NotesFAQContact Us
Collection
Advanced
Search Tips
What Works Clearinghouse Rating
Showing 1 to 15 of 246 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
Direct linkDirect link
Cohen, Jefna M. – Learning Professional, 2023
How does one overcome the challenges to finding time for meaningful professional learning? The authors asked seven experts in the field, and these practitioners offer powerful strategies for making better use of educator time. An example from Illinois centers student data in school systems as an essential component of a school's overall commitment…
Descriptors: Time on Task, Faculty Development, Educational Change, Data Use
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Putman, Hannah; Peske, Heather – State Education Standard, 2022
With three school years touched by the pandemic so far, the extent of the damage to this generation of students is coming into focus. Three concerns are top of mind for state and district leaders: making up for disrupted learning, ensuring that schools have enough quality teachers and staff to lead this work, and building a diverse teacher…
Descriptors: Data Use, Standards, Teacher Certification, Educational Administration
Peer reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
Direct linkDirect link
Brannegan, Andrew; Takahashi, Sola – Learning Professional, 2023
Educators have long been awash in a sea of standardized test score data, with the understanding that their engagement with these data will lead to improvement in teaching and learning. But, in practice, these data have often been too infrequent, too lagging, and too distant from day-to-day practice to inform actionable next steps. To improve…
Descriptors: Standardized Tests, Data Use, Educational Improvement, Data Analysis
Peer reviewed Peer reviewed
Direct linkDirect link
Burgard, Tanja; Bosnjak, Michael; Studtrucker, Robert – Research Synthesis Methods, 2022
To enable optimal decision-making based on the best evidence available, open syntheses are called for. To make data accessible and comprehensible even for decision-makers without proficient knowledge in meta-analysis, a graphical user interface (GUI) provides flexible data visualizations including interpretation aids. Moreover, due to a growing…
Descriptors: Psychological Studies, Meta Analysis, Synthesis, Metadata
Peer reviewed Peer reviewed
PDF on ERIC Download full text
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
Thompson, Greg; Rutkowski, Leslie; Rutkowski, David – Phi Delta Kappan, 2023
Those asked to make valid decisions with data don't have the technical knowledge to understand nuance around data quality, assessment aims, and statistical limitations that influence how they should interpret the data. This reality is what Greg Thompson, Leslie Rutkowski, and David Rutkowski call the validity paradox. Educators can surmount this…
Descriptors: Validity, Decision Making, Data Use, Educational Assessment
Peer reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Boughton, Heather; Kerr, Sara – State Education Standard, 2023
Evidence-based policymaking can transform the delivery of education services, restore public trust in schools, and improve outcomes for students. It can cut through the noise of political and cultural divisions and give decision makers clarity on how to prioritize the use of limited resources. And it can help build a shared understanding of where…
Descriptors: Evidence Based Practice, Educational Policy, Policy Formation, State Boards of Education
Peer reviewed Peer reviewed
Direct linkDirect link
Camm, Jeffrey D.; McCray, Gordon E.; Roehm, Michelle L. – Decision Sciences Journal of Innovative Education, 2023
Based on our experience developing and delivering a highly successful data visualization course within a Master of Science in Business Analytics program, we present a taxonomy for data visualization courses and recommend content and pedagogical features for each type of data visualization course therein. We also discuss the interdependence between…
Descriptors: Visual Aids, Masters Programs, Business Administration Education, Data Use
Peer reviewed Peer reviewed
Direct linkDirect link
Grosse, Scott D.; Nichols, Phyllis; Nyarko, Kwame; Maenner, Matthew; Danielson, Melissa L.; Shea, Lindsay – Journal of Autism and Developmental Disorders, 2022
Strengthening systems of care to meet the needs of individuals with autism spectrum disorder (ASD) is of growing importance. Administrative data provide advantages for research and planning purposes, including large sample sizes and the ability to identify enrollment in insurance coverage and service utilization of individuals with ASD.…
Descriptors: Autism, Pervasive Developmental Disorders, Data Use, Databases
Previous Page | Next Page ยป
Pages: 1  |  2  |  3  |  4  |  5  |  6  |  7  |  8  |  9  |  10  |  11  |  ...  |  17