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Yunyun Liu; Yinghua Ye – European Journal of Psychology of Education, 2025
Self-regulated learning (SRL) is the key variable to ensuring success or failure in online learning. However, in real-world online learning, college students face SRL deficiency, such as procrastination, decreased learning motivation, poor time management, and resource management. Therefore, scientifically exploring how to effectively promote the…
Descriptors: Individualized Instruction, Cooperative Learning, Electronic Learning, Small Group Instruction
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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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Xiaoqing Xu; Wei Zhao; Yue Li; Lifang Qiao; Jinhong Tao; Fengjuan Liu – Education and Information Technologies, 2025
The success of online learning relies on college students' self-regulated learning. The common visualizations (e.g., presentation learning behaviors' frequency and duration) are widely used to enhance online self-regulated learning. But most college students still have difficulty in accurately understanding their learning patterns and…
Descriptors: Individualized Instruction, Electronic Learning, College Students, Visualization
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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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Xueyu Sun; Ting Wang – International Journal of Information and Communication Technology Education, 2024
This study innovates English network teaching by applying a refined Association Rule Mining (ARM) algorithm. It integrates an "interest" parameter into ARM, dynamically adapting content to individual learners' profiles, improving engagement and outcomes. Controlled experiments, spanning diverse online platforms, validate the ARM model's…
Descriptors: Models, Design, Algorithms, Individualized Instruction
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Huang, Tao; Hu, Shengze; Yang, Huali; Geng, Jing; Liu, Sannyuya; Zhang, Hao; Yang, Zongkai – IEEE Transactions on Learning Technologies, 2023
The global outbreak of the new coronavirus epidemic has promoted the development of intelligent education and the utilization of online learning systems. In order to provide students with intelligent services, such as cognitive diagnosis and personalized exercises recommendation, a fundamental task is the concept tagging for exercises, which…
Descriptors: Educational Technology, Prediction, Electronic Learning, Intelligent Tutoring Systems
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DongMei Xu – International Journal of Information and Communication Technology Education, 2024
With the rapid development of Internet technology, distance online education and training is becoming an important part of the education and training market. Based on the theory of perceived value, taking the distance online education and training platform as the research object, this paper establishes a sample database, analyzes the reliability,…
Descriptors: Distance Education, Electronic Learning, Parent Attitudes, Educational Quality
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Rafael Alé-Ruiz; Fernando Martínez-Abad; María Teresa del Moral-Marcos – Education and Information Technologies, 2024
The flexible, changing, and uncertain nature of present-day society requires its citizens have new personal, professional, and social competences which exceed the traditional knowledge-based, academic skills imparted in higher education. This study aims to identify those factors associated with active methodologies that predict university…
Descriptors: Learner Engagement, Individualized Instruction, Active Learning, Higher Education
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Bellarhmouch, Youssra; Jeghal, Adil; Tairi, Hamid; Benjelloun, Nadia – Education and Information Technologies, 2023
Nowadays, the need for e-learning is amplified, especially after the COVID-19 pandemic. E-learning platforms present a solution for the continuity of the learning process. Learners are using different platforms and tools for learning. For this, it is necessary to model the learner for the personalization of the learning environment according to…
Descriptors: Electronic Learning, Educational Environment, Models, Individualized Instruction
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Lange, Christopher – Open Learning, 2023
Cognitive processing issues online may be reduced through e-learning personalisation, which allows learners to address individual learning needs by controlling how they process information. While some research shows that e-learning personalisation may actually complicate information processing under specific circumstances, this study examines…
Descriptors: Electronic Learning, Individualized Instruction, Cognitive Processes, Difficulty Level
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Hattingh, Sherene; Northcote, Maria – Journal of Further and Higher Education, 2023
In the last few decades, the expansion of online learning and online assessment has attracted both negative and positive attention, some of which has celebrated the flexibility and individualised affordances of online learning contexts, while also lamenting the overuse of one-size-fits-all teaching approaches. Virtual learning contexts have been…
Descriptors: Individualized Instruction, Computer Assisted Testing, Literature Reviews, Online Courses
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Babb, David; Howard, Ervin – Online Journal of Distance Learning Administration, 2023
The University of North Georgia's division of Distance Education & Technology Integration, DETI, developed a series of self-paced workshops to assist faculty in professional development as a response to faculty inquiries and the pandemic. The pandemic changed the way we look at our professional development opportunities. DETI concluded that we…
Descriptors: Workshops, Faculty Development, Individualized Instruction, Pacing
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Lee, Jung-Chieh; Xiong, Liangnan – Education and Information Technologies, 2023
Mobile-assisted language learning (MALL) applications (apps) can provide users with personalized learning content to meet their learning needs. Besides, from the learner perspective, the apps can be regarded as 'social' individuals, like anthropomorphic instructors who offer social support to help them with language learning. However, the current…
Descriptors: Use Studies, Decision Making, Handheld Devices, Electronic Learning
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Cakir, Ozlem – Journal of Learning and Teaching in Digital Age, 2022
Since Personalized Instruction increases the motivation, interest, performance and attitude of the student, it is aimed to develop an instructional management system that can be adapted to the individual, taking into account the prior knowledge level of the person who provides the personalization of all instructional materials. The project is…
Descriptors: Individualized Instruction, Electronic Learning, Calculus, College Mathematics
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Guoqian Luo; Hengnian Gu; Xiaoxiao Dong; Dongdai Zhou – Education and Information Technologies, 2025
In the realm of e-learning, supporting personalized learning effectively necessitates recommending sequences of learning items that maximize learning efficiency while minimizing cognitive load, all tailored to the learner's goals. These recommendations must account for the prerequisite relationships among learning items and the learner's…
Descriptors: Electronic Learning, Individualized Instruction, Sequential Learning, Learning Processes
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