Media Research Center

About: Media Research Center is a based out in . It is known for research contribution in the topics: Collaborative learning & Educational technology. The organization has 491 authors who have published 950 publications receiving 28581 citations. The organization is also known as: MRC.

Multimodal Engagement Analysis from Facial Videos in the Classroom

Abstract: Student engagement is a key construct for learning and teaching. While most of the literature explored the student engagement analysis on computer-based settings, this paper extends that focus to classroom instruction. To best examine student visual engagement in the classroom, we conducted a study utilizing the audiovisual recordings of classes at a secondary school over one and a half month's time, acquired continuous engagement labeling per student (N=15) in repeated sessions, and explored computer vision methods to classify engagement levels from faces in the classroom. We trained deep embeddings for attentional and emotional features, training Attention-Net for head pose estimation and Affect-Net for facial expression recognition. We additionally trained different engagement classifiers, consisting of Support Vector Machines, Random Forest, Multilayer Perceptron, and Long Short-Term Memory, for both features. The best performing engagement classifiers achieved AUCs of .620 and .720 in Grades 8 and 12, respectively. We further investigated fusion strategies and found score-level fusion either improves the engagement classifiers or is on par with the best performing modality. We also investigated the effect of personalization and found that using only 60-seconds of person-specific data selected by margin uncertainty of the base classifier yielded an average AUC improvement of .084. 4.Our main aim with this work is to provide the technical means to facilitate the manual data analysis of classroom videos in research on teaching quality and in the context of teacher training.

Coping with bad-mouthing in peer-to-peer file sharing networks

Abstract: In the recent years, the P2P file sharing systems have adopted rating systems in the hope to stop the propagation of bad files. In a rating system, users rate files after downloading and a file with positive feedback is considered a good file. However, a dishonest rater can undermine the rating system by giving positive rating to bad files and negative rating to good files. In this paper, we design two filters based on probabilistic models such that the good files with negative feedback are not completely kept out of the system. The first filter is based on the binomial distribution of the ratings of a file, and the second filter considers the confidence of the downloading peer and the difference of positive and negative ratings of a file to calculate the probability to take a risk to download the file or reject it. Our filters only need the ratings of a file and this makes them suitable for popular torrent sharing websites that rank the files using a binary rating system without any information about raters. In addition, we can implement them entirely on the client side without any modification to the content sharing sites.

Patterns of Social Practice: A Psychological Perspective

Abstract: In the past decades, a collection of widely accepted (design) patterns has been developed, as descriptions that externalize and document the implicit knowledge of experts in the domain of software engineering. The idea of using patterns to describe complex software problems, and to offer an analytical framework to solve these problems, seems to be a good way to transfer and discuss social practice as well. Recently, some efforts to use patterns in the field of e-learning and education have been shown. In this chapter, the application of patterns in the context of social practice will be considered from a psychological point of view. After briefly introducing the history of patterns, this chapter will discuss the specific conditions that apply for formulating and using patterns of social practice, as well as the benefits and challenges of their application. This discussion will result in four main challenges. In order to address them, the chapter presents psychological approaches that deal with the relevant issues and help to understand potential benefits of patterns of social practice. It concludes with some remaining open questions for future research. The entire chapter focuses on the structure that patterns provide, and how this structure supports the communication, exchange, and learning of social practice. The discussion

Augmented telexistence in smart space

Abstract: In this paper, we present the new environment for telexistence using our smart space which we have built for interactive space. We've developed several component modules for telexistence, such as display module for large scale display system, interaction module for multimodal interaction, video module for streaming and rendering module for augmented composition in our smart space. Those systems are well-integrated and allow for augmented telexistence functionality which is more natural and also give a beyond face-to-face communication between remote users. Based on our proposed environment, we can create new possibilities for immersive and interactive communication across the space.

Design and verification of the procedure for interoperability between video surveillance systems

Abstract: This paper proposes a design of the procedure for interoperability between video surveillance systems and verifies whether these systems are interworked according to the designed interworking procedures. In order to verify the interworking procedure of video surveillance systems, we implemented interoperability verification monitoring system. Through implementation results, we prove that video surveillance systems are well interworked based on designed interoperability procedures.