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National Forum on Education Statistics, 2023
This guide is designed for use by school, district, and state education agency staff to improve the effectiveness of efforts to collect and use discipline data, including reporting accurate and timely data to the federal government. It explains the importance of collecting discipline data, identifies key considerations for agencies implementing…
Descriptors: Discipline, Data Collection, Data Analysis, School Districts
National Forum on Education Statistics, 2012
Education data are growing in quantity, quality, and value. When appropriately used to guide action, data can be a powerful tool for improving school operations, teaching, and learning. Education stakeholders who possess the knowledge, skills, and abilities to appropriately access, analyze, and interpret data will be able to use data to take…
Descriptors: Educational Indicators, Data Interpretation, Information Utilization, Data Analysis
Pan, Diane; Smith-Hansen, Lotte; Jones, Debra Hughes; Rudo, Zena H.; Alexander, Celeste; Kahlert, Rahel Kahlert, Rahel – US Department of Education, 2004
Information is one of the most important tools education decision makers need to help them effectively spend taxpayer money, allocate qualified staff, and determine the effectiveness of education investments. Decision makers must understand the role and influence of monetary and staff resources on the education system, and they must have…
Descriptors: Academic Achievement, Decision Making, State Departments of Education, Resource Allocation

Keith, Bruce; Moore, Helen A. – Teaching Sociology, 1995
Reports on a study of professional socialization and the emergence of career aspirations among 566 graduate students in sociology. Finds that access to initial funding and mentoring have substantial effects on students' professional socialization. (CFR)
Descriptors: Career Choice, Decision Making, Departments, Graduate Students

Kassicieh, Suleiman K.; Nowak, John W. – Information Processing and Management, 1986
Discusses importance of academic planning and describes a model-based decision support system for academic units in a university hierarchy. This system integrates macro-level decisions by examining individual departments' budgets to determine future plans. Quantitative techniques for forecasting change are reviewed, including use of spreadsheet…
Descriptors: Administrative Organization, Budgeting, Computer Simulation, Databases