This article provides teachers with a toolkit for assessing students in the context of data-based individualization (DBI) in mathematics. Assessing students is a critical component of DBI because it provides teachers with information about what they may need to modify in their instructional programs. In this article, we provide teachers with…

Recent data from statewide assessments, scores on the National Assessment of Educational Progress (NAEP), and college remediation needs show that an increasing number of K-12 students are not performing at grade level. As schools look to support these students' learning, some districts are turning to a proven strategy for identifying the students…

Data-based instruction (DBI) is a process in which teachers use progress data to make ongoing instructional decisions for students with learning disabilities. Curriculum-based measurement (CBM) is a common form of progress monitoring, and CBM data are placed on a graph to guide decision-making. Despite the central role that graph interpretation…

Background/Purpose: This study examines the use of the Interactive Growth Guide, a structured coaching tool, within a year-long high-intensity induction program for beginning teachers. Specifically, the study investigates how the Interactive Growth Guide was integrated into the mentoring relationship between a beginning teacher and her coach and…

Enhancing special educators' data literacy is critical to informing instructional decision-making, especially for students with learning disabilities. One tool special educators commonly use is curriculum-based measurement (CBM). These data are displayed on time-series graphs, and student responsiveness is evaluated. Graph construction varies and…

Current literature exists centered on Multi-Tiered Systems of Support (MTSS) framework, its components, and ways in which MTSS is intended to support all students. Yet, there is a gap in the literature that examines how elementary schools are implementing it. This dissertation study sought to understand what the MTSS framework implementation at…

Pragmatically, machine learning techniques can improve educators' capacity to monitor students' learning progress when applied to quality data. For developing countries, the major obstacle has been the unavailability of quality data that fits the purpose. This is partly because the in-use information systems are either not properly managed or not…

The purpose of this small case-study is to gain an in depth understanding of how secondary school teachers perceive that data walls impact their teaching practices and subsequently, students' learning and growth. By drawing on a conceptual model of evidence-informed practice (EIP), this case study examined responses from secondary school teachers…

Through time-series graphs, teachers often evaluate progress monitoring data to make both low- and high-stakes decisions for students. The construction of these graphs--specifically, the presence of an aimline and the data points per x- to y-axis ratio (DPPXYR)--may impact decisions teachers make. The purpose of this study was to evaluate the…

Although student advising is known to improve student success, its application is often inadequate in institutions that are resource constrained. Given recent advances in large language models (LLMs) such as Chat Generative Pre-trained Transformer (ChatGPT), automated approaches such as the AutoScholar Advisor system affords viable alternatives to…

The collection of student data through screening and progress monitoring of social and emotional learning (SEL) skills is just as important as the implementation of curriculum and practices. Monitoring skill acquisition allows teachers to identify effective practices, provide intervention, and intensify support for students who need it. In this…

Monitoring applications (MAs) use digital and online tools to collect and track data on student behavior, and they have become increasingly popular among schools. Empirical research on these complex surveillance platforms is scant, and little is known about the efficacy or impact that they have on students. This study used a multi-method…

Data-based individualization (DBI) is a framework that allows educators to make timely and informed decisions about student progress in academics or behavior. In this article, we focus on the DBI framework as applied to math intervention within a tiered support model for students experiencing math difficulty. We review how DBI starts with an…

Schooling in Australia has become subject to increased processes of data-based governance. This article draws upon the insights of an experienced teacher, 'Meriam', who, having taught more than 34-years over almost a 50-year span, reflected upon the nature of such changes. Utilising theorising in relation to datafication processes and…

The purpose of this explorative study was to examine the use and understanding of key components of data-based decision making by educators in two countries--Germany and the United States. Educators responded to a survey that asked about data use and characteristics related to data-based decision making (DBDM). Results suggest educators in both…