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Proceedings of the Third International Conference on Learning Analytics and Knowledge, 2013
New high-frequency data collection technologies and machine learning analysis techniques could offer new insights into learning, especially in tasks in which students have ample space to generate unique, personalized artifacts, such as a computer program, a robot, or a solution to an engineering challenge. To date most of the work on learning analytics
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New high-frequency data collection technologies and machine learning analysis techniques could offer new insights into learning, especially in tasks in which students have ample space to generate unique, personalized artifacts, such as a computer program, a robot, or a solution to an engineering challenge. To date most of the work on learning analytics
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Learning Multimodal Latent Attributes
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2014The rapid development of social media sharing has created a huge demand for automatic media classification and annotation techniques. Attribute learning has emerged as a promising paradigm for bridging the semantic gap and addressing data sparsity via transferring attribute knowledge in object recognition and relatively simple action classification. In
Yanwei Fu 0001 +3 more
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Hierarchical Multimodal Metric Learning for Multimodal Classification
2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017Multimodal classification arises in many computer vision tasks such as object classification and image retrieval. The idea is to utilize multiple sources (modalities) measuring the same instance to improve the overall performance compared to using a single source (modality). The varying characteristics exhibited by multiple modalities make it necessary
Heng Zhang 0003 +2 more
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Multimodal Learning Hub: A Tool for Capturing Customizable Multimodal Learning Experiences
2018Studies in Learning Analytics provide concrete examples of how the analysis of direct interactions with learning management systems can be used to optimize and understand the learning process. Learning, however, does not necessarily only occur when the learner is directly interacting with such systems. With the use of sensors, it is possible to collect
Jan Schneider 0001 +3 more
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ACM Transactions on Multimedia Computing, Communications, and Applications
Food-centered study has received more attention in the multimedia community for its profound impact on our survival, nutrition and health, pleasure, and enjoyment. Our experience of food is typically multi-sensory: We see food objects, smell its odors, taste its flavors, feel its texture, and hear sounds when chewing.
Weiqing Min +9 more
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Food-centered study has received more attention in the multimedia community for its profound impact on our survival, nutrition and health, pleasure, and enjoyment. Our experience of food is typically multi-sensory: We see food objects, smell its odors, taste its flavors, feel its texture, and hear sounds when chewing.
Weiqing Min +9 more
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Multimodality in a Mobile Learning Environment
2008 19th International Workshop on Database and Expert Systems Applications, 2008The aim of this paper is to investigate the use of multimodal interfaces as an opportunity for students involved in mobile learning activities to enhance their didactic experience. The MoULe (Mobile and Ubiquitous Learning) system, a technological platform that we developed in order to support on-site learning experiences through handheld devices ...
Seta Luciano +6 more
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Hebbian Learning In A Multimodal Environment
Advances in Artificial Life, ECAL 2013, 2013Hebbian learning is a classical non-supervised learning algorithm used in neural networks. Its particularity is to transcribe the correlations between couple of neurons within their connecting synapse. From this idea, we created a robotic task where 2 sensory modalities indicate the same target in order to find out if a neural network equipped with ...
Julien Hubert +2 more
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Multimodal Interfaces for Inclusive Learning
2018In this paper, we propose that the artificial intelligence in education (AIED) community lead the charge in leveraging multimodal interfaces, in conjunction with artificial intelligence, to advance learning interfaces and experiences that are more inclusive.
Marcelo Worsley +4 more
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Transfer learning in multimodal corpora
2013 IEEE 4th International Conference on Cognitive Infocommunications (CogInfoCom), 2013People use both their speech and their body when they communicate face to face, thus human communication is multimodal. The development of multimodal coginfocom systems requires models of the relation between the various modalities, but many studies have shown that multimodal behaviours depend on numerous factors comprising the culture, the setting and
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