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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
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
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
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
Maria Sargent – Brookes Publishing Company, 2025
How do young children learn, and what do educators need to know and do to teach them? Covering the full birth-8 early childhood age range, this introductory text delivers up-to-date answers through a unique lens: a deep focus on the neurological foundations of developmentally appropriate practices. Preservice and inservice educators will explore…
Descriptors: Young Children, Developmentally Appropriate Practices, Neurology, Child Development
Treatment Integrity of Primary (Tier 1) Prevention Efforts in Tiered Systems: Mapping the Literature
Buckman, Mark Mathew; Lane, Kathleen Lynne; Common, Eric Alan; Royer, David James; Oakes, Wendy Peia; Allen, Grant Edmund; Lane, Katie Scarlett; Brunsting, Nelson C. – Education and Treatment of Children, 2021
Treatment integrity is an important component of rigorous educational research. Information about the extent to which an intervention was implemented as planned provides necessary context for interpreting student outcomes. In the context of increasing use of tiered systems in schools, treatment integrity takes on additional practical importance.…
Descriptors: Intervention, Student Needs, Program Effectiveness, Prevention
EdTrust-West, 2025
As California State University (CSU) launches its Pregnant and Parenting Students Initiative to increase graduation rates for parenting students at its campuses and works to implement the Greater Accessibility, Information, Notice, and Support (GAINS) for Student Parents Act, an exciting window of opportunity has opened for student voice to inform…
Descriptors: Child Rearing, Parents, College Students, Graduation Rate
Nancy Montes; Fernanda Luna – UNESCO International Institute for Educational Planning, 2024
This article characterizes and reflects on the possible uses of early warning systems (hereafter, EWS) in the region as effective tools to support educational pathways, whenever they identify risks of dropout, difficulties for the achievement of substantive learning, and the possibility of organizing specific actions. This article was developed in…
Descriptors: Data Collection, Data Use, At Risk Students, Foreign Countries
Brann, Kristy L.; Naser, Shereen C.; Clough, Mac – Journal of Educational and Psychological Consultation, 2023
The current study describes the process of a participatory consultation framework, the Participatory Culture Specific Intervention Model (PCSIM), to plan and implement a data-based decision-making framework. The framework integrates proactive and systematic identification of emotional and behavioral needs as well as cognitive psychology techniques…
Descriptors: Consultation Programs, Data Use, Decision Making, Intervention
Ma, Zijie; Travers, Jason C. – Intervention in School and Clinic, 2022
Special education and related professionals often understand the importance of adhering to intervention procedures (i.e., fidelity), but may be less familiar with concepts of intervention intensity. In some cases, professionals may correctly apply an intervention, but with insufficient intensity. This can result in an intervention failing to…
Descriptors: Students with Disabilities, Autism, Pervasive Developmental Disorders, Intervention
De Silva, Liyanachchi Mahesha Harshani; Chounta, Irene-Angelica; Rodríguez-Triana, María Jesús; Roa, Eric Roldan; Gramberg, Anna; Valk, Aune – Journal of Learning Analytics, 2022
Although the number of students in higher education institutions (HEIs) has increased over the past two decades, it is far from assured that all students will gain an academic degree. To that end, institutional analytics (IA) can offer insights to support strategic planning with the aim of reducing dropout and therefore of minimizing its negative…
Descriptors: College Students, Dropouts, Dropout Prevention, Data Analysis
Dunlap, Jill; Palmer, Iris; Wesley, Alexa – New America, 2021
The use of student data to inform decision-making and communication is still evolving in higher education. Often missing from campus conversations about use of student data are student voices about their preferences and needs. NASPA and New America engaged in a joint research effort to better understand student perceptions of data use within…
Descriptors: Data Use, Student Attitudes, Decision Making, Trust (Psychology)
Kittelman, Angus; Storie, Sloan; Horner, Robert H.; Machalicek, Wendy – Center on Positive Behavioral Interventions and Supports, 2020
Young students starting school for the first time (e.g., kindergarteners) often benefit from more than typical intensity of behavioral support. Learning new social expectations, routines, and interaction patterns can be daunting. This is an important concern for schools implementing positive behavioral interventions and supports (PBIS). Learning a…
Descriptors: Behavior Modification, Positive Behavior Supports, Intervention, Kindergarten
Wahman, Charis L.; Light-Shriner, Cheryl L.; Pizzella, Danielle M. – Young Exceptional Children, 2022
Reported percentages of young children who engage in challenging behavior is estimated between 10% and 20%. This percentage is even greater for children with disabilities. Not surprisingly, when young children with challenging behavior do not receive services and supports early on, they can experience negative social and emotional outcomes long…
Descriptors: Behavior Problems, Students with Disabilities, Special Education Teachers, Teacher Collaboration
Bohanon, Hank; Love, Lisa Caputo; Morrissey, Kelly – Eye on Education, 2020
Accessibly written and specifically designed for secondary schools, "Implementing Systematic Interventions" provides you with the tools you need to successfully organize for and smoothly implement schoolwide intervention strategies. Discover how to: (1) organize administrative support and leadership teams; (2) create effective…
Descriptors: Secondary Schools, Teamwork, Intervention, Leadership Role
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