Enhancing knowledge management in online collaborative learning

This study aims to explore two crucial aspects of collaborative work and learning: on the one hand, the importance of enabling collaborative learning applications to capture and structure the information generated by group activity and, on the other hand, to extract the relevant knowledge in order to provide learners and tutors with efficient awareness, feedback and support as regards group performance and collaboration. To this end, in this paper we first propose a conceptual model for data analysis and management that identifies and classifies the many kinds of indicators that describe collaboration and learning into high-level aspects of collaboration. Then, we provide a computational platform that, at a first step, collects and classifies both the event information generated asynchronously from the users' actions and the labeled dialogues from the synchronous collaboration according to these indicators. This information is then analyzed in next steps to eventually extract and present to participants the relevant knowledge about the collaboration. The ultimate aim of this platform is to efficiently embed information and knowledge into collaborative learning applications. We eventually suggest a generalization of our approach to be used in diverse collaborative learning situations and domains

Assessing WebCT and Moodle for Collaborative Learning of ESP

[Abstract] Two versions of Moodle and WebCT have been analyzed considering their collaborative language learning tools and the instructional design of two ESP subjects. The instructional design is based on constructivist pedagogy and peer collaboration, as well as five systems adapted from the emerging mobile learning paradigm: team memory, team communication, team awareness, team workplace and team assessment. The results of the analysis are not quite satisfactory as none of the two Virtual Learning Environments provide enough tools to design efficient and satisfactory ESP team-focussed activities

Efficient interaction analysis for an effective provision of knowledge about the discussion process to CSCL practices

The discussion process plays an important social task in Computer-Supported Collaborative Learning (CSCL) where participants can discuss about the activity being performed, collaborate with each other through the exchange of ideas that may arise, propose new resolution mechanisms, as well as justify and refine their own contributions and thus acquire new knowledge. Indeed, learning by discussion when applied to collaborative learning scenarios can provide significant benefits for students in collaborative learning, and in education in general. However, the discussion process in the context of distance education presents high drop out in comparison to traditional programs due chiefly to a sense of isolation of participants who do not have knowledge about others nor they can compare their own progress and performance to the group. To alleviate this problem, the provision of appropriate knowledge from the analysis of on-line interaction is rapidly gaining popularity due to its great impact on the discussion performance and outcomes. This implies a need to capture and structure all types of information generated by group activity and then to extract the relevant knowledge in order to provide participants with efficient awareness and feedback as regards group performance and collaboration. As a result, it is necessary to process and analyzed complex event log files from group activity in a constant manner, and thus it may require computational capacity beyond that of a single computer. To this end, in this paper we show how a Grid approach can considerably increase the overall efficiency of processing group activity log files and thus allow discussion participants to receive effective knowledge even in real time. The context of this study is a real discussion experience that took place at the Open University of Catalonia (UOC).Peer ReviewedPostprint (published version

Context-Sensitive Awareness Services for Communities of Practice

The eLogbook is a Web-Based collaborative environment particularly adapted to the needs of communities of practice. It is deployed at the Swiss Federal Institute of Technology in Lausanne (EPFL) and developed within the framework of the Palette European Project. This paper presents the eLogbook “Context- Sensitive View” intended to increase the environment usability and acceptability by communities of practice and to support collaboration and communication by embedding different types of awareness “cues” within an innovative user- friendly interface

From mirroring to guiding: A review of the state of art technology for supporting collaborative learning

We review systems that support the management of collaborative interaction, and propose a classification framework built on a simple model of coaching. Our framework distinguishes between mirroring systems, which display basic actions to collaborators, metacognitive tools, which represent the state of interaction via a set of key indicators, and coaching systems, which offer advice based on an interpretation of those indicators. The reviewed systems are further characterized by the type of interaction data they assimilate, the processes they use for deriving higher-level data representations, and the type of feedback they provide to users

Cooperation model for learning: a system of patterns

Learning is frequently assumed as a natural result of projects performed by groups, and cooperative work tools disposal within a computational environment is enough to motivate or to induce cooperation among participants. However, many times cooperation simply does not happen within the environments, or it has to be externally articulated by a tutor. We claim that CSCL environments should be built under na explicit cooperation model to be efficient. The goal of this work is to present a Cooperation Model for Learning which is described through patterns, and to contextua1ize it within a software engineering approach to facilitate the development of environments aimed at generating an effective cooperation learning process

A review of the empirical studies of computer supported human-to-human communication

This paper presents a review of the empirical studies of human-to-human communication which have been carried out over the last three decades. Although this review is primarily concerned with the empirical studies of computer supported human-to-human communication, a number of studies dealing with group work in non-computer-based collaborative environments, which form the basis of many of the empirical studies of the recent years in the area of CSCW, are also discussed. The concept of person and task spaces is introduced and then subsequently used to categorise the large volume of studies reported in this review. This paper also gives a comparative analysis of the findings of these studies, and draws a number of general conclusions to guide the design and evaluation of future CSCW systems

Semantics-supported cooperative learning for enhanced awareness

Awareness is required for supporting all forms of cooperation. In Computer Supported Collaborative Learning (CSCL), awareness can be used for enhancing collaborative opportunities across physical distances and in computer-mediated environments. Shared Knowledge Awareness (SKA) intends to increase the perception about the shared knowledge, students have in a collaborative learning scenario and also concerns the understanding that this group has about it. However, it is very difficult to produce accurate awareness indicators based on informal message exchange among the participants. Therefore, we propose a semantic system for cooperation that makes use of formal methods for knowledge representation based on semantic web technologies. From these semantics-enhanced repository and messages, it could be easier to compute more accurate awareness

Team Knowledge Networks, Task Dependencies and Coordination: Preliminary Findings from Software Teams

Today’s work increasingly involves teams with fluid boundaries, and members working on multiple projects at a time. To understand how work is effectively coordinated in such complex organizations, we focus on the role of a company’s task dependency network. We integrate three research streams – coordination, team knowledge and social networks to conceptualize multiteam work as a large collaboration with members in multiple functional roles and areas of expertise, with complex task dependency relationships, operating as a coherent and well-coordinated knowledge network. Through this integration and empirical test of associated hypotheses with data from a European software company, our study illustrates how to represent multiple relationships in one complex multiplex network. This extends our understanding of how the various knowledge relationships and individual attribute differences influence the effective coordination in collaborative software development work. We address the concepts of awareness and shared familiarity and how they affect coordination, while keeping our focus on illustrating the power of network analytics to gain nuanced insights into the drivers of effective coordination

Taxonomía de mecanismos de <i>awareness</i>

En el contexto de los sistemas de trabajo colaborativo mediado por tecnología, un grupo puede ser visto como un conjunto de individuos que interactúan directamente o por medio de artefactos compartidos y que se perciben a si mismos como un grupo. En gran parte, estas percepciones se logran a través de mecanismos de awareness. En este trabajo se presenta una comparación de los mecanismos de awareness estudiados, y se propone una Taxonomía de este tipo de mecanismos.XI Workshop Tecnología Informática Aplicada en EducaciónRed de Universidades con Carreras en Informática (RedUNCI