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Yaqian Zheng; Deliang Wang; Junjie Zhang; Yanyan Li; Yaping Xu; Yaqi Zhao; Yafeng Zheng – Education and Information Technologies, 2025
Generating personalized learning pathways for e-learners is a critical issue in the field of e-learning as it plays a pivotal role in guiding learners towards the successful achievement of their learning objectives. The existing literature has proposed various methods from different perspectives to address this issue, including learner-based,…
Descriptors: Individualized Instruction, Electronic Learning, Academic Achievement, Student Educational Objectives
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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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Suthinanth Rattanachotithavorn; Pattarawat Jeerapattanatorn – Journal of Education and Learning, 2025
This review article examines the emerging trends in business education to address the rapidly evolving demands of a global, technology-driven economy. The study systematically analyzed 64 research articles from academic databases, of which 28 high-quality studies met the inclusion criteria based on their direct relevance to business education and…
Descriptors: Business Education, Educational Trends, Educational Research, Artificial Intelligence
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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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Fatima Rahioui; Mohammed Ali Tahri Jouti; Mohammed El Ghzaoui – Journal of Educators Online, 2024
Artificial intelligence (AI) is now affecting all aspects of our social lives. Without always knowing it, we interact daily with intelligent systems. They serve us invisibly. At least that is the goal we assign to them: to make our lives better, task by task. Artificial intelligence has the potential to make biology education more engaging,…
Descriptors: Artificial Intelligence, Biological Sciences, Scientific Concepts, Technology Integration
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Xingle Ji; Lu Sun; Xueyong Xu; Xiaobing Lei – International Journal of Information and Communication Technology Education, 2024
This study examines the current research on educational data mining, educational learning support services, personalized learning services, and personalized learning paths in education. The authors aim to integrate personalized learning concepts into traditional support services by drawing on the latest theoretical and practical research. Using…
Descriptors: Information Retrieval, Data Analysis, Educational Research, Individualized Instruction
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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Frost, Raymond; Matta, Vic; Kenyo, Lauren – Journal of Information Systems Education, 2021
Student learning benefits from individual support and feedback. This type of support does not scale well especially in large classes. A system was built to automate the delivery of individual support and feedback on Excel assignments in information systems and analytics courses. The system embeds instructional scaffolding in the distributed…
Descriptors: Automation, Scaffolding (Teaching Technique), Formative Evaluation, Individualized Instruction
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Morakinyo Akintolu; Akinpelu A. Oyekunle – Journal of Educators Online, 2025
This paper provides a comprehensive overview of the research on the application of artificial intelligence (AI) in primary education to explore its potential to enhance teaching and learning processes. Through a systematic review of the relevant literature, this study identifies key areas in which AI can significantly impact primary education and…
Descriptors: Data Analysis, Learning Analytics, Artificial Intelligence, Computer Software
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Li, Xiaoyu; Xia, Jianping – Science Insights Education Frontiers, 2020
The rise of big data technology provides direction and support for the reform and development of education. Big data technology can realize the inventory management and effective dynamic monitoring of schools, students, and teachers. It is conducive to comprehensively and accurately controlling the development of teaching activities, injecting new…
Descriptors: Foreign Countries, Middle School Students, Data Analysis, Data Collection
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Mamcenko, Jelena; Kurilovas, Eugenijus; Krikun, Irina – Informatics in Education, 2019
The paper aims to present application of Educational Data Mining and particularly Case-Based Reasoning (CBR) for students profiling and further to design a personalised intelligent learning system. The main aim here is to develop a recommender system which should help the learners to create learning units (scenarios) that are the most suitable for…
Descriptors: Case Method (Teaching Technique), Individualized Instruction, Intelligent Tutoring Systems, Cognitive Style
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Pardo, Abelardo; Jovanovic, Jelena; Dawson, Shane; Gaševic, Dragan; Mirriahi, Negin – British Journal of Educational Technology, 2019
There is little debate regarding the importance of student feedback for improving the learning process. However, there remain significant workload barriers for instructors that impede their capacity to provide timely and meaningful feedback. The increasing role technology is playing in the education space may provide novel solutions to this…
Descriptors: Learning, Data Analysis, Feedback (Response), Technology Uses in Education
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Ipek, Ziyaeddin Halid; Gözüm, Ali Ibrahim Can; Papadakis, Stamatios; Kallogiannakis, Michail – Educational Process: International Journal, 2023
Background/purpose: ChatGPT is an artificial intelligence program released in November 2022, but even now, many studies have expressed excitement or concern about its introduction into academia and education. While there are many questions to be asked, the current study reviews the literature in order to reveal the potential effects of ChatGPT on…
Descriptors: Artificial Intelligence, Educational Technology, Technology Uses in Education, Educational Benefits
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Pardo, Abelardo; Bartimote-Aufflick, Kathryn; Shum, Simon Buckingham; Dawson, Shane; Gao, Jing; Gaševic, Dragan; Leichtweis, Steve; Liu, Danny; Martínez-Maldonado, Roberto; Mirriahi, Negin; Moskal, Adon Christian Michael; Schulte, Jurgen; Siemens, George; Vigentini, Lorenzo – Journal of Learning Analytics, 2018
The learning analytics community has matured significantly over the past few years as a middle space where technology and pedagogy combine to support learning experiences. To continue to grow and connect these perspectives, research needs to move beyond the level of basic support actions. This means exploring the use of data to prove richer forms…
Descriptors: Individualized Instruction, Data Analysis, Learning, Feedback (Response)
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Prior-Grosch, Ariadne; Woodruff, Karen – Science Teacher, 2022
Fall 2020 presented myriad challenges for teachers trying to plan curricula to meet students' social-emotional and learning needs following an unprecedented spring and summer of isolation and loss due to the pandemic caused by SARS-CoV-2 (Rivera and Wallace 2020). The result of creative planning and adjusting of curricula for remote instruction…
Descriptors: COVID-19, Pandemics, School Closing, Distance Education
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