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Nurassyl Kerimbayev; Karlygash Adamova; Rustam Shadiev; Zehra Altinay – Smart Learning Environments, 2025
This review was conducted in order to determine the specific role of intelligent technologies in the individual learning experience. The research work included consider articles published between 2014 and 2024, found in Web of Science, Scopus, and ERIC databases, and selected among 933 ?articles on the topic. Materials were checked for compliance…
Descriptors: Intelligent Tutoring Systems, Artificial Intelligence, Computer Software, Databases
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Ana M. Hernández; Annette Daoud – TESOL Journal, 2025
This study examined bilingual preservice teachers' self-efficacy in the context of lesson differentiation for multilingual learners in Spanish. Thirty-six bilingual preservice teachers across three California State University programs participated in a quantitative methods study of lesson plan analysis. Findings showed that preservice teachers…
Descriptors: Preservice Teachers, Bilingualism, Self Efficacy, Individualized Instruction
Jeni Gotto; Oliver Grenham; Brian J. Kosena; Robert J. Marzano; Pamela Swanson – Solution Tree, 2025
Westminster Public Schools (WPS) in Colorado has embarked on a transformative journey toward competency-based education. Through strategic planning and continuous improvement, WPS developed a learner-centered system prioritizing personalized learning and student agency. Their road map--rooted in shared vision and second-order change--highlights…
Descriptors: Public Schools, Competency Based Education, Student Centered Learning, Individualized Instruction
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Rani Van Schoors; Jan Elen; Annelies Raes; Stefanie Vanbecelaere; Kamakshi Rajagopal; Fien Depaepe – Technology, Knowledge and Learning, 2025
The ever-evolving landscape of education is constantly intersecting with rapid advances in technology. Digital personalized learning (DPL)--learning which occurs in a digital learning environment that adapts to the individual learner--is believed to benefit both students and teachers. While DPL is believed to benefit students and teachers, there…
Descriptors: Teacher Attitudes, Electronic Learning, Individualized Instruction, Theory Practice Relationship
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Tao Gong; Lan Shuai; Robert J. Mislevy – Journal of Educational Measurement, 2024
The usual interpretation of the person and task variables in between-persons measurement models such as item response theory (IRT) is as attributes of persons and tasks, respectively. They can be viewed instead as ensemble descriptors of patterns of interactions among persons and situations that arise from sociocognitive complex adaptive system…
Descriptors: Cognitive Processes, Item Response Theory, Social Cognition, Individualized Instruction
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Timothy Gallagher; Bert Slof; Marieke van der Schaaf; Michaela Arztmann; Sofia Garcia Fracaro; Liesbeth Kester – Journal of Computer Assisted Learning, 2024
Background: Learning analytics dashboards are increasingly being used to communicate feedback to learners. However, little is known about learner preferences for dashboard designs and how they differ depending on the self-regulated learning (SRL) phases the dashboards are presented (i.e., forethought, performance, and self-reflection phases) and…
Descriptors: Learning Analytics, Experiential Learning, Individualized Instruction, Computer System Design
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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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