Titlebook: Collaboration Technologies and Social Computing; 27th International C Davinia Hernández-Leo,Reiko Hishiyama,Hiroaki Ogat Conference proceed

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Donghui Lin,Toru Ishida,Yohei Murakamiries. Analysis of existing datasets from CS projects can broaden our understanding of how different stakeholder groups interact and contribute to the joint achievements. To this end, we have collected publicly available forum data from the “Chimp&See” project hosted on the Zooniverse platform via cr

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Data Service API Design for Data Analyticsuccess of the group depends to a great extent on the engagement of its group members. During the COVID-19 pandemic, it became possible to automatically detect engagement using students learning data as all the teaching and learning processes can be recorded. This paper presents an exploratory study

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Lecture Notes in Computer Sciencee cues are not shared. In this paper, we propose a system for facilitating turn-taking through the sharing of gaze cues in multi-party video conferences. We implemented video conferencing systems that use arrows and modification of the video window size to share gaze cues the same as in face-to-face

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Automatic Content Analysis of Student Moral Discourse in a Collaborative Learning Activityte the learning tasks, in order to provide guidance and feedback. Without appropriate technological means that support the processes of collection and selection of students’ generated responses, these duties can result in a high cognitive load for teachers, especially if students generate textual, q

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Learning Gains in Pyramid Computer-Supported Collaboration Scripts: Factors and Implications for Desteraction and learning. Despite CSCL research has shown these benefits for some scripts in particular contexts, more evidence is needed about to what extent learning gains are actually achieved for more families of scripts and in different conditions of implementation. This paper studies how three C

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Emotion Annotation of Music: A Citizen Science Approachre is a particular interest in developing algorithms to “predict” the emotions in music perceived by or induced to a listener. However, the gathering of reliable “ground truth” data for modeling the emotional content of music poses challenges, since tasks related with annotations of emotions are tim