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Yang Shi; Robin Schmucker; Keith Tran; John Bacher; Kenneth Koedinger; Thomas Price; Min Chi; Tiffany Barnes – Journal of Educational Data Mining, 2024
Understanding students' learning of knowledge components (KCs) is an important educational data mining task and enables many educational applications. However, in the domain of computing education, where program exercises require students to practice many KCs simultaneously, it is a challenge to attribute their errors to specific KCs and,…
Descriptors: Programming Languages, Undergraduate Students, Learning Processes, Teaching Models
National Forum on Education Statistics, 2021
"The Forum Guide to Strategies for Education Data Collection and Reporting (SEDCAR)" was created to provide timely and useful best practices for education agencies that are interested in designing and implementing a strategy for data collection and reporting, focusing on these as key elements of the larger data process. It builds upon…
Descriptors: Data Collection, Educational Research, Statistical Data, Data Analysis
Michelle Hock; Tonya R. Moon; Coby V. Meyers – Journal of Teacher Education, 2025
Because data-informed decision-making (DIDM) can help teachers meet diverse learners' needs (van Geel et al., 2016), educator preparation programs (EPPs) must ensure that preservice teachers (PSTs) develop the data literacy skills needed for effective data use. However, little is known about the ways in which EPPs work towards building PSTs' data…
Descriptors: Preservice Teachers, Data Use, Decision Making, Preservice Teacher Education
Juan D’Brot; W. Chris Brandt – Region 5 Comprehensive Center, 2024
In today's educational landscape, state and local educational agencies (SEAs and LEAs) often experience challenges connecting large-scale accountability data with actual school improvement initiatives. These challenges tend to be rooted in incoherent design and use of data systems for continuous improvement. As we aim to support SEAs in…
Descriptors: Educational Improvement, Data Collection, State Departments of Education, School Districts
Bryant, Rebecca; Fransen, Jan; de Castro, Pablo; Helmstutler, Brenna; Scherer, David – OCLC Online Computer Library Center, Inc., 2021
Research information management (RIM) is a rapidly growing area of investment in US research universities. RIM systems that support the collection and use of research outputs metadata have been in place for many years. Globally, the RIM ecosystem is quite mature in locales where national research assessment exercises like the United Kingdom's…
Descriptors: Research Universities, Information Management, Metadata, Data Use
Bryant, Rebecca; Fransen, Jan; de Castro, Pablo; Helmstutler, Brenna; Scherer, David – OCLC Online Computer Library Center, Inc., 2021
Research Information Management (RIM) is a rapidly growing area of investment in US research universities, comprised of a variety of use cases, stakeholders, and products. This growth has been characteristically decentralized, resulting in silos, multiple systems, and frequent duplication of efforts at many institutions. This report is a two-part…
Descriptors: Research Universities, Information Management, Metadata, Data Use
Debnam, Katrina J.; Edwards, Kelly; Maeng, Jennifer L.; Cornell, Dewey – Journal of School Leadership, 2022
National interest in using school climate as an accountability measure makes it important to understand how school leaders view and make use of school climate data. The purpose of this study was to investigate how school and district administrators use climate data in Virginia, where a statewide school climate survey is annually administered.…
Descriptors: Leadership, Administrator Attitudes, Data Use, Educational Environment
Romano, Richard M.; D'Amico, Mark M. – Association for Institutional Research, 2021
A commonly used metric for measuring college costs, drawn from data in the Integrated Postsecondary Education Data System (IPEDS), is expenditure per full-time equivalent (FTE) student. This article discusses an error in this per FTE calculation when using IPEDS data, especially with regard to community colleges. The problem is that expenditures…
Descriptors: Noncredit Courses, Enrollment, Community Colleges, Institutional Characteristics
Hunt-Isaak, Noah; Cherniavsky, Peter; Snyder, Mark; Rangwala, Huzefa – International Educational Data Mining Society, 2020
National failure rates seen in undergraduate introductory CS courses are quite high. In this paper, we develop a predictive model for student in-class performance in an introductory CS course. The model can serve as an early warning system, flagging struggling students who might benefit from additional support. We use a variety of features from…
Descriptors: Textbooks, Surveys, Grade Prediction, Undergraduate Students
Hutton, Amy – Strategic Enrollment Management Quarterly, 2021
Strategy and research are essential parts of strategic enrollment management (SEM), yet little information exists regarding how to use research and predictive analytics for effective strategy. It is often easier to react to what is happening in the moment, rather than be proactive in predicting the future or developing long-term plans. This…
Descriptors: Enrollment Management, Strategic Planning, Educational Research, Prediction
Jessica R. Toste; Marissa J. Filderman; Nathan H. Clemens; Erica Fry – Journal of Learning Disabilities, 2025
Data-based instruction (DBI) is a process in which teachers use progress data to make ongoing instructional decisions for students with learning disabilities. Curriculum-based measurement (CBM) is a common form of progress monitoring, and CBM data are placed on a graph to guide decision-making. Despite the central role that graph interpretation…
Descriptors: Preservice Teachers, Data Use, Decision Making, Progress Monitoring
Allison F. Gilmour; Li Feng; Roddy Theobald – Remedial and Special Education, 2025
Special educator shortages have threatened the provision of services U.S. to students with disabilities since the passage of the Education for All Handicapped Children Act in 1975, since reauthorized as the Individuals with Disabilities Education Act. We conducted a systematic review of studies that used administrative data to study the special…
Descriptors: Special Education Teachers, Data Use, Educational Research, Teacher Distribution
Dukes, Dominique – MDRC, 2021
The Evidence to Action project (2019-2021), led by MDRC and the State Higher Education Executive Officers Association (SHEEO) and supported by Arnold Ventures, initiated a body of work designed to disentangle the barriers that exist between research and state-level higher education policy and partnered with state higher education agencies to…
Descriptors: State Policy, Educational Policy, Higher Education, Educational Research
Müller, Eve; Wood, Caitlin; Cannon, Lynn; Childress, Deb – Focus on Autism and Other Developmental Disabilities, 2023
This pilot study examined (a) the perceived barriers to creating high-quality social and emotional learning (SEL) IEP goals for autistic students without intellectual disabilities, and (b) the impact of using a data-driven SEL IEP goal builder--a key component of the Ivymount Social Cognition Instructional Package (IvySCIP)--on the quality of SEL…
Descriptors: Autism Spectrum Disorders, Students with Disabilities, Barriers, Social Emotional Learning
State Council of Higher Education for Virginia, 2019
"The Virginia Plan for Higher Education" articulates the objective that the Commonwealth will be the best-educated state by 2030. To achieve this objective, Virginia not only must increase educational-attainment rates, but also close the gaps in the differing rates of attainment that exist across its population and its regions. The…
Descriptors: Educational Attainment, Higher Education, Data Use, State Policy
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