A problem exists in NC Montessori schools with effective data analysis for specific learning disabilities (SLD) placement. The purpose of this study was to identify administrators' and teachers' perceptions of data collection and analysis within multitiered systems of support (MTSS) in a Montessori school. Fixsen's implementation science theory…

The rise of data collection in the public and private sectors has presented policymakers with an unprecedented opportunity to leverage vast amounts of data to create more efficient systems, improve program performance, and drive equitable outcomes. Empowering policymakers and practitioners with functional access to accurate data has the potential…

Attention to mixed methods studies research has increased in recent years, particularly among funding agencies that increasingly require a mixed methods approach for program evaluation. At the same time, researchers operating within large-scale, rapid-turnaround research projects are faced with the reality that collection and analysis of large…

This report presents school-level finance data on expenditures by function from the School-Level Finance Survey (SLFS). The SLFS is an extension of two existing collections being conducted by the National Center for Education Statistics (NCES) in collaboration with the Census Bureau: the School District Finance Survey (F-33) and the state-level…

The 2020 General Assembly directed the State Council of Higher Education for Virginia (SCHEV) to develop a plan for implementing a statewide survey of institutional expenditures by program and academic discipline at Virginia's public higher education institutions, and submit a report and recommendations to the Governor and the Chairs of the House…

For any labor market to function properly, clear information is needed to guide decision making; its absence invariably leads to less than optimal decisions and inefficiencies. While the broader labor market is riddled with imperfect information, the teacher labor market is particularly vulnerable--largely for the lack of the most basic…

"Which preschool programs best prepare students for kindergarten?" "Which students from which schools need remediation classes in higher education?" "How successful are college graduates in the workforce by major or credential?" These are just a few of the questions that can be answered by a robust longitudinal data…

The link between health and learning is clear: healthy, active and well-nourished children are more likely to attend school, arrive ready to learn and stay engaged in class. Yet far too many students spend their days in schools that do not offer them adequate clean air and water, nutritious food, physical activity and the support of a school…

In recent years and especially over the past 12 months, with the COVID-19 pandemic and the unrest after the death of George Floyd, community colleges have been making efforts to view and rethink their missions through an equity lens. These efforts have included turning this prism toward institutional operations like student services, human…

The issue of student retention and graduation from postsecondary institutions has grown in stature over the past decade. While the last 40 years of federal and state policies have focused largely on access to college, there is now a very real interest in not only getting students into college but also helping them earn baccalaureate and other…

This issue brief describes the programs and systems of the MDRC Center for Data Insights. Ranging from simple descriptive summaries to advanced machine learning algorithms, the Center's eight current projects aim to use institutions' increasingly rich data to provide new insights that can help refine and target their client's services: (1)…

This study takes a novel approach toward understanding success in a math course by examining the linguistic features and affect of students' language production within a blended (with both on-line and traditional face to face instruction) undergraduate course (n=158) on discrete mathematics. Three linear effects models were compared: (a) a…

Purpose: In an era of unprecedented student measurement and emphasis on data-driven educational decision making, the full potential for using data to target resources to students has yet to be realized. This study explores the utility of machine-learning techniques with large-scale administrative data to identify student dropout risk. Research…

In order to enhance Extension evaluation efforts it is important to understand current practices. The study reported here researched the evaluation behaviors of county-based Extension professionals. Extension professionals from eight states (n = 1,173) responded to a survey regarding their evaluation data collection, analysis, and reporting…

The field of learning analytics is being discussed in many circles as an emerging concept in education. In many districts and states, the core philosophy behind learning analytics is not entirely new; for more than a decade, discussions of data-driven decision making and the use of data to drive instruction have been common. Still, the U.S.…