The visual analysis of data presented in time-series graphs are common in single-case design (SCD) research and applied practice in school psychology. A growing body of research suggests that visual analysts' ratings are often influenced by construct-irrelevant features including Y-axis truncation and compression of the number of data points per…

Data-driven decision-making and data-intensive research are becoming prevalent in many sectors of modern society, i.e. healthcare, politics, business, and entertainment. During the COVID-19 pandemic, huge amounts of educational data and new types of evidence were generated through various online platforms, digital tools, and communication…

In this new edition of a bestseller, school counseling scholar and advocate Trish Hatch and National School Counselor of the Year Julie Hartline provide school counselors with new ways for moving from reactive to proactive and from random to intentional counseling. By using data to determine what all students deserve to receive and when some…

Before developing a school- and community-wide work plan around preventing bullying and harassment, school administrators should employ data collection tools to determine their specific areas of focus. Successful bullying prevention efforts must be driven by local data and rooted in research on effective practices. These policies must undergo…

Prospective longitudinal data collection is an important way for researchers and evaluators to assess change. In school-based settings, for low-risk and/or likely-beneficial interventions or surveys, data quality and ethical standards are both arguably stronger when using a waiver of parental consent--but doing so often requires the use of…

Tools for automatic grading programming assignments, also known as Online Judges, have been widely used to support computer science (CS) courses. Nevertheless, few studies have used these tools to acquire and analyse interaction data to better understand the students' performance and behaviours, often due to data availability or inadequate…

Identifying effective literacy interventions for teachers of very young children is important, but it is not easy. In this case study, we share our experiences implementing a quasi-experimental evaluation of an early literacy program. We describe the design and context of the study and discuss three key issues that we encountered with data…

Faced with increasing demands for accountability, teachers are having to base their instructional decisions and choice of interventions on data on student performance. This book shows how to make this otherwise daunting task much more manageable by means of case studies and countless evidence-based forms and graphs. Although this book often refers…

This article presents discussion and recommendations on approaches to retrospectively evaluating development interventions in the long term through a systems lens. It is based on experiences from the implementation of an 18-month study to investigate the impact of development interventions on economic and social change over a 40-year period in the…

This paper defines and promotes the qualities of a "bottom-up" approach to single-case research (SCR) data analysis. Although "top-down" models, for example, multi-level or hierarchical linear models, are gaining momentum and have much to offer, interventionists should be cautious about analyses that are not easily understood, are not governed by…

This guide for district and school leaders shows how to recognize opportunities to embed randomized controlled trials (RCTs) into planned policies or programs. Opportunistic RCTs can generate strong evidence for informing education decisions--with minimal added cost and disruption. The guide also outlines the key steps to conduct RCTs and responds…

Learning Analytics (LA) is a field that aims to optimize learning through the study of dynamical processes occurring in the students' context. It covers the measurement, collection, analysis and reporting of data about students and their contexts. This study aims at surveying existing research on LA to identify approaches, topics, and needs for…

The use of data to inform decisionmaking and practice at the school and district levels is now a common feature of reform efforts. Advances in districts' technological capacities have produced data systems that allow a flow of data to and from schools, often to the point of creating an overwhelming flood of information. To make the flow of…

As the quality of educational outputs has been problematized, accountability systems have driven reform based upon summative assessment data. These policies impact the ways that educators use data within schools and subsequently, how teacher education programs may adjust their curricula to teach data-driven decision-making to inform instruction.…

We report a study that addressed behavior data recording by direct-care staff at a child services program. In response to a decreasing percentage of daily data recording in two community-based group homes, a supervisory intervention was implemented, consisting of a revised data recording form and providing performance feedback to the direct-care…