Performance management in university-based scientific research institutions is essential for driving reform, advancing education quality, and fostering innovation. However, current performance evaluation models often focus solely on research indicators, neglecting the critical interdependence between the education and research systems. This…

School districts have recognized the undeniable power of using data to enhance performance. As a result, teachers are now required to use data to prepare for critical state assessments and to improve district levels. These assessments are crucial in determining the school's rating by the state and can even result in a state takeover if scores are…

The focus of this study was derived from staggering attrition rates that it calls centers year over year. At times call centers post-COVID-19 pandemic saw attrition rates fluctuating between 30%-50%. With any job there are challenges that are faced. These attrition rates stand 28%-40% higher than the United States 2023 national attrition rates of…

Performance-based funding policies for postsecondary institutions have been enacted throughout the United States as an answer to reductions in public funding and increased accountability mandates. Institutional effectiveness, as demonstrated through metrics such as graduation and retention rates, dictates the level of funding received. Educational…

Data Envelopment Analysis (DEA) is a widely adopted non-parametric technique for evaluating R&D performance. However, traditional DEA models often struggle to provide reliable solutions in the presence of data uncertainty. To address this limitation, this study develops a novel robust super-efficiency DEA approach to evaluate R&D…

State education departments find themselves pressured to reduce costs while improving student performance. To do so, state education departments must measure the performance of each school district in an objective, data-informed manner. We present a benchmarking methodology and illustrate its application in New York State school districts. We…

In this paper, we put forward the OTTO Model as a means for developing data literacy in pre-service teacher education. The OTTO Model was developed using a combination of quantitative and qualitative data drawn from a three-year study investigating the nature and development of pre-service teachers' data literacy. The aim of the study was to…

Research has shown that mathematical proficiency gaps are related to students' and schools' indicators of poverty, with fewer studies on neighborhood effects on achievement gaps. Although this literature has accounted for students' nesting within schools, so far, methodological constraints have not allowed researchers to formally account for…

Equitable opportunities for performance measurement learning among social work graduate students can create a diverse professional pipeline toward higher performing organizations. A Foundation-University partnership was developed to "expand the bench" of students, primarily of color, trained in performance measurement with the…

Since 2016, the Advanced Distributed Learning (ADL) Initiative has been developing the Total Learning Architecture (TLA), a 4-pillar data strategy for managing lifelong learning. Each pillar describes a type of learning-related data that needs to be captured, managed, and shared across an organization. Each data pillar is built on a set of…

"Using Data for Continuous Improvement in Educator Preparation" provides case studies that illuminate and contextualize the ways in which educator preparation programs determine the data they need to improve, collect data, analyze data, share data with stakeholders, and close the loop by making focused improvements based on the data.…