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Hidetsugu Suto; Qianran Wang – New Directions for Adult and Continuing Education, 2024
Japan, like many countries, is facing problems with an aging society, and lifelong learning is becoming more and more important. To provide older adults with the opportunity to enroll in lifelong learning programs, it is essential to offer suitable programs. However, designing learning programs for older adults is not easy because they may have…
Descriptors: Foreign Countries, Lifelong Learning, Older Adults, Educational Opportunities
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Jusuf Blegur; Sefri Hardiansyah – Journal of Education and Learning (EduLearn), 2024
Research and publications on differentiation instruction in various subjects have developed rapidly in the world. Unfortunately, this trend is not directly proportional to the subject of physical education, even though differentiation instruction is the latest learning trend that is based on student learning needs. This research aims to analyze…
Descriptors: Physical Education, Individualized Instruction, Educational Research, Bibliometrics
Kalena Cortes; Karen Kortecamp; Susanna Loeb; Carly Robinson – National Bureau of Economic Research, 2024
This paper presents the results from a randomized controlled trial of Chapter One, an early elementary reading tutoring program that embeds part-time tutors into the classroom to provide short bursts of 1:1 instruction. Eligible kindergarten students were randomly assigned to receive supplementary tutoring during the 2021-22 school year (N=818).…
Descriptors: Kindergarten, Tutoring, Individualized Instruction, African American Students
Jiayu Shao – ProQuest LLC, 2024
Recognizing the existing research gaps concerning learner characteristics in the realm of personalized learning in Chinese higher art education, this study initially analyzed prevailing patterns in personalized learning research and its current implementation in higher education through an extensive literature review. Subsequently, a quantitative…
Descriptors: Foreign Countries, Higher Education, College Students, Student Characteristics
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Smith, Bevan I.; Chimedza, Charles; Bührmann, Jacoba H. – Education and Information Technologies, 2022
Although using machine learning for predicting which students are at risk of failing a course is indeed valuable, how can we identify which characteristics of individual students contribute to their being At-Risk? By characterising individual At-Risk students we could potentially advise on specific interventions or ways to reduce their probability…
Descriptors: Individualized Instruction, At Risk Students, Intervention, Models
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McBride, Krista K. – Physics Teacher, 2023
It can be difficult to find ways to motivate students while teaching a physics course for non-physics students. Students come to class with many different attitudes and preconceptions, some of which are detrimental to their learning. As physics educators, we strive for student engagement and motivation in course material no matter what type of…
Descriptors: Physics, Nonmajors, Relevance (Education), Student Motivation
Seitz, Stacey L. – ProQuest LLC, 2023
MCL unclearly defined for the teachers asked to implement it in the classroom. This study sought to determine how teacher's implement MCL through the data collection of a mind map, which instructional components teachers used, the ideas that MCL has advanced and the idea that MCL made sense of. This qualitative case study analyzed six teacher's…
Descriptors: Individualized Instruction, Cognitive Mapping, Teacher Attitudes, Instructional Design
Ho, Eric Ming-Yin – ProQuest LLC, 2023
Personalized learning, which has the potential to raise student achievement, requires understanding the competencies of students. Visualizations can help provide this understanding. Jeon et al. (2021) presented a latent space model that creates interaction maps visualizing response patterns from item response data. My dissertation proposes…
Descriptors: Visual Aids, Individualized Instruction, Responses, Models
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Ana Paula Juliana Perin; Deivid Eive dos S. Silva; Natasha M. C. Valentim – Informatics in Education, 2023
In Education 4.0, a personalized learning process is expected, and that students are the protagonist. In this new education format, it is necessary to prepare students with the skills and competencies of the 21st-Century, such as teamwork, creativity, and autonomy. One of the ways to develop skills and competencies in students can be through block…
Descriptors: Programming, High School Students, Learning, Learning Processes
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Raf Vanderstraeten – Nordic Journal of Studies in Educational Policy, 2023
The genesis of the education system is linked with the rapid expansion of school education in the eighteenth and nineteenth century. The genesis of the education system therefore brought about a primary form of differentiation in the education system, viz. the differentiation between family and school. Family education and school education can be…
Descriptors: Public Schools, Home Schooling, Individualized Instruction, Education
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Lin Zhong – Interactive Learning Environments, 2023
While most educators regard personalized learning as beneficial for higher education and continuous research has demonstrated the effectiveness of personalized learning, a comprehensive understanding of how personalized learning has been designed and implemented in higher education is scarce. The purpose of this review study is to examine the…
Descriptors: Individualized Instruction, Higher Education, Instructional Design, Instructional Materials
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
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Klarisa I. Vorobyeva; Svetlana Belous; Natalia V. Savchenko; Lyudmila M. Smirnova; Svetlana A. Nikitina; Sergei P. Zhdanov – Contemporary Educational Technology, 2025
In this analysis, we review artificial intelligence (AI)-supported personalized learning (PL) systems, with an emphasis on pedagogical approaches and implementation challenges. We searched the Web of Science and Scopus databases. After the preliminary review, we examined 30 publications in detail. ChatGPT and machine learning technologies are…
Descriptors: Individualized Instruction, Artificial Intelligence, Intelligent Tutoring Systems, Ethics
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Angelos Bakogiannis – Journal of Learning Development in Higher Education, 2025
In a higher education (HE) landscape that is becoming increasingly internationalised and diversified, the importance of inclusive teaching practices, particularly in the context of English for Academic Purposes (EAP), is gaining growing international attention. While comprehensive frameworks and strategies are developed through educational…
Descriptors: English for Academic Purposes, Higher Education, Inclusion, Educational Policy
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Roneet Merkin – PRIMUS, 2024
This paper reports on a novel corequisite design and implementation for College Algebra at Florida International University. The corequisite course uses online, just-in-time, prerequisite assignments delivered on an open-educational platform. Students get help from near-peer learning assistants inside a math emporium environment. The course…
Descriptors: Required Courses, College Mathematics, Algebra, Mathematics Instruction
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