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Sara A. Hart; Christopher Schatschneider; Tara Reynolds; Favenzio Calvo – Journal of Learning Disabilities, 2024
The purpose of this invited paper is to show the learning disabilities field what LDbase is, why it's important for the field, what it offers the field, and examples of how you can leverage LDbase in your own work.
Descriptors: Learning Disabilities, Databases, Information Storage, Access to Information
Susan T. Hibbard; Jeanne McClure; Shaun Kellogg – New Directions for Teaching and Learning, 2024
This chapter introduces the learning analytics as a catalyst to transform data utilization and bolster support for the scholarship of teaching and learning.
Descriptors: Learning Analytics, Allied Health Occupations Education, Data Use, Scholarship
Tochukwu Okoye – Learning Professional, 2024
Data is ubiquitous and inseparable from the human experience. It constantly informs and transforms interactions, decisions, and understanding. If the total amount of all the data created daily was printed on paper, it would fill a library the size of 110 Libraries of Congress. As a senior research consultant for an education market research and…
Descriptors: Elementary Secondary Education, Data Use, Inclusion, Educational Improvement
National Assessment of Educational Progress (NAEP), 2024
The National Assessment of Educational Progress (NAEP) is an integral measure of academic progress across the nation and over time. It is the largest nationally representative and continuing assessment of what our nation's students know and can do in various subjects, such as civics, mathematics, reading, and U.S. history. The program also…
Descriptors: National Competency Tests, Preadolescents, Adolescents, Mathematics Achievement
Siobhan Reilley – Impacting Education: Journal on Transforming Professional Practice, 2024
The purpose of this essay is to discuss the impact of the EdD experience on one teacher's understanding of data and research. From a first-person narrative, the author shares how learning to collect and analyze qualitative data has the potential to change the way teachers can engage with "data-driven decision making" in a high school…
Descriptors: Data Use, Data Collection, Data Analysis, Teacher Leadership
Colorado Department of Higher Education, 2024
In the 2023 report "Colorado's Longitudinal Data Landscape. Report to the Education Committees of the Colorado House of Representatives and the Colorado Senate. Statute: 23-1-141," the Colorado Department of Higher Education (CDHE) provided a detailed overview of Colorado's long history of efforts to support more connected, longitudinal…
Descriptors: Data Collection, State Legislation, Educational Legislation, Best Practices
Soyoung Park; Pamela M. Stecker; Sarah R. Powell – Intervention in School and Clinic, 2024
This article provides teachers with a toolkit for assessing students in the context of data-based individualization (DBI) in mathematics. Assessing students is a critical component of DBI because it provides teachers with information about what they may need to modify in their instructional programs. In this article, we provide teachers with…
Descriptors: Student Evaluation, Individualized Instruction, Mathematics Instruction, Progress Monitoring
Rebecca Croxton; Bradley Coverdale; Amy Svirsky – Assessment Update, 2024
The Grand Challenges for Assessment in Higher Education project is a collaborative effort of 10 endorsing organizations and over 400 volunteers to increase the extent to which assessment (1) supports equity; (2) is visible, actionable, and drives innovation; and (3) guides rapid improvements in pedagogy (Singer-Freeman and Robinson 2020). Several…
Descriptors: Data, Visualization, Data Use, Educational Assessment
Data Quality Campaign, 2024
Recent data from statewide assessments, scores on the National Assessment of Educational Progress (NAEP), and college remediation needs show that an increasing number of K-12 students are not performing at grade level. As schools look to support these students' learning, some districts are turning to a proven strategy for identifying the students…
Descriptors: National Competency Tests, Academic Achievement, Elementary Secondary Education, At Risk Students
Jessica Arnold; Julie Webb – WestEd, 2024
While there are many different types of education data, policymakers and education leaders often place heavy emphasis on data from large-scale quantitative measures, such as annual state assessments. But data from these sources alone do not provide a complete picture of learning and are often not well suited to informing improvements at the local…
Descriptors: Data Use, Measurement, Educational Improvement, Outcomes of Education
Marissa J. Filderman; Samantha A. Gesel – TEACHING Exceptional Children, 2024
Data-based decision making (DBDM) is a process of using student data to inform instructional decisions and intensify intervention for students whose data indicate inadequate academic and behavioral progress. Data teams, an important structure for DBDM, are a collaborative group of school faculty who meet to systematically analyze student data,…
Descriptors: Evidence Based Practice, Decision Making, Data Use, Intervention
Sarah Hensley; Janet Fox; Missy Cummins; Meggan Franks; Marianne Bird; Cindy Wells; JoLynn Miller – Journal of Extension, 2024
Cooperative Extension professionals utilize proven qualitative techniques to collect and analyze information to make data-driven decisions that guide program direction and determine impact. While the process may not always look the same, it is indeed essential to ensure findings are credible and reflective of the data. A codebook is a valuable…
Descriptors: Youth Clubs, Nonprofit Organizations, Extension Education, Data Use
Louise Gwenneth Phillips; M. Obaidul Hamid; Vicente Reyes; Ian Hardy – Educational Review, 2024
We live in a data-driven world. The voluminous scale of data gathered can lead to diminished consciousness of ethics whilst economic interests are prioritised. Across recent decades education has come to be heavily data driven and datafied. We have witnessed the dehumanising and increased labour impacts of school datafication. In search for…
Descriptors: Foreign Countries, Educational Researchers, Data, Data Use
Alexandra M. Pierce; Melissa A. Collier-Meek; Thea R. Bucherbeam; Lisa M. H. Sanetti – Communique, 2024
Students cannot experience the full potential benefits of an intervention unless they are receiving the intervention. This is the second installment in a three-part series on intervention fidelity designed to highlight the importance of ensuring classroom supports are implemented as intended. This article provides guidance related to measuring and…
Descriptors: Data Use, Decision Making, Intervention, Fidelity
Region 1 Comprehensive Center, 2024
The Maine Department of Education (MDOE) wanted to better understand if their current educator workforce data collection could help them quantify supply and demand for educators in the state. They also wanted to understand if local school administrative units collected data that could inform future efforts to understand educator vacancies to…
Descriptors: School Administration, Teacher Characteristics, Labor Force, Data Collection