3,186 research outputs found

    Detecting Low Rapport During Natural Interactions in Small Groups from Non-Verbal Behaviour

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    Rapport, the close and harmonious relationship in which interaction partners are "in sync" with each other, was shown to result in smoother social interactions, improved collaboration, and improved interpersonal outcomes. In this work, we are first to investigate automatic prediction of low rapport during natural interactions within small groups. This task is challenging given that rapport only manifests in subtle non-verbal signals that are, in addition, subject to influences of group dynamics as well as inter-personal idiosyncrasies. We record videos of unscripted discussions of three to four people using a multi-view camera system and microphones. We analyse a rich set of non-verbal signals for rapport detection, namely facial expressions, hand motion, gaze, speaker turns, and speech prosody. Using facial features, we can detect low rapport with an average precision of 0.7 (chance level at 0.25), while incorporating prior knowledge of participants' personalities can even achieve early prediction without a drop in performance. We further provide a detailed analysis of different feature sets and the amount of information contained in different temporal segments of the interactions.Comment: 12 pages, 6 figure

    Towards Multimodal Analysis of Dialogic Moments in Storytelling-based Discourse

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    The key to an effective communication method arguably lies in its ability to facilitate moments of high mutual understanding (dialogic moments). It would, therefore, be useful to identify these moments and perhaps facilitate them. In this pilot study, we present a multimodal analysis of dialogic moments in storytelling-based discussions. We collected skin conductance, heartrate, speaking turns, relative body position, conversation transcripts, and subjective experience. This multimodal data corpus enables the computational study of these highly subjective moments and the potential creation of digital communication aids. Preliminary results show that there might be subcategories of dialogic moments that were previously unidentified

    Integrating project-based learning, taskbased language teaching approach and youtube in the ESP class: a study on students’ motivation

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    ESP courses have been considered as crucial for the academic training of future professionals in different areas of knowledge. Their broad spectrum mainly includes the mastery of a foreign language, the learning of specific terminology, and the development of skills related to students’ career needs. Recent research has examined the implementation of the task-based language teaching approach, the design and accomplishment of projects, and the use of technology for the enhancement of digital competence. Nevertheless, few studies have addressed the combination of these three key elements in the ESP class and its effects on students’ motivation. This study examines the effects of merging of project-based learning sequenced into different communicative tasks on ESP students’ motivation. A research project was designed and structured in communicative tasks integrating the use of YouTube as a source of multimodal input. To measure motivation, an adaptation of the intrinsic motivation questionnaire was administered to students. Results reveal high mean scores in the motivation subscales studied along with positive correlations between motivation and participants’ academic performance. These findings may contribute to the body of research that appraises the value of merging different teaching methodologies and approaches for the teaching and learning of ESP disciplines

    Multiliteracies meaning-making: How four boys’ video gaming experiences influence their cultural knowledge—Two ethnographic cases

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    Scholars have acknowledged the potential contribution of video gaming to complex forms of learning, identifying links between gaming and engagement, experiential learning spaces, problem-solving, strategies, transliteracy reflectivity, critical literacy, and metacognitive thinking. Despite this movement toward the inclusion of video gaming in literacy teaching, concerns about certain risks raised by scholars have slowed the adoption of using video games to foster learning. Using a multiliteracies lens, this multi-case study examined the experiences of four boys engaged with video gaming in two different contexts: a community centre and an after-school video club. By drawing on Feminist Post-Structural Theory, Vygotskian, and video gaming technology, I have gained an understanding of the nature of boys’ behavior and learning in social settings while they engage in video game play. Studying the ways in which boys make meanings through multimodal ways of learning can offer insights into strategies that can potentially reinvent traditional literacy pedagogical boundaries and establish new ways and practices for building knowledge. These ethnographic cases, along with their naturalistic aspects, strengthened the authenticity of the social-contextual-cultural experiences of the four, adolescent-aged boys and allowed an understanding of their everyday experiences. Interpretations of the cultural meanings made by each of the boys, based on their individual unique experiences engaging with video games, can provide readers with insights into how to approach adolescent aged boys’ literacy development. This study describes how these four boys developed their multimodal ways of learning by engaging with visual perspectives of video games. My methodological approach documented what boys are saying, as much as possible, which is currently understudied in the literature surrounding boys and their video gaming practices. There were a number of findings emanating from this study, including the following: (i) boys use their video gaming practices for meaning-making and collaborative efforts in order to gain an understanding of several knowledge processes (such as decision-making, predicting, analyzing, strategizing, etc.), (ii) boys extend and apply their cultural knowledge as creative innovators, producing and publishing YouTube instructional videos for video game players and designing video games for a history project, (iii) boys demonstrate peer mentoring through storytelling, face-to-face interactions or in their online community of practice, (iv) boys make meanings using metacognitive literacy skills in a variety of ways, and (v) boys focus on cultural preservation and narrative storytelling. While acknowledging concerns related to video gaming, such as negative identity construction, violence, distraction, and time commitment for integration, this study seeks to contribute to the scholarly discussion about the use of video games in classrooms by explicitly considering the ways in which gaming may support boys’ meaning-making and cultural knowledge. Keywords Available designs, boys, community of practice, cultural meaning-making systems, literacy, multiliteracies, multimodal meanings, video gamin

    The promise and challenges of multimodal learning analytics

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    Cerita (Stories): A Pedagogical Model for Teaching Story Genres to Lower Secondary School Students in Indonesia

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    Teacher professional learning programs often aim to support teachers to develop new knowledge or instructional practices in order to improve students’ learning outcomes. However, connecting these knowledge and skills to the teachers’ specific context remains a challenge. The gap is even wider in contexts of teaching English as a foreign language (EFL), such as Indonesia, where pedagogical frameworks adopted for English language curriculum have been developed for use in language settings a long way from most EFL situations (see Baker, 2016; Canagarajah, 2016; Chaaban, 2017). As such, the contents of professional learning are commonly perceived as propaganda for vested interests, and unrelated to local classroom realities (Fang, 2012). This study investigates the potential of a professional learning program based on genre theory (after Martin, 1985; Martin & Rose, 2008) a model that underpins the current English language curriculum for secondary school students in Indonesia. The design and implementation of the program in the study are drawn from Reading to Learn (R2L) (Rose & Martin, 2012), a scaffolded approach to literacy education that has developed from systemic functional theory as developed by Halliday and his colleagues (e.g. Halliday, 1975; Halliday & Matthiessen, 2014; Rose & Martin, 2012). The program described in this study offered workshops, supported pedagogy and ongoing dialogue to promote a story-oriented renovation of R2L, incorporating story sharing activities such as multimodal storytelling and scripted performances as an additional learning stage in order to enhance secondary students’ control of writing story genres in English

    Capturing the Visitor Profile for a Personalized Mobile Museum Experience: an Indirect Approach

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    An increasing number of museums and cultural institutions around the world use personalized, mostly mobile, museum guides to enhance visitor experiences. However since a typical museum visit may last a few minutes and visitors might only visit once, the personalization processes need to be quick and efficient, ensuring the engagement of the visitor. In this paper we investigate the use of indirect profiling methods through a visitor quiz, in order to provide the visitor with specific museum content. Building on our experience of a first study aimed at the design, implementation and user testing of a short quiz version at the Acropolis Museum, a second parallel study was devised. This paper introduces this research, which collected and analyzed data from two environments: the Acropolis Museum and social media (i.e. Facebook). Key profiling issues are identified, results are presented, and guidelines towards a generalized approach for the profiling needs of cultural institutions are discussed

    Collocated Collaboration Analytics: Principles and Dilemmas for Mining Multimodal Interaction Data

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    © 2019, Copyright © 2017 Taylor & Francis Group, LLC. Learning to collaborate effectively requires practice, awareness of group dynamics, and reflection; often it benefits from coaching by an expert facilitator. However, in physical spaces it is not always easy to provide teams with evidence to support collaboration. Emerging technology provides a promising opportunity to make collocated collaboration visible by harnessing data about interactions and then mining and visualizing it. These collocated collaboration analytics can help researchers, designers, and users to understand the complexity of collaboration and to find ways they can support collaboration. This article introduces and motivates a set of principles for mining collocated collaboration data and draws attention to trade-offs that may need to be negotiated en route. We integrate Data Science principles and techniques with the advances in interactive surface devices and sensing technologies. We draw on a 7-year research program that has involved the analysis of six group situations in collocated settings with more than 500 users and a variety of surface technologies, tasks, grouping structures, and domains. The contribution of the article includes the key insights and themes that we have identified and summarized in a set of principles and dilemmas that can inform design of future collocated collaboration analytics innovations

    Graphical models for social behavior modeling in face-to face interaction

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    International audienceThe goal of this paper is to model the coverbal behavior of a subject involved in face-to-face social interactions. For this end, we present a multimodal behavioral model based on a Dynamic Bayesian Network (DBN). The model was inferred from multimodal data of interacting dyads in a specific scenario designed to foster mutual attention and multimodal deixis of objects and places in a collaborative task. The challenge for this behavioral model is to generate coverbal actions (gaze, hand gestures) for the subject given his verbal productions, the current phase of the interaction and the perceived actions of the partner. In our work, the structure of the DBN was learned from data, which revealed an interesting causality graph describing precisely how verbal and coverbal human behaviors are coordinated during the studied interactions. Using this structure, DBN exhibits better performances compared to classical baseline models such as Hidden Markov Models (HMMs) and Hidden Semi-Markov Models (HSMMs). We outperform the baseline in both measures of performance, i.e. interaction unit recognition and behavior generation. DBN also reproduces more faithfully the coordination patterns between modalities observed in ground truth compared to the baseline models
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