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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
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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
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Ling Wang; Guochu Liang – International Journal of Web-Based Learning and Teaching Technologies, 2025
The rapid development of online education has underscored the necessity of data-driven teaching functions for enhancing teaching quality and efficiency. This paper investigates the role of data-driven approaches in online education, with a particular focus on the practical application of data for evaluating learning outcomes. It highlights the…
Descriptors: Data Use, Educational Quality, Online Courses, Distance Education
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Vykopal, Jan; Seda, Pavel; Svabensky, Valdemar; Celeda, Pavel – IEEE Transactions on Learning Technologies, 2023
Hands-on computing education requires a realistic learning environment that enables students to gain and deepen their skills. Available learning environments, including virtual and physical laboratories, provide students with real-world computer systems but rarely adapt the learning environment to individual students of various proficiency and…
Descriptors: Students, Educational Technology, Computer Assisted Instruction, Media Adaptation
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Hongyu Xie; He Xiao; Yu Hao – International Journal of Web-Based Learning and Teaching Technologies, 2024
Modern e-learning system is a representative service form in innovative service industry. This paper designs a personalized service domain system, optimizes various parameters and can be applied to different education quality evaluation, and proposes a decision tree recommendation algorithm. Information gain is carried out through many existing…
Descriptors: Artificial Intelligence, Electronic Learning, Individualized Instruction, Models
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Kristen L. McMaster; Erica S. Lembke; Emma Shanahan; Seohyeon Choi; Jechun An; Christopher Schatschneider; McKinzie D. Duesenberg-Marshall; Seyma Birinci; Elizabeth McCollom; Carol Garman; Kim Moore – Journal of Learning Disabilities, 2025
In a multiyear, multisite, randomized control trial, we examined the effects of comprehensive professional development designed to support teachers' data-based instruction (DBI) for students with intensive early writing needs. Teachers (N = 154; primarily special educators or intervention specialists) were assigned randomly to a treatment group (n…
Descriptors: Data Use, Individualized Instruction, Writing Instruction, Special Needs Students
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Sarah R. Powell; Samantha E. Bos; Sarah G. King; Leanne Ketterlin-Geller; Erica S. Lembke – TEACHING Exceptional Children, 2024
Data-based individualization (DBI) is a framework that allows educators to make timely and informed decisions about student progress in academics or behavior. In this article, we focus on the DBI framework as applied to math intervention within a tiered support model for students experiencing math difficulty. We review how DBI starts with an…
Descriptors: Middle School Mathematics, Middle School Students, Middle School Teachers, Mathematics Instruction
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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
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Tetzlaff, Leonard; Schmiedek, Florian; Brod, Garvin – Educational Psychology Review, 2021
Personalized education--the systematic adaptation of instruction to individual learners--has been a long-striven goal. We review research on personalized education that has been conducted in the laboratory, in the classroom, and in digital learning environments. Across all learning environments, we find that personalization is most successful when…
Descriptors: Individualized Instruction, Instructional Effectiveness, Instructional Design, Student Characteristics
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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
Regan, Kelley; Evmenova, Anya S.; Hutchison, Amy; Day, Jamie; Stephens, Madelyn; Verbiest, Courtney; Gafurov, Boris – TEACHING Exceptional Children, 2022
The process of analyzing student data to determine an appropriate instructional decision is crucial for student academic growth. This article details how teachers can make data-driven decisions to carefully design writing instruction. Steps are presented for teachers to follow throughout the data driven decision-making process in order to meet…
Descriptors: Writing Instruction, Decision Making, Essays, Data Analysis
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Huimin Yang – International Journal of Web-Based Learning and Teaching Technologies, 2025
In view of the traditional teaching mode, this study focuses on the application of big data in personalized English teaching in colleges and universities. It aims at improving the teaching effect by using big data. By combining personalized teaching and big data theory, this paper analyzes the current situation of college English teaching,…
Descriptors: Data Use, Second Language Instruction, Teaching Methods, English (Second Language)
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Haering, Marlo; Bano, Muneera; Zowghi, Didar; Kearney, Matthew; Maalej, Walid – IEEE Transactions on Learning Technologies, 2021
With the vast number of apps and the complexity of their features, it is becoming challenging for teachers to select a suitable learning app for their courses. Several evaluation frameworks have been proposed in the literature to assist teachers with this selection. The iPAC framework is a well-established mobile learning framework highlighting…
Descriptors: Automation, Courseware, Computer Software Evaluation, Computer Software Selection
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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
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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
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