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…

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…

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…

Collecting treatment integrity data is critical for (a) strengthening internal validity within a research study, (b) determining the impact of an intervention on student outcomes, and (c) assessing the need for implementation supports. Although researchers have noted the increased inclusion of treatment integrity data in published articles, there…

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…

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…

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…

Purpose: The purpose of this review article was to (a) scope the literature related to coaching caregivers of children with autism to provide an overview of current practices for assessment and intervention conducted via telepractice in collaboration with caregivers and (b) examine commonly reported challenges related to telepractice and potential…

Treatment fidelity data are critical to evaluate intervention effectiveness, yet there are only general guidelines regarding treatment fidelity measurement. Initial investigations have found treatment fidelity data collected via direct observation to be more reliable than data collected via permanent product or self-report. However, the comparison…

This book is designed to build and enhance educators' knowledge about decision-making processes, including the use of multiple sources of assessment and data to inform instruction, interventions, services, and supports for all students within a comprehensive system to conduct action research. This resource demystifies, describes, and connects the…

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…

BASIE is a framework for interpreting impact estimates from evaluations. It is an alternative to null hypothesis significance testing. This guide walks researchers through the key steps of applying BASIE, including selecting prior evidence, reporting impact estimates, interpreting impact estimates, and conducting sensitivity analyses. The guide…

How can we close opportunity gaps for young children affected by poverty and systemic racism--and build hope and resilience for children and their families? Research points the way forward, and in this timely volume, 40+ leading researchers identify new approaches, insights, and technologies that can promote educational equity and improve outcomes…

Direct Behavior Ratings (DBRs) are behavioral assessment methods that combine the benefits of systematic direct observation and behavior rating scales. That is, DBRs involve the observation of operationally defined target behaviors during a prespecified observation period and the evaluation of those behaviors via brief ratings. In this way, DBR is…