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da Silva, Lidia M.; Dias, Lucas P. S.; Barbosa, Jorge L. V.; Rigo, Sandro J.; dos Anjos, Julio C. S.; Geyer, Claudio F. R.; Leithardt, Valderi R. Q. – Informatics in Education, 2022
Advances in information and communication technologies have contributed to the increasing use of virtual learning environments as support tools in teaching and learning processes. Virtual platforms generate a large volume of educational data, and the analysis of this data allows useful information discoveries to improve learning and assist…
Descriptors: Learning Analytics, Cooperative Learning, Distance Education, Electronic Learning
Klein-Collins, Rebecca; Taylor, Jason; Bishop, Carianne; Bransberger, Peace; Lane, Patrick; Leibrandt, Sarah – Council for Adult and Experiential Learning, 2020
This report describes the adult student's experience with prior learning assessment (PLA) using student record data from 72 degree-granting postsecondary institutions in the United States, primarily focusing on the data from 69 of those institutions based on the more detailed data provided by those institutions to the study. Researchers from the…
Descriptors: Prior Learning, Student Evaluation, Adult Students, Student Records
Klein-Collins, Rebecca; Taylor, Jason; Bishop, Carianne; Bransberger, Peace; Lane, Patrick; Leibrandt, Sarah – Council for Adult and Experiential Learning, 2020
This report describes the adult student's experience with prior learning assessment (PLA) using student record data from 72 degree-granting postsecondary institutions in the United States, primarily focusing on the data from 69 of those institutions based on the more detailed data provided by those institutions to the study. Researchers from the…
Descriptors: Prior Learning, Student Evaluation, Adult Students, Student Records
Lynch, Collin F. – Theory and Research in Education, 2017
Big Data can radically transform education by enabling personalized learning, deep student modeling, and true longitudinal studies that compare changes across classrooms, regions, and years. With these promises, however, come risks to individual privacy and educational validity, along with deep policy and ethical issues. Education is largely a…
Descriptors: Data Analysis, Data Collection, Privacy, Evaluation Methods
González-Sancho, Carlos; Vincent-Lancrin, Stéphan – Policy Futures in Education, 2016
Data use is becoming a prominent strategy for educational innovation and improvement across countries. However, the fragmentation of data collection often hinders the capacity of policymakers, researchers and practitioners to access and analyse the wealth of data routinely generated in educational institutions. A critical step towards realising…
Descriptors: Educational Change, Information Systems, Data Collection, Integrated Learning Systems
Hunter, Gerald P.; Williamson, Stephanie; Wilks, Asa; Hanley, Janet M.; Stecher, Brian M. – RAND Corporation, 2020
The Intensive Partnerships for Effective Teaching initiative, which was funded by the Bill & Melinda Gates Foundation, was a multiyear effort to improve student outcomes--particularly high school graduation and college attendance among low-income minority students--by increasing student access to effective teaching. The RAND Corporation worked…
Descriptors: Data Collection, Data Use, Instructional Effectiveness, Teacher Effectiveness
Cohen, Jonathan – Regional Educational Laboratory Mid-Atlantic, 2015
The REL Mid-Atlantic Webinar discussed the elements in a positive school climate and shared different methods for assessing school data, including the Comprehensive School Climate Inventory. The Q&A presented in this document address the questions participants had for Dr. Cohen following the webinar. The webinar recording and PowerPoint…
Descriptors: Educational Environment, School Culture, Evaluation Methods, Measurement Techniques
Crawford, Lindy – Preventing School Failure, 2014
This article discusses the role of assessment in a response-to-intervention model. Although assessment represents only 1 component in a response-to-intervention model, a well-articulated assessment system is critical in providing teachers with reliable data that are easily interpreted and used to make instructional decisions. Three components of…
Descriptors: Intervention, Models, Response to Intervention, Student Evaluation
Mah, Dana-Kristin – Technology, Knowledge and Learning, 2016
Learning analytics and digital badges are emerging research fields in educational science. They both show promise for enhancing student retention in higher education, where withdrawals prior to degree completion remain at about 30% in Organisation for Economic Cooperation and Development member countries. This integrative review provides an…
Descriptors: Educational Research, Data Collection, Data Analysis, Recognition (Achievement)
Lee, Brason – Multiple Voices for Ethnically Diverse Exceptional Learners, 2014
This study applies a diagnostic errors framework to identify and classify mistakes that were made in a psychoeducational assessment of a bilingual student who was misidentified as a person with autism. Findings of diagnostic errors were categorized under four domains--faulty knowledge, faulty data gathering, faulty data processing, and faulty…
Descriptors: Bilingualism, Evaluation Methods, Error Patterns, Knowledge Level
Data Quality Campaign, 2014
A wide array of federal funding opportunities exists to help states build a secure infrastructure to support data use and ensure that students are prepared for college and careers. Because the reporting requirements for these programs are frequently developed without input from other programs and agencies, grantees are required to report data that…
Descriptors: Student Records, Data Collection, Compliance (Legal), Federal Programs

Marco, Gary L.; And Others – Journal of Educational Measurement, 1976
Special emphasis is given to the kinds of control that can be exercised over initial status, including the use of proxy input data. A rationale for the classification scheme is developed, based on (1) three one-shot, one cross-sectional, and two longitudinal data types and (2) two types of referencing: criterion referencing and norm referencing.…
Descriptors: Classification, Data Collection, Evaluation Methods, Methods
National Archives and Records Administration, 2009
The Secretary of Education (Secretary) establishes requirements, definitions, and approval criteria for the State Fiscal Stabilization Fund (Stabilization or SFSF) program. The Secretary may use one or more of these requirements, definitions, and approval criteria in awarding funds under this program in fiscal year (FY) 2010. These requirements,…
Descriptors: Educational Finance, Resource Allocation, Financial Support, Criteria
Saunders, Richard R.; Koplik, Kathy – AAESPH Review, 1975
Presented is a design for a data recording sheet which is claimed to be flexible, simple, time-saving , and convenient for classroom teachers to use. It is explained that scoring indicates criterion level, number and pattern of correct and incorrect responses, and a linear graph of the student's ongoing performance. (CL)
Descriptors: Data Collection, Educational Media, Evaluation Methods, General Education

Kelly, Karen M.; Siegel, Ellin B.; Allinder, Rose M. – Intervention in School and Clinic, 2001
This article presents a rationale and explanation of a personal profile assessment summary, a means of gathering, synthesizing, and conveying critical information about students with moderate and severe disabilities. A summary of information from a preliminary study on the use of personal profile summaries is included. (Contains references.)…
Descriptors: Data Collection, Elementary Secondary Education, Evaluation Methods, Portfolio Assessment
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