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…

This paper deeply discusses the transformation potential of integrating Internet big data into the pre-school education model in colleges and universities. Through in-depth analysis, we studied the challenges and opportunities faced by preschool education in colleges and universities, and discussed the innovative influence of big data technology…

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…

Statewide longitudinal data systems (SLDSs) can enable researchers, policymakers, and practitioners to identify and understand important relationships and trends across the education-to-workforce continuum. A well-developed SLDS can increase state and territory governments' ability to establish more informed and equitable policies, enable agency…

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…

Conducting high-quality overviews of reviews (OoR) is time-consuming. Because the quality of systematic reviews (SRs) varies, it is necessary to critically appraise SRs when conducting an OoR. A well-established appraisal tool is A Measurement Tool to Assess Systematic Reviews (AMSTAR) 2, which takes about 15-32 min per application. To save time,…

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…

Early Warning Systems (EWS) are research-based analytics that use statistical models to assess dropout risk. School leaders use this analytic to consolidate data about a student and provide actionable data to craft an intervention. Little is currently known about the processes involved in school implementation or data use. By analyzing Montana EWS…

Background: Understanding knowledge utilisation in policymaking is a core task for the social and political sciences. However, limitations and biases abound in commonplace approaches to measuring such use. Consequently, we have little systematic evidence of the extent to which knowledge sources are used in policy decisions. Aims and objectives:…

Single-case design is a research methodology that entails repeated measurement to assess the influence of an independent variable on a dependent variable over time. Data collected in this manner are regularly analyzed using visual analysis of data displayed in a linear graph. Although there is agreement regarding critical elements of visual…

There is a significant amount of data available about students and their learning activities in many educational systems today. However, these datasets are frequently spread across several different digital services, making it challenging to use them strategically. In addition, there are no established standards for collecting, processing,…

Evaluation is a critical component of continuous improvement in education. Robust evaluations enable engaged parties to determine program and intervention impact on key outcomes, identify areas for improvement, and guide future actions. Additionally, as educational systems increasingly focus on data-driven decisionmaking, evaluation becomes even…

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…

Background: There is growing recognition in the education sector of the critical role empirical data plays in aiding strategic decision-making and supporting personalised learning. The call for increased and more nuanced data-driven decision-making has been primarily addressed by the institutional use of student learning dashboards and learner…

Purpose: Research shows data-informed leadership matters for school improvement and student achievement, but less is known about what motivates leaders' data use toward such outcomes, particularly in the Catholic school context. Design/methodology/approach: This qualitative interview study uses interview (n = 23) data from a sample of Catholic…