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Eysink, Tessa H. S.; Schildkamp, Kim – Educational Research, 2021
Background: To enable all students to reach their full potential, teachers have to adapt their instruction to students' varying needs. In order to do this, teachers need to engage in activities associated with formative assessment, as well as those associated with differentiation. However, both of these types of activities are, in themselves,…
Descriptors: Individualized Instruction, Formative Evaluation, Student Evaluation, Educational Practices
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
Eun Ok Baek; Romina Villaflor Wilson – International Journal of Adult Education and Technology, 2024
The emergence of generative AI technologies has provoked considerable debate among educators regarding their role in education. This study is an investigation of the benefits, disadvantages, and potential strategies for integrating generative AI in educational settings by analyzing societal impacts based on a literature review. We have surveyed…
Descriptors: Artificial Intelligence, Technology Uses in Education, Information Technology, Educational Strategies
Emma Shanahan; Seohyeon Choi; Jechun An; Bess Casey-Wilke; Seyma Birinci; Caroline Roberts; Emily Reno – Grantee Submission, 2025
Although data-based individualization (DBI) has positive effects on learning outcomes for students with learning difficulties, this framework can be difficult for teachers to implement due to its complexity and contextual barriers. The first aim of this synthesis was to investigate the effects of ongoing professional development (PD) support for…
Descriptors: Data Use, Individualized Instruction, Learning Problems, Students with Disabilities
Emma Shanahan; Seohyeon Choi; Jechun An; Bess Casey-Wilke; Seyma Birinci; Caroline Roberts; Emily Reno – Journal of Learning Disabilities, 2025
Although data-based individualization (DBI) has positive effects on learning outcomes for students with learning difficulties, this framework can be difficult for teachers to implement due to its complexity and contextual barriers. The first aim of this synthesis was to investigate the effects of ongoing professional development (PD) support for…
Descriptors: Data Use, Individualized Instruction, Learning Problems, Students with Disabilities
Fabienne van der Kleij; Pauline Taylor-Guy; Tanya Vaughan; Marijne Medhurst; Christina Rogers – Australian Council for Educational Research, 2023
This literature review outlines the evidence that underpins the development of a set of evidence-informed elaborations, or specific practices, that support student engagement and wellbeing across the 9 domains of the National School Improvement Tool (NSIT). These observable, measurable practices to support student engagement and wellbeing have…
Descriptors: Educational Improvement, Learner Engagement, Well Being, Academic Achievement
Heartley B. Huber; Erik W. Carter – Review Journal of Autism and Developmental Disorders, 2016
Although peer-mediated interventions have emerged as an evidence-based practice for students with autism spectrum disorder (ASD), little attention has focused on approaches for tailoring these interventions to meet individual students' unique needs. In this systematic literature review of 29 studies, we identified assessment procedures used to…
Descriptors: Intervention, Autism Spectrum Disorders, Evidence Based Practice, Peer Relationship

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