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Showing 1 to 15 of 18 results Save | Export
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Yuan Liu; Yongquan Dong; Chan Yin; Cheng Chen; Rui Jia – Education and Information Technologies, 2024
The open online course (MOOC) platform has seen an increase in usage, and there are a growing number of courses accessible for people to select. An effective method is urgently needed to recommend personalized courses for users. Although the existing course recommendation models consider that users' interests change over time, they often model…
Descriptors: MOOCs, Online Courses, Models, Course Selection (Students)
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Yicong Zheng; Aike Shi; Xiaonan L. Liu – npj Science of Learning, 2024
This Perspective article expands on a working memory-dependent dual-process model, originally proposed by Zheng et al., to elucidate individual differences in the testing effect. This model posits that the testing effect comprises two processes: retrieval-attempt and post-retrieval re-encoding. We substantiate this model with empirical evidence…
Descriptors: Short Term Memory, Models, Individual Differences, Testing
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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
Mariel Anne Farrar Werner – ProQuest LLC, 2024
When multiple clients are collaboratively learning and training a shared model, incentives problems can arise. The clients may have different learning objectives and application domains, or they may be competitors whose participation in the learning system could reduce their competitive advantage. While collaborative learning is a powerful…
Descriptors: Cooperative Learning, Alignment (Education), Educational Objectives, Incentives
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Nicolas J. Tanchuk; Rebecca M. Taylor – Educational Theory, 2025
AI tutors are promised to expand access to personalized learning, improving student achievement and addressing disparities in resources available to students across socioeconomic contexts. The rapid development and introduction of AI tutors raises fundamental questions of epistemic trust in education. What criteria should guide students' critical…
Descriptors: Individualized Instruction, Artificial Intelligence, Technology Uses in Education, Tutors
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Paola Mejia-Domenzain; Jibril Frej; Seyed Parsa Neshaei; Luca Mouchel; Tanya Nazaretsky; Thiemo Wambsganss; Antoine Bosselut; Tanja Käser – International Journal of Artificial Intelligence in Education, 2025
Writing high-quality procedural texts is a challenging task for many learners. While example-based learning has shown promise as a feedback approach, a limitation arises when all learners receive the same content without considering their individual input or prior knowledge. Consequently, some learners struggle to grasp or relate to the feedback,…
Descriptors: Writing Instruction, Academic Language, Content Area Writing, Cooking Instruction
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Hao Zhou; Wenge Rong; Jianfei Zhang; Qing Sun; Yuanxin Ouyang; Zhang Xiong – IEEE Transactions on Learning Technologies, 2025
Knowledge tracing (KT) aims to predict students' future performances based on their former exercises and additional information in educational settings. KT has received significant attention since it facilitates personalized experiences in educational situations. Simultaneously, the autoregressive (AR) modeling on the sequence of former exercises…
Descriptors: Learning Experience, Academic Achievement, Data, Artificial Intelligence
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Hon Keung Yau; Ka Fai Tung – Turkish Online Journal of Educational Technology - TOJET, 2025
This study explores the development and evaluation of a chatbot model designed to facilitate learning within a department of a university. The project aims to enhance the learning experience by incorporating customized data into the chatbot's knowledge base, enabling personalized and context-aware interactions. The research investigates the…
Descriptors: Instructional Effectiveness, Artificial Intelligence, Computer Software, Technology Integration
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Xiang Wu; Huanhuan Wang; Yongting Zhang; Baowen Zou; Huaqing Hong – IEEE Transactions on Learning Technologies, 2024
Generative artificial intelligence has become the focus of the intelligent education field, especially in the generation of personalized learning resources. Current learning resource generation methods recommend customized courses based on learning styles and interests, improving learning efficiency. However, these methods cannot generate…
Descriptors: Artificial Intelligence, Individualized Instruction, Intelligent Tutoring Systems, Cognitive Style
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Hongyu Xie; He Xiao; Yu Hao – International Journal of Web-Based Learning and Teaching Technologies, 2024
Modern e-learning system is a representative service form in innovative service industry. This paper designs a personalized service domain system, optimizes various parameters and can be applied to different education quality evaluation, and proposes a decision tree recommendation algorithm. Information gain is carried out through many existing…
Descriptors: Artificial Intelligence, Electronic Learning, Individualized Instruction, Models
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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
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Linlin Hu – Asia Pacific Education Review, 2024
Differentiated instruction (DI) is a beneficial approach to addressing students' diverse learning needs, abilities, and interests to ensure that each student has the opportunity to make academic progress. To answer the question of how teachers utilize DI in K-12 classrooms, this systematic review was based on 61 empirical studies on DI published…
Descriptors: Individualized Instruction, Elementary Secondary Education, Educational Trends, Elementary School Mathematics
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Xiaoxia A. Newton; John W. McKenna; Frederick J. Brigham – Journal of Research in Special Educational Needs, 2025
The relationships among teachers' knowledge, use, and perceived effectiveness of inclusive instructional practices for students with emotional disturbance (ED) has implications for the provision of a free appropriate public education (FAPE). We unpacked these nuanced relationships through mediation analysis. Data for our study came from a broader…
Descriptors: Mediation Theory, Models, Inclusion, Educational Practices
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Genevieve Thraves – Australasian Journal of Gifted Education, 2024
Gifted education has been recognised as a fractured field that can be categorised using varying paradigmatic approaches. Over the past thirty years, Gagne's Differentiated Model of Giftedness and Talents (DMGT) has maintained a strong influence in Australia, which means that the paradigmatic assumptions that are present in this model have shaped…
Descriptors: Foreign Countries, Gifted Education, Educational Policy, Web Sites
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Tracy Bobko; Mikiko Corsette; Minjuan Wang; Erin Springer – IEEE Transactions on Learning Technologies, 2024
This article discusses the transformative impact of technology on knowledge acquisition and sharing, focusing on the emergence of the metaverse as a virtual community with vast potential for virtual learning. Learning in the metaverse is found to enhance engagement, motivation, and retention, while fostering 21st-century skills. It also offers…
Descriptors: Educational Innovation, Computer Simulation, Technology Uses in Education, Models
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