Publication Date
| In 2026 | 0 |
| Since 2025 | 195 |
| Since 2022 (last 5 years) | 1174 |
| Since 2017 (last 10 years) | 3394 |
| Since 2007 (last 20 years) | 7948 |
Descriptor
Source
Author
Publication Type
Education Level
Audience
| Practitioners | 935 |
| Teachers | 576 |
| Policymakers | 493 |
| Researchers | 485 |
| Administrators | 411 |
| Students | 79 |
| Community | 51 |
| Media Staff | 48 |
| Parents | 48 |
| Counselors | 20 |
| Support Staff | 17 |
| More ▼ | |
Location
| Australia | 369 |
| California | 365 |
| United States | 351 |
| Canada | 261 |
| United Kingdom | 249 |
| Texas | 197 |
| Florida | 188 |
| Turkey | 176 |
| New York | 173 |
| Illinois | 152 |
| Pennsylvania | 141 |
| More ▼ | |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
| Meets WWC Standards without Reservations | 3 |
| Meets WWC Standards with or without Reservations | 4 |
| Does not meet standards | 2 |
Peer reviewedSquires, Jane – Infants and Young Children, 1996
The "Ages and Stages Questionnaires," a parent-completed developmental monitoring system, is described, and various strategies for using the system to identify young children with developmental delays are compared. Strategies include mail-out, home visit, on-site (completed by either parent with assistance from service provider),…
Descriptors: Child Development, Data Collection, Developmental Delays, Developmental Stages
Peer reviewedFarland, Gary – Journal of Education Finance, 1997
Stresses the need for having financial and staff data available at the school level and relates Minnesota's state department of education's experience with school-level data collection. Schools need to develop unit record data collection and integrated, relational databases. School-level data can provide answers to major questions concerning…
Descriptors: Costs, Data Collection, Elementary Secondary Education, Human Resources
Peer reviewedPatterson, Valerie – Journal of Career Planning & Employment, 1996
Describes the practice of benchmarking and its use in staffing. Examines benchmarking's roots in quality control and how businesses can establish reference points in pursuing their goals. Includes suggestions on planning benchmarking efforts, strategies for data collection, data analysis, and taking action. Provides a benchmarking code of conduct…
Descriptors: Benchmarking, Data Collection, Evaluation Methods, Evaluation Utilization
Peer reviewedPorter, Stephen R. – Journal of College Student Retention, 2004
Discusses empirical problems in confining college student retention studies to stay-versus-go outcomes, reviewing data resources (exit surveys, transcript requests, withdrawn student surveys, state transfer student databases, and the National Student Clearinghouse's Enrollment Search Program), which can enhance understanding of first-year…
Descriptors: Academic Persistence, College Students, Data Collection, Dropouts
Peer reviewedMelamid, Elan; Brodbar, Gabriel – Child Welfare, 2003
This article presents results from an outcomes-based needs assessment in an urban child welfare service district. The assessment's methodology emphasized consistent data collection from actual case records and explicitly included line staff and clients in the planning process. It was concluded that such reviews could benefit a variety of…
Descriptors: Case Records, Child Welfare, Children, Community Programs
Peer reviewedDuy, Joanna; Vaughan, Liwen – Journal of Academic Librarianship, 2003
Vendor-provided electronic resource usage statistics are not currently standardized across vendors. This study investigates the feasibility of using locally collected data to check the reliability of vendor-provided data. Vendor-provided data were compared with local data collected from North Carolina State University (NCSU) Libraries' Web…
Descriptors: Academic Libraries, Comparative Analysis, Data Analysis, Data Collection
Connaway, Lynn Silipigni – Library Administration & Management, 1996
Summarizes the literature explaining focus group interview techniques and provides ideas on how they can be used for needs assessment and program evaluation in libraries and information centers. Discussion includes focus group session objectives, the level of moderator involvement, various methodologies, data analysis, and reporting in qualitative…
Descriptors: Data Analysis, Data Collection, Evaluation Methods, Focus Groups
Peer reviewedTschechtelin, James D. – Community College Journal of Research and Practice, 1997
Provides information on the population of Maryland and describes the development of the state's 18 community colleges. Reviews student and system characteristics, governance, and finances. Highlights current issues related to procuring state financial support, revising the transfer policy, maintaining system-wide data, and implementing distance…
Descriptors: College Administration, Community Colleges, Data Collection, Demography
Peer reviewedBarton, R. – School Science Review, 1993
Explores the reasons why data logging is still not an integral part of the science curriculum in the majority of British schools. Suggests some strategies to assist science teachers in taking the initial steps towards utilizing this technology. (DDR)
Descriptors: Computer Uses in Education, Data Collection, Educational Strategies, Foreign Countries
Peer reviewedAlcock, James – Journal of Geological Education, 1994
Explains how controlling student access to data can be used as a strategy enabling students to take the role of a research geologist. Students develop models based on limited data and conduct field tests by comparing their predictions with the additional data. (DDR)
Descriptors: College Curriculum, Course Content, Data Analysis, Data Collection
Peer reviewedTinker, Robert F. – Journal of Science Education and Technology, 1997
Explores student-scientist partnerships (SSPs) that help students gain a unique understanding of both the content and the process of science. Discusses the potential of SSPs, the range of SSP activities, a strategy for national impact, the educational importance of SSPs, the research importance of SSPs, and technology as a facilitator. (JRH)
Descriptors: Cooperation, Data Analysis, Data Collection, Educational Change
Peer reviewedWolery, Mark; Brashers, Margaret Sigalove; Neitzel, Jennifer C. – Topics in Early Childhood Special Education, 2002
This article explains how educators can use the ecological congruence assessment process for identifying functional goals for young children with disabilities. Process steps include: teacher collects information about functioning in usual classroom activities, routines, and transitions; summarizes the collected information; and shares the…
Descriptors: Child Care Centers, Child Caregivers, Classroom Observation Techniques, Data Collection
Peer reviewedRonau, Robert N.; Karp, Karen S. – Mathematics Teaching in the Middle School, 2001
Reports on a project in which a 6th grade class determined the type of trash being thrown away on their school grounds through data collection, analysis, and graphing. (YDS)
Descriptors: Data Collection, Educational Technology, Grade 6, Graphs
Peer reviewedSchall, Carol – Focus on Autism and Other Developmental Disabilities, 2002
This article provides instruction for caregivers on managing and monitoring psychotropic medication for individuals with autism. Includes 20 questions for caregivers to ask about psychotropic medication, 12 guidelines for caregivers to follow when giving medications, and specific examples of data collection methods to measure the effect of…
Descriptors: Autism, Data Collection, Drug Therapy, Elementary Secondary Education
Peer reviewedCooper, Linda Z. – Journal of the American Society for Information Science and Technology, 2002
Presents an overview of some of the methodology used in a project that examined children's understanding of library information and how those perspectives change in the first five years of formal schooling. Following a description of data collection methods and analysis, a discussion focuses on the reasons for using these particular methods of…
Descriptors: Access to Information, Cognitive Processes, Data Analysis, Data Collection


