Learning stylesLearning preferencesKinesthetic learnersVARK’s modalitiesMultimodal learning approachNumerous learning styles, schemes, and models are described in the literature. Most common are VARK (visual, auditory, read/write, kinesthetic) model of learning style and Kolb's experiential learning. Since...
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Multimodal learning suggests that when a number of our senses – visual, auditory, kinaesthetic – are being engaged during learning, we understand and remember more. By combining these modes, learners experience learning in a variety of ways to create a diverse learning style. For example, let’...
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J. Hwang, “Meta-stylespeech: Multi-speaker adaptive text-to-speech generation,” arXiv, 2021. [178] B. Shi, W.-N. Hsu, K. Lakhotia, and A. Mohamed, “Learning audio-visual speech representation by masked multimodal cluster prediction,” arXiv, 2022. [179] K. Ramesh, C. Xing,...
Firstly, large multimodal models have the ability to personalize learning experiences. By analyzing a student's learning style, preferences, and abilities, these models can tailor educational content to meet their individual needs. This personalized approach is particularly beneficial for students with spe...
Federated learning (FL), which provides a collaborative training scheme for distributed data sources with privacy concerns, has become a burgeoning and attractive research area. Most existing FL studies focus on taking unimodal data, such as image and text, as the model input and resolving the het...
Multimodal In-Context Learning Multimodal Chain-of-Thought LLM-Aided Visual Reasoning Foundation Models Evaluation Multimodal RLHF Others Awesome Datasets Datasets of Pre-Training for Alignment Datasets of Multimodal Instruction Tuning Datasets of In-Context Learning ...
Learning styles of first-year medical students attending Erciyes University in Kayseri, Turkey Educational researchers postulate that every individual has a different style. The aim of this descriptive study was to determine the styles of first-year ... Z Baykan,M Nacar - 《Ajp Advances in Physiol...
self-supervised learning has become an attractive strategy to alleviate the annotation bottleneck. Building on these two directions, self-supervised multimodal learning (SSML) provides ways to learn from raw multimodal data. In this survey, we provide a comprehensive review of the state-of-the-art ...