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Huaiya Liu; Yuyue Zhang; Jiyou Jia – IEEE Transactions on Learning Technologies, 2024
Intelligent tutoring systems (ITSs) aim to deliver personalized learning support to each learner, aligning with the educational aspiration of many countries, including China. ITSs' personalized support is mainly achieved by providing individual prompts to learners when they encounter difficulties in problem-solving. The guiding principles and…
Descriptors: Intelligent Tutoring Systems, Mathematics Achievement, Individualized Instruction, Foreign Countries
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Keuning, Trynke; van Geel, Marieke – IEEE Transactions on Learning Technologies, 2021
Although many schools in the Netherlands have purchased adaptive learning systems (ALSs) to reduce workload and improve differentiated instruction, the use of ALSs with teacher dashboards in the classroom does not in itself necessarily improve differentiated instruction. The question is, what skills and knowledge do teachers need to provide…
Descriptors: Foreign Countries, Individualized Instruction, Integrated Learning Systems, Educational Technology
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Hu, Jie; Peng, Yi; Chen, Xiao – IEEE Transactions on Learning Technologies, 2023
The prevalence of information and communication technologies (ICTs) has brought about profound changes in the field of reading, resulting in a large and rapidly growing number of young digital readers. The article intends to identify key contextual factors that synergistically differentiate high and low performers, high and average performers, and…
Descriptors: Decoding (Reading), Educational Technology, Information Technology, Reading Skills
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Jyoti, Vishav; Lahiri, Uttama – IEEE Transactions on Learning Technologies, 2020
Children with autism spectrum disorder (ASD) are characterized by deficits in social communication, partly attributed to the inability to pick up cues from social partners using joint attention (JA) skill. These deficits have cascading adverse effects on language acquisition and the development of cognitive skills. Therapist-mediated JA…
Descriptors: Computer Simulation, Autism, Pervasive Developmental Disorders, Children
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Wan, Han; Zhong, Zihao; Tang, Lina; Gao, Xiaopeng – IEEE Transactions on Learning Technologies, 2023
Small private online courses (SPOCs) have influenced teaching and learning in China's higher education. Learning management systems (LMSs) are important components in SPOCs. They can collect various data related to student behavior and support pedagogical interventions. This research used feature engineering and nearest neighbor smoothing models…
Descriptors: Online Courses, Learning Management Systems, Higher Education, Student Behavior
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Yousuf, Bilal; Conlan, Owen – IEEE Transactions on Learning Technologies, 2018
This paper introduces VisEN, a novel visual narrative framework that has been shown to facilitate, support, and enhance student engagement in an adaptive Online Learning Environment (OLE). VisEN provides explorable visual narratives personalized to students in order to support them in engaging with course content. The evaluation of VisEN showed…
Descriptors: Learner Engagement, Visual Aids, Electronic Learning, Individualized Instruction
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Rajendran, Ramkumar; Iyer, Sridhar; Murthy, Sahana – IEEE Transactions on Learning Technologies, 2019
The importance of affective states in learning has led many Intelligent Tutoring Systems (ITS) to include students' affective states in their learner models. The adaptation and hence the benefits of an ITS can be improved by detecting and responding to students' affective states. In prior work, we have created and validated a theory-driven model…
Descriptors: Feedback (Response), Individualized Instruction, Intelligent Tutoring Systems, Psychological Patterns
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Baneres, David; Rodriguez-Gonzalez, M. Elena; Serra, Montse – IEEE Transactions on Learning Technologies, 2019
Identifying at-risk students as soon as possible is a challenge in educational institutions. Decreasing the time lag between identification and real at-risk state may significantly reduce the risk of failure or disengage. In small courses, their identification is relatively easy, but it is impractical on larger ones. Current Learning Management…
Descriptors: Prediction, Feedback (Response), At Risk Students, College Freshmen
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Yao, Ching-Bang – IEEE Transactions on Learning Technologies, 2017
Although m-learning applications have been widely researched, few studies have investigated applying adaptive learning content to various learning environments and efficient input interfaces. This study combined a context-aware mechanism, which can be used to provide suitable learning information anytime and anyplace by using GPS technology, with…
Descriptors: Electronic Learning, Educational Technology, Usability, Individualized Instruction
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Cabielles-Hernandez, David; Pérez-Pérez, Juan-Ramón; Paule-Ruiz, MPuerto; Fernández-Fernández, Samuel – IEEE Transactions on Learning Technologies, 2017
New possibilities offered by mobile devices for special education students have led to the design of skill acquisition software applications. Advances in mobile technologies development have made progress possible in helping teachers with autistic students modelling and evaluation. "Chain of Words" theoretical basis is the autism…
Descriptors: Autism, Pervasive Developmental Disorders, Children, Communication Strategies