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Showing 1 to 15 of 516 results Save | Export
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Qin Ni; Yifei Mi; Yonghe Wu; Liang He; Yuhui Xu; Bo Zhang – IEEE Transactions on Learning Technologies, 2024
Learning style recognition is an indispensable part of achieving personalized learning in online learning systems. The traditional inventory method for learning style identification faces the limitations such as subject and static characteristics. Therefore, an automatic and reliable learning style recognition mechanism is designed in this…
Descriptors: Cognitive Style, Electronic Learning, Prediction, Identification
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Akila Nallabelli; Heidi L. Lujan; Stephen E. DiCarlo – Advances in Physiology Education, 2024
The movement of air into and out of the lungs is facilitated by changes in pressure within the thoracic cavity relative to atmospheric pressure, as well as the resistance encountered by airways. In this process, the movement of air into and out of the lungs is driven by pressure gradients established by changes in lung volume and intra-alveolar…
Descriptors: Physics, Motion, Misconceptions, Scientific Concepts
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Ulrike Cress; Joachim Kimmerle – International Journal of Computer-Supported Collaborative Learning, 2023
Generative Artificial Intelligence (AI) tools, such as ChatGPT, have received great attention from researchers, the media, and the public. They are gladly and frequently used for text production by many people. These tools have undeniable strengths but also weaknesses that must be addressed. In this squib we ask to what extent these tools can be…
Descriptors: Artificial Intelligence, Cognitive Style, Computer Assisted Instruction, Learning Strategies
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Troussas, Christos; Giannakas, Filippos; Sgouropoulou, Cleo; Voyiatzis, Ioannis – Interactive Learning Environments, 2023
Computer-Supported Collaborative Learning is a promising innovation that ameliorates tutoring through modern technologies. However, the way of recommending collaborative activities to learners, by taking into account their learning needs and preferences, is an important issue of increasing interest. In this context, this paper presents a framework…
Descriptors: Computer Assisted Instruction, Cognitive Style, Cooperative Learning, Models
Reima Al-Jarf – Online Submission, 2024
Multimodal learning refers to teaching strategies that involve multiple sensory systems simultaneously. Teachers can create materials for students with different learning styles (auditory, visual, kinesthetic reading, and writing). Multimodal learning keeps students engaged, encourages them to apply what they learn in real-life situations,…
Descriptors: Grammar, Multimedia Instruction, Problem Solving, Student Projects
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Sridharan, Shwetha; Saravanan, Deepti; Srinivasan, Akshaya Kesarimangalam; Murugan, Brindha – Education and Information Technologies, 2021
There exist numerous resources online to gain the desired level of knowledge on any topic. However, this complicates the process of selecting the most appropriate resources. Every learner differs in terms of their learning speed, proficiency, and preferred mode of learning. This paper develops an adaptive learning management system to tackle this…
Descriptors: Integrated Learning Systems, Computer Assisted Instruction, Individualized Instruction, Learning Analytics
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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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Trifirò, Catherine Elizabeth Vucetic; Laing, Gregory Kenneth – e-Journal of Business Education and Scholarship of Teaching, 2021
Purpose: The purpose of this paper is to examine the various models concerned with identifying learning styles and cognitive traits of students as a means to adapt teaching methods. With attention to the applicability of the models to on-line teaching strategies and requirements. Design/Method/Approach: The approach adopted in this paper is one of…
Descriptors: Cognitive Style, Electronic Learning, Integrated Learning Systems, Teaching Methods
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Benabbes, Khalid; Housni, Khalid; Hmedna, Brahim; Zellou, Ahmed; Mezouary, Ali El – Education and Information Technologies, 2023
Today, with the extension of learning management systems (LMSs) and the diversity of learners' needs for online learning, instructors have to be assisted to adapt their syllabus to meet learners' needs. Therefore, it is necessary to tailor course instruction to meet individual needs and determine how well they serve the learners using these online…
Descriptors: Learning Management Systems, Student Needs, Cognitive Style, Context Effect
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Hui Jin; Hyo Jeong Shin; Dante Cisterna – International Journal of Science and Mathematics Education, 2024
Learning progressions (LPs) are cognitive models that describe the development of scientific knowledge and practices in students. They are constructed based on learning theories and student data. Scholars have advocated for using LPs to align curriculum, instruction, and assessment into a coherent system, and by doing so, promote productive…
Descriptors: Educational Research, Cognitive Style, Evaluation Methods, Learning Trajectories
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Aguilar, J.; Buendia, O.; Pinto, A.; Gutiérrez, J. – Interactive Learning Environments, 2022
Social Learning Analytics (SLA) seeks to obtain hidden information in large amounts of data, usually of an educational nature. SLA focuses mainly on the analysis of social networks (Social Network Analysis, SNA) and the Web, to discover patterns of interaction and behavior of educational social actors. This paper incorporates the SLA in a smart…
Descriptors: Learning Analytics, Cognitive Style, Socialization, Social Networks
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Liontas, John I.; Mannion, Patrick – Iranian Journal of Language Teaching Research, 2021
This paper presents the primary benefits digital storytelling affords teachers and students. Maximizing the multimodal authoring conditions for optimal online/offline learning comprises the paper's main focus. Throughout, it is asserted that stories worth telling are stories worth sharing but only if embedded in dialogic constructs supporting…
Descriptors: Information Technology, Story Telling, Multimedia Materials, Learning Processes
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Balti, Rihab; Hedhili, Aroua; Chaari, Wided Lejouad; Abed, Mourad – Education and Information Technologies, 2023
Since the COVID pandemic, universities propose online education to ensure learning continuity. However, the insufficient preparation led to a major drop in the learner's performance and his/her dissatisfaction with the learning experience. This may be due to several reasons, including the insensitivity of the virtual learning environment to the…
Descriptors: Cognitive Style, Pandemics, COVID-19, Distance Education
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Mainali, Bhesh – International Electronic Journal of Mathematics Education, 2021
Preferences for solution methods have an important implication teaching and learning mathematics and students' mathematical performances. In the domain of learning mathematics, there are two modes of processing mathematical information: verbal logical and visual-pictorial. Learners who process mathematical information using verbal logical and…
Descriptors: Teaching Methods, Mathematics Instruction, Preferences, Mathematics Achievement
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Campo, Marcelo; Amandi, Analia; Biset, Julio Cesar – Education and Information Technologies, 2021
Moodle represents a great contribution to the educational world since it provides an evolving platform for Virtual Learning Management Systems (VLMS) that became a standard de facto for most of the educational institutions around the world. Through the pedagogical functions provided, it collects in the many globally spread out databases a huge…
Descriptors: Computer Software, Computer Simulation, Integrated Learning Systems, Teaching Methods
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