12 school curricula is a relatively new but crucial challenge faced by education systems worldwide. Attempts to address this challenge are hindered by a serious lack of curriculum materials and tools to aid teachers in teaching AI. This article introduces the theoretical foundations and…

The Common Core State Standards for Mathematics have a widespread impact on children's statistical learning opportunities. The Grade 6 standards are particularly ambitious in the goals they set. In this critique, experiences helping children work toward the Grade 6 Common Core statistics expectations are used in conjunction with previous research…

With the rise of big data, it is becoming increasingly important to educate groups of students at many educational levels about data analytics. In particular, students without a strong mathematical background may have an unenthusiastic attitude towards high-dimensional data and find it challenging to understand relevant complex analytical methods,…

The purpose of this study was to determine if there was a difference in how high and low performing elementary school districts use and analyze data to differentiate instruction, make changes to district/grade level curriculum, determine professional development needs, determine teacher effectiveness, and determine the use of school district…

The TALPS study aims to build on the existing research base to develop promising methodologies to identify chronically low-performing and turnaround schools, as well as to identify promising strategies for turning around chronically low-performing schools. By looking specifically at schools identified as turnaround, in comparison to nonturnaround…

We describe activities created to help student participants in Project ITEAMS (Innovative Technology-Enabled Astronomy for Middle Schools) develop a deeper understanding of picture elements (pixels), image creation, and analysis of the recorded data. ITEAMS is an out-of-school time (OST) program funded by the National Science Foundation (NSF) with…

To meet the constantly changing needs of schools and diverse learners, educators must frequently monitor student learning, revise curricula, and improve instruction. Consequently, it is critical that careful analyses of student performance data are ongoing components of curriculum decision-making processes. The primary purpose of this study is to…