M. Worsley, K. Chiluiza, Joseph F. Grafsgaard, X. Ochoa
{"title":"2015 Multimodal Learning and Analytics Grand Challenge","authors":"M. Worsley, K. Chiluiza, Joseph F. Grafsgaard, X. Ochoa","doi":"10.1145/2818346.2829995","DOIUrl":null,"url":null,"abstract":"Multimodality is an integral part of teaching and learning. Over the past few decades researchers have been designing, creating and analyzing novel environments that enable students to experience and demonstrate learning through a variety of modalities. The recent availability of low cost multimodal sensors, advances in artificial intelligence and improved techniques for large scale data analysis have enabled researchers and practitioners to push the boundaries on multimodal learning and multimodal learning analytics. In an effort to continue these developments, the 2015 Multimodal Learning and Analytics Grand Challenge includes a combined focus on new techniques to capture multimodal learning data, as well as the development of rich, multimodal learning applications.","PeriodicalId":20486,"journal":{"name":"Proceedings of the 2015 ACM on International Conference on Multimodal Interaction","volume":"4 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2015-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2015 ACM on International Conference on Multimodal Interaction","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2818346.2829995","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9
Abstract
Multimodality is an integral part of teaching and learning. Over the past few decades researchers have been designing, creating and analyzing novel environments that enable students to experience and demonstrate learning through a variety of modalities. The recent availability of low cost multimodal sensors, advances in artificial intelligence and improved techniques for large scale data analysis have enabled researchers and practitioners to push the boundaries on multimodal learning and multimodal learning analytics. In an effort to continue these developments, the 2015 Multimodal Learning and Analytics Grand Challenge includes a combined focus on new techniques to capture multimodal learning data, as well as the development of rich, multimodal learning applications.