It has been argued that cohesion plays a central role in collaborative learning. In face-to-face classes, it can be reckoned from several visual or oral cues. In a Learning Management System or CSCL environment, such cues are absent. In this paper, we show that Social Network Analysis concepts, adapted to the collaborative distance-learning context, can help measuring the cohesion of small groups. Working on data extracted from a 10-week distance-learning experiment, we computed cohesion in several ways in order to highlight isolated people, active subgroups and various roles of the members in the group communication structure. We argue that such processing, embodied in monitoring tools, can display global properties both at individual level and at group level and efficiently assist the tutor in following the collaboration within the group. It seems to be more appropriate than the long and detailed textual analysis of messages and the statistical distribution of participants' contributions.

Link to this article: http://journals.cambridge.org/abstract_S0958344008000426How to cite this article: Maud Ciekanski and Thierry Chanier (2008). Developing online multimodal verbal communication to enhance the writing process in an audio-graphic conferencing environment. ReCALL, 20, pp 162-182 AbstractOver the last decade, most studies in Computer-Mediated Communication (CMC) have highlighted how online synchronous learning environments implement a new literacy related to multimodal communication. The environment used in our experiment is based on a synchronous audio-graphic conferencing tool. This study concerns false beginners in an English for Specific Purposes (ESP) course, presenting a high degree of heterogeneity in their proficiency levels. A coding scheme was developed to translate the video data into user actions and speech acts that occurred in the various modalities of the system (aural, textchat, text editing, websites). The paper intends to shed further light on and increase our understanding of multimodal communication structures through learner participation and learning practices. On the basis of evidence from an ongoing research investigation into online CALL literacy, we identify how learners use different modalities to produce collectively a writing task, and how the multimodal learning interaction affects the learners' focus and engagement within the learning process. The adopted methodology combines a quantitative analysis of the learners' participation in a writing task with regard to the use of multimodal tools, and a qualitative analysis focusing on how the multimodal dimension of communication enhances language and learning strategies. By looking at the relationship between how the learning tasks are designed by tutors and how they are implemented by learners, that is to say taking into account the whole perception of multimodal communication for language learning purposes, we provide a framework for evaluating the potential of such an environment for language learning.

Three-dimensional synthetic worlds introduce possibilities for nonverbal communication in computer-mediated language learning. This paper presents an original methodological framework for the study of multimodal communication in such worlds. It offers a classification of verbal and nonverbal communication acts in the synthetic world Second Life and outlines relationships between the different types of acts that are built into the environment. The paper highlights some of the differences between the synthetic world's communication modes and those of face-to-face communication and exemplifies the interest of these for communication within a pedagogical context.We report on the application of the methodological framework to a course in Second Life which formed part of the European project ARCHI21. This course, for Architecture students, adopted a Content and Learning Integrated Learning approach (CLIL). The languages studied were French and English. A collaborative building activity in the students' L2 is considered, using a method designed to organise the data collected in screen recordings and to code and transcribe the multimodal acts. We explore whether nonverbal communication acts are autonomous in Second Life or whether interaction between synchronous verbal and nonverbal communication exists. Our study describes how the distribution of the verbal and nonverbal modes varied depending on the pre-defined role the student undertook during the activity. We also describe the use of nonverbal communication to overcome verbal miscommunication where direction and orientation were concerned. In addition, we illustrate how nonverbal acts were used to secure the context for deictic references to objects made in the verbal mode. Finally, we discuss the importance of nonverbal and verbal communication modes in the proxemic organisation of students and the impact of proxemic organisation on the quantity of students' verbal production and the topics discussed in this mode.This paper seeks to contribute to some of the methodological reflections needed to better understand the affordances of synthetic worlds, including the verbal and nonverbal communication opportunities Second Life offers, how students use these and their impact on the interaction concerning the task given to students.

Abstract. We describe a situation of distance learning based on collaborative production occurring within groups over a significant time span. For such a situation, we suggest giving priority to monitoring and not to guiding systems. We also argue that we need models which are easily computable in order to deal with the heterogeneous and the large scale amount of data related to interactions, i.e. models relying on theoretical assumptions which characterise the structures of groups and of interactions. Social Network Analysis is a good candidate we applied to our experiment in order to compute communication graphs and cohesion factors in groups. This application represents an essential part of a system which would enable tutors to detect a problem or a slowdown of group interaction.

HAL is a multidisciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

HAL is a multidisciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

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Many computer-assisted language learning systems specifically designed to be used in the curriculum and which exploit AI techniques have neither a learner model nor consequently any deep error analysis. Evidence from applied linguistics shows that learners have their own system of rules for the production of a foreign language. We believe the central issue is to determine the appropriate level of description of these rules and uncover the strategies used by the learners in particular situations. This information represents the major part of the learner model. We review error analysis in second language learning and tutoring systems related to this perspective. We introduce a new structure, called an "applicable rule", that can be used to help diagnose and to represent a learner's performance. We propose a design for the architecture of a system for computer diagnoses of learners' grammatical performances in a communicative environment. Examples of diagnosis using applicable rules illustrate the functioning of this architecture.