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This paper summarizes the third Multimodal Learning Analytics Workshop and Grand Challenges (MLA'14). This subfield of Learning Analytics focuses on the interpretation of the multimodal interactions that occurs in learning environments, both digital and physical. This is a hybrid event that includes presentations about methods and techniques to analyze and(More)
This paper identifies, by means of video and Kinect data, a set of predictors that estimate the presentation skills of 448 individual students. Two evaluation criteria were predicted: eye contact and posture and body language. Machine-learning evaluations resulted in models that predicted the performance level (good or poor) of the presenters with 68% and(More)
Multimodal Learning Analytics is a field that studies how to process learning data from dissimilar sources in order to automatically find useful information to give feedback to the learning process. This work processes video, audio and pen strokes information included in the Math Data Corpus, a set of multimodal resources provided to the participants of the(More)
This paper proposes a simple estimation of the quality of student oral presentations. It is based on the study and analysis of features extracted from the audio and digital slides of 448 presentations. The main goal of this work is to automatically predict the values assigned by professors to different criteria in a presentation evaluation rubric. Machine(More)
The traditional recording of student interaction in classrooms has raised privacy concerns in both students and academics. However, the same students are happy to share their daily lives through social media. Perception of data ownership is the key factor in this paradox. This article proposes the design of a personal Multimodal Recording Device (MRD) that(More)
This study explores the impact of a tabletop-generated feedback on student's collaborative skills over time. Twenty-one Computer Science students participated in a three-week experimentation. A two-group design was used to assess three dimensions of collaboration: contributions, communication and respect. While the experimental group was asked to solve a(More)
Data synchronization gathered from multiple sensors and its corresponding reliable data analysis has become a difficult challenge for scalable multimodal learning systems. To tackle this particular issue, we developed a distributed framework to decouple the capture task from the analysis task through nodes across a publish/subscription server. Moreover, to(More)
This study explores the design of a tabletop system that seeks to bolster the argumentative skills of Computer Science students. A set of four design guidelines - positive interdependence, stages, interference, and awareness - were derived from user research and used for designing and prototyping a multi-display tabletop application. Four students evaluated(More)
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(More)
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