This article illustrates one of several learning sequences from the Interdisciplinary Mathematics and Science (IMS) Learning project, connecting science and mathematics learning in the primary school. Investigating Body Height involved a series of investigations conducted in Years 5 and 6 across six classes in one school. The project teachers…

Children require access to high-quality statistics education to develop the skills to participate in a technological and data-reliant workforce. This study consisted of a five-lesson integrated STEM unit designed to develop the statistical literacy of 62 6th-grade (11-12 years old) emerging bilingual (EB) learners. Learning was situated in the…

This study investigates how 11- to 12-year-old students construct data-based decision trees using data cards for classification purposes. We examine the students' heuristics and reasoning during this process. The research is based on an eight-week teaching unit during which students labeled data, built decision trees, and assessed them using test…

This study investigated the process of instructional change required to translate data on student progress along learning trajectories (LTs) into relevant instructional modifications. Researchers conducted a professional development session on ratio LTs, which included analyzing 3 years of district-level data from Math-Mapper 6-8, a digital…

In an increasingly data-driven society, making decisions with data is a requirement not only for research scientists but also for navigating life more generally (Kjelvik & Schultheis, 2019). An informed citizenry must be prepared to discover patterns, predict outcomes, make decisions with data, and evaluate data-based claims for legitimacy and…

Background: Wearable technologies offer new opportunities to address in-school physical inactivity. However, children are often excluded from discussing issues which directly impact them, including the use of wearable technologies in a school setting. Thus, the aim of this study is to understand primary school pupils' experiences and perceptions…

The purpose of the study was to better understand the extent to which middle school principals' transformational leadership styles affect teachers' data-informed instruction, the influence of teachers' data-informed instruction on middle school student achievement, and the extent to which transformational leaders affect student achievement through…

The new research results on the online- testing method in the Latvian education system for a learning process assessment are presented. Data mining is a very important field in education because it helps to analyse the data gathered in various researches and to implement the changes in the education system according to the learning methods of…

National testing and reform agendas, with their focus on school improvement, has led to increased collection and scrutiny of student data. The analysis of these data usually occurs at a school level, often by school leaders. What is less common is the opportunity for students to scrutinise their individual data and take ownership over the results…

This study examines what forms of data school leaders use, how they matter for students' learning, and which school contexts matter for such leadership practices to succeed. Utilizing hierarchical linear modeling, we analyzed survey responses from 1,381 school leaders and administrative data from 269 Florida schools. We find that although school…

Purpose: Drawing from the equitable education fund (EEF) launching 6Qs innovation in the teacher school quality program (TSQP) for small and medium schools, this research aims to analyze the effect size of the ordinary national educational test (O-NET) scores between TSQP schools that implement 6Qs innovation and non-TSQP schools and explain the…

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…

Large-scale learning assessments can be used to generate performance and contextual data on student learning outcomes. They can be national, regional, or international; school based or household based. The UNESCO International Institute for Educational Planning (IIEP-UNESCO) has conducted a qualitative study to explore both how and why learning…

Sources of longitudinal achievement data are increasing thanks partially to the expansion of available interim assessments. These tests are often used to monitor the progress of students, classrooms, and schools within and across school years. Yet, few statistical models equipped to approximate the distinctly seasonal patterns in the data exist,…

Recent work describes methods for systematic, data-driven improvement to instructional content and calls for diverse teams of learning engineers to implement and evaluate such improvements. Focusing on an approach called "design-loop adaptivity," we consider the problem of how developers might use data to target or prioritize particular…