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Zachary Weingarten; Amy Peterson; Kyle Allen – National Center on Intensive Intervention, 2023
Readiness for change is an important factor in successful implementation and scale-up of a new practice or program in schools. The process of assessing and developing readiness for change is a key feature of the Exploration Stage, which is the first of four implementation stages identified by the Active Implementation Research Network. Data-based…
Descriptors: Data Use, Intervention, Individualized Instruction, Student Needs
Christothea Herodotou; Sagun Shrestha; Catherine Comfort; Heshan Andrews; Paul Mulholland; Vaclav Bayer; Claire Maguire; John Lee; Miriam Fernandez – Journal of Learning Analytics, 2025
In this paper, we explore the design of a student-facing dashboard for online and distance learning with a focus on capturing and addressing specific learning needs. A participatory process involving 20 students was employed, which included a screening questionnaire and focus group discussions. The selection of data points to be displayed on the…
Descriptors: Electronic Learning, Distance Education, Student Attitudes, Educational Technology
M. B. Saikrishna – On the Horizon, 2025
Purpose: The purpose of this paper is to investigate how educators perceive and adapt their roles in the face of changes in technology-driven learning environments. The Gioia methodology explores how educators enable adaptive learning, broaden their pedagogical practice and promote cultural inclusivity to educate diverse students.…
Descriptors: Teacher Attitudes, Educational Technology, Technology Uses in Education, Teacher Role
Amelia Parnell – Journal of Postsecondary Student Success, 2022
Data-informed decision-making is no longer an optional or occasional practice, as higher education professionals now routinely respond to calls for accountability by providing data to show how their work impacts students. Institutions are operating with a culture that, at a minimum, includes the use of descriptive and diagnostic analyses to assess…
Descriptors: Student Needs, Data Use, Prediction, Data Analysis
Melissa A. Gallagher; Jennifer E. Scholla – Mathematics Teacher: Learning and Teaching PK-12, 2025
Adaptive teachers use student data to guide instruction. Learn about using an anecdotal record form to support adaptive teaching. In this article, the authors describe how teachers can use learning trajectories to make adaptive decisions to meet the needs of their students. They provide an example using the U .S. Math Recovery Council's learning…
Descriptors: Mathematics Instruction, Learning Trajectories, Developmentally Appropriate Practices, Student Needs
Zachary Weingarten; Paul K. Steinle – National Center on Intensive Intervention, 2023
Data-based individualization (DBI) is a systematic approach to intensifying and individualizing interventions for students who require more support. Diagnostic data represent the third step in the DBI process. When progress monitoring data indicate that a student is not making adequate progress in an intervention, educators use diagnostic data to…
Descriptors: Data Use, Student Needs, Intervention, Individualized Instruction
Fazlul, Ishtiaque; Koedel, Cory; Parsons, Eric – Education Next, 2023
Among the 50 states, 44 use free and reduced-price lunch enrollment to identify low-income students. These data are also commonly used to allocate federal, state, and local funding to schools serving low-income children. School and district poverty rates, as determined by free and reduced-price lunch enrollment, additionally feature prominently in…
Descriptors: Lunch Programs, Student Needs, Identification, Poverty
Jessica Arnold; Susan Hayes; Elizabeth Zagata – WestEd, 2025
Despite decades of tenacious advocacy and improvement efforts to expand and enshrine rights for students with disabilities, many students with individualized education programs (IEPs) still lack access to high-quality, effective learning opportunities. This can be due to a range of factors, including low expectations, exclusion from general…
Descriptors: Students with Disabilities, Equal Education, Student Evaluation, Evaluation Methods
Data Quality Campaign, 2022
For decades, schools nationwide have collected household income data to identify those eligible for free and reduced-price lunch programs. State leaders have long used this information as a proxy for student economic disadvantage--yet this data is insufficient to understand and address students' needs. Measures based on FRL data lack critical…
Descriptors: State Policy, Student Needs, Measurement Techniques, Disadvantaged Youth
Botvin, Maya; Hershkovitz, Arnon; Forkosh-Baruch, Alona – Education and Information Technologies, 2023
Decision-making is key for teaching, with informed decisions promoting students and teachers most effectively. In this study, we explored data-driven decision-making processes of K-12 teachers (N = 302) at times of emergency remote teaching, as experienced during the COVID-19 pandemic outbreak in Israel. Using both quantitative and qualitative…
Descriptors: Foreign Countries, COVID-19, Pandemics, Emergency Programs
Maria L. Hugh; Kathleen Tuck; Alana Schnitz; Lisa Didion; Andrea Nelson – Journal of Special Education Preparation, 2024
Improving outcomes for young children with high-intensity needs requires a high-quality workforce trained in equitable, intensive, individualized instructional practices and supports incorporating culturally and linguistically responsive evidence-based practices (Gunn, 2020) and developmentally appropriate practices (DAP; NAEYC, 2021) Nationally…
Descriptors: Special Education, Early Childhood Education, Intervention, Preservice Teacher Education
Kristopher Hawk Yeager; Malarie E. Deardorff; Belkis Choiseul-Praslin; Wendy R. Mitchell; Courtney Tennell; Brooki Beasley – Journal of the American Academy of Special Education Professionals, 2024
Educational professionals (e.g., special educators, general educators, administrators, related service providers) play an important role in promoting engagement with parents during the development of individualized education programs (IEPs). For this study, we conducted semi-structured interviews to evaluate parents' (n = 16) perceptions of…
Descriptors: Parent School Relationship, Cooperative Planning, Teacher Role, Administrator Role
Lindsay Ruhter; Meagan Karvonen – Remedial and Special Education, 2024
There is evidence that data-based decision-making (DBDM) can improve outcomes for a wide range of students. However, less is known about how special education teachers are trained to use data to inform instruction that targets academic progress for students with extensive support needs (ESN). The purpose of this systematic literature review was to…
Descriptors: Student Needs, Decision Making, Data Use, Outcomes of Education
Rosemary Vellar; Boris Handal; Sean Kearney; Chris Forlin – Issues in Educational Research, 2024
Evidence based decision making is essential for enabling improved student learning. Teacher motivations and beliefs about the types and use of data are critical determinants of decision making. Our research explored the types of data teachers use and consider valuable when measuring improvement in student learning. Findings from 294 teachers from…
Descriptors: Catholic Schools, Elementary Secondary Education, Learning Analytics, Student Needs
Greer, Lucas; Steiner, Elizabeth D. – RAND Corporation, 2023
The urgent need to help students -- and particularly students who are Black or Hispanic -- recover from the negative effects of the coronavirus disease 2019 (COVID-19) pandemic on mathematics learning and access equitable opportunities in mathematics will require that teachers use every available tool to diagnose student learning needs and…
Descriptors: Mathematics Teachers, Data Use, Student Characteristics, Access to Information

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