Data- driven decision making DDDM in school settings is often guided and influenced by various sources of data that assist in improving students' outcomes. School principals as the main educational leaders, play a pivotal role in DDDM using the available school data. Semi-structured interviews with 24 school principals were conducted to…

Adapting interventions based on learner progress is paramount to the effectiveness of interventions in special education and applied behavior analysis. Although there is some research on effective methods for training practitioners to make general instructional decisions (e.g., modify an intervention) based on graphed performance data, research on…

This chapter explores the potential of integrating conversational AI tools such as ChatGPT with data visualization (DV) tools such as Power BI in higher education settings. A brief history of chatbots is summarized and challenges and opportunities in higher education are outlined. The highlights include AI's prospects for enhancing data-informed…

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…

In current contexts of education, educators are tasked with using data, most often without any critical preparation to do so. In this way, data are presented as objective measures of student progress and participation in school without consideration of the systemic and structural influences on that progress and participation. This article reports…

We report findings of this replication study, examining the internalizing subscale (SRSS-I4) of the revised version of the Student Risk Screening Scale for Internalizing and Externalizing behavior (SRSS-IE 9) and the internalizing subscale of the Teacher Report Form (TRF). Using the sample from 13 elementary schools across three U.S. states with…

Background: Studies of socio-scientific decision-making in times of crisis are in their infancy. This study investigates how minoritized youth engage and make sense of newly developed COVID-19 vaccines and their intersections with the evolving multi-pandemic. Guided by theories of lively data, data sense and epistemic injustice, we center the…

From a new institutional theoretical perspective, this article explores school actors' sense-making linked to data-based decision making (DBDM) policy in general and processes of data analysis in particular. The study revealed how actors' interpretation of and response to DBDM pointed to strong and weak couplings between and within the local…

Purpose: School principals are increasingly responsible for acting as instructional leaders, but research on data teams typically considers principals as secondary players responsible for ensuring that meetings occur but not necessarily for their quality. We investigated how elementary school principals in one district committed to data use…

In a time when fewer resources force school leaders to make critical decisions, the data-driven decision-making model continues to offer promise. This research project provides observations about factors used for decision making from 14 district leaders across five Iowa school districts. Placing these factors for decision making within the…

Students with extensive support needs (ESN), most of whom are taught in separate settings by special educators without extensive academic preparation, have difficulty making progress in the general education curriculum. Although there is evidence that data-based decision-making improves achievement for a wide range of students, there is little…

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…

Enabling college graduates to achieve career success is increasingly considered a major responsibility of universities. Many studies have developed models of predicting students' career decisions and have sought to provide appropriate treatments or early support for students to achieve this goal. Most studies, however, have focused on using…

We present a historical case study of "data-driven" general education policy reform at the City University of New York, where within-system transfer issues prompted the need for curricular reform that was debated and eventually implemented from 2011 to 2017. Through an empirical examination of artifacts such as meeting minutes, internal…

Background: To improve the use of evidence in policy and practice, many organisations and individuals seek to promote research-policy engagement activities, but little is known about what works. Aims and objectives: We sought (a) to identify existing research-policy engagement activities, and (b) evidence on impacts of these activities on research…