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Melly Preston; Pearl Subban; Muhamad Nanang Suprayogi; Annisa Nanda Liyani; Andrea Prita Purnama Ratri – Journal of Education and Learning (EduLearn), 2025
The increasing diversity of students in higher education presents numerous advantages for the sector, yet it also imposes substantial challenges for educators. This study explored the experiences of five academics across two countries as they strive to implement differentiated instruction (DI) to accommodate the diverse needs of students. The…
Descriptors: Individualized Instruction, College Instruction, Higher Education, College Faculty
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Ángela María Méndez-Vargas; Andrés Chiappe; María Soledad Ramirez-Montoya; Diego Fernando Becerra Rodríguez – Cambridge Journal of Education, 2025
This conceptual literature review explores the evolution of personalised pearning (PL) through an analysis of 39 research articles indexed in Scopus and Web of Science to delve into its main conceptualisations, trends and challenges. The review was carried out by applying the guidelines of the PRISMA statement to research articles published in…
Descriptors: Literature Reviews, Meta Analysis, Individualized Instruction, Educational Trends
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Dannie Wammes; Liesbeth Kester; Bert Slof – International Journal of Technology and Design Education, 2025
Hands-on activities promote interest in engineering, but their use in primary education is under pressure due to doubts about their effect on learning. Based on the Challenge Point Framework, we hypothesized that an adaptive approach in which a pupil starts with tasks at its level of prior knowledge would raise the learning results of hands-on…
Descriptors: Difficulty Level, Prior Learning, Elementary School Students, Individualized Instruction
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Daniel Lupiya Mpolomoka – Pedagogical Research, 2025
Overview: This systematic review explores the utilization of artificial intelligence (AI) for assessment, grading, and feedback in higher education. The review aims to establish how AI technologies enhance efficiency, scalability, and personalized learning experiences in educational settings, while addressing associated challenges that arise due…
Descriptors: Artificial Intelligence, Higher Education, Evaluation Methods, Literature Reviews
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Frank Stinar; HaeJin Lee; Clara Belitz; Nidhi Nasiar; Stephen E. Fancsali; Steve Ritter; Husni Almoubayyed; Ryan S. Baker; Jaclyn Ocumpaugh; Nigel Bosch – International Educational Data Mining Society, 2025
Students' reading ability affects their outcomes in learning software even outside of reading education, such as in math education, which can result in unexpected and inequitable outcomes. We analyze an adaptive learning software using Bayesian Knowledge Tracing (BKT) to understand how the fairness of the software is impacted when reading ability…
Descriptors: Mathematics Education, Bayesian Statistics, Reading Ability, Information Management
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Pearl Subban; Muhamad Nanang Suprayogi; Melly Preston; Annisa Nanda Liyani; Andrea Prita Purnama Ratri – Asia-Pacific Education Researcher, 2025
Differentiated instruction is an effective means of addressing student diversity, and is increasingly being adopted by educators within the higher education sector. However, the global pandemic and changes to content delivery have altered the educational landscape. Hybridised delivery has resulted in the need for more innovative and contemporary…
Descriptors: Individualized Instruction, Educational Benefits, Teacher Attitudes, College Faculty
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Fang Xu; Nicholas A. Gage; Holly B. Lane; Valentina Contesse; Gentry O'Steen; Florence Bason – Reading & Writing Quarterly, 2025
Student engagement during reading instruction, including during small group and individualized intensive reading instruction, is critical for student success. If students are not engaged with instruction, they are not learning. This study examined student reading engagement during individualized intensive literacy tutoring in a summer reading…
Descriptors: Learner Engagement, Elementary School Students, Grade 1, Grade 2
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Khaldi, Amina; Bouzidi, Rokia; Nader, Fahima – Smart Learning Environments, 2023
In recent years, university teaching methods have evolved and almost all higher education institutions use e-learning platforms to deliver courses and learning activities. However, these digital learning environments present significant dropout and low completion rates. This is primarily due to the lack of student motivation and engagement.…
Descriptors: Gamification, Electronic Learning, Higher Education, Recognition (Achievement)
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Yang, Christopher C. Y.; Ogata, Hiroaki – Education and Information Technologies, 2023
The application of student interaction data is a promising field for blended learning (BL), which combines conventional face-to-face and online learning activities. However, the application of online learning technologies in BL settings is particularly challenging for students with lower self-regulatory abilities. In this study, a personalized…
Descriptors: Individualized Instruction, Learning Analytics, Intervention, Academic Achievement
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van Vijfeijken, Marijke; van Schilt-Mol, Tamara; van den Bergh, Linda; Scholte, Ron H. J.; Denessen, Eddie – Cogent Education, 2023
Teachers need to make choices about how they distribute their time and support, and a school's vision may support teachers in making these choices. This study aimed to gain insight into how individual teachers--each with their own beliefs about fair classroom differentiation--handle differentiation dilemmas in the context of their school's vision.…
Descriptors: Teacher Attitudes, Individualized Instruction, Educational Objectives, Elementary School Teachers
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Scott, Jennifer L.; Knezek, Gerald; Poirot, James R.; Lin-Lipsmeyer, Lin – TechTrends: Linking Research and Practice to Improve Learning, 2023
Work-based and employee-driven informal learning, training and development have been increasing in importance in the last few decades. Concurrently, organizations seek to measure the extent to which they develop a culture and structure that supports individual learning and organizational learning. This study examines the perception of a learning…
Descriptors: Individualized Instruction, Electronic Learning, Alternative Assessment, Test Construction
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Costley, Jamie; Lange, Christopher – Interactive Learning Environments, 2023
The use of e-learning personalization allows learners to control their learning by choosing which content to process and how to process it. In order to explain the processes that occur when students use e-learning personalization, this study looks at how it interacts with two other variables: sequencing and fading, a scaffolding technique where…
Descriptors: Electronic Learning, Individualized Instruction, Cognitive Processes, Difficulty Level
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Wong, Billy Tak-ming; Li, Kam Cheong; Cheung, Simon K. S. – Journal of Computing in Higher Education, 2023
This paper presents an analysis of learning analytics practices which aimed to achieve personalised learning. It addresses the need for a systematic analysis of the increasing amount of practices of learning analytics which are targeted at personalised learning. The paper summarises and highlights the characteristics and trends in relevant…
Descriptors: Learning Analytics, Individualized Instruction, Context Effect, Stakeholders
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Mustapha Riad; Mohammed Qbadou; Es-Saâdia Aoula; Soukaina Gouraguine – Journal of Education and Learning (EduLearn), 2023
E-learning has increased in popularity, especially during the COVID-19, due to its numerous advantages that allow learners to study anywhere and anytime. Therefore, recommending a list of the most appropriate learning objects for learners according to their specific needs is a great challenge for adaptive e-learning systems. In an e-learning…
Descriptors: Electronic Learning, COVID-19, Pandemics, Cognitive Style
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Teresa M. Ober; Blair A. Lehman; Reginald Gooch; Olasumbo Oluwalana; Jaemarie Solyst; Geoffrey Phelps; Laura S. Hamilton – ETS Research Report Series, 2023
Culturally responsive personalized learning (CRPL) emphasizes the importance of aligning personalized learning approaches with previous research on culturally responsive practices to consider social, cultural, and linguistic contexts for learning. In the present discussion, we briefly summarize two bodies of literature considered in defining and…
Descriptors: Culturally Relevant Education, Individualized Instruction, Definitions, Educational Principles
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