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About 10,000 papers for “collaborative work environment”

Environment to Environment (E2E) Communication Systems for Collaborative Work

Ish Rishabh, Vivek K. Singh, Hamed Pirsiavash et al. · 2008

E2E is an initiative to harness the power of the World Wide Web (WWW) along with intelligent sensing of environments, to provide effective bi-directional communication which is free from the limitations imposed by devices. Through a sentient information system, automatic selection of the best media streams can be done. Thus, the user need not worry about the location of sensors and presentation devices. Moreover, various forms of interactions can be supported through the capabilities provided by the Web. Hence, apart from point-to-point communication, social networking, virtual meetings, shared collaborative work and asynchronous communication can also be done. The ability to index, archive, retrieve and search event-specific multimedia enhances the versatility of communication.

Cited by 1

Next Generation Integrated Environment for Collaborative Work Across Internets

Harvey B. Newman · OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) · 2009

We are now well-advanced in our development, prototyping and deployment of a high performance next generation Integrated Environment for Collaborative Work. The system, aimed at using the capability of ESnet and Internet2 for rapid data exchange, is based on the Virtual Room Videoconferencing System (VRVS) developed by Caltech. The VRVS system has been chosen by the Internet2 Digital Video (I2-DV) Initiative as a preferred foundation for the development of advanced video, audio and multimedia collaborative applications by the Internet2 community. Today, the system supports high-end, broadcast-quality interactivity, while enabling a wide variety of clients (Mbone, H.323) to participate in the same conference by running different standard protocols in different contexts with different bandwidth connection limitations, has a fully Web-integrated user interface, developers and administrative APIs, a widely scalable video network topology based on both multicast domains and unicast tunnels, and demonstrated multiplatform support. This has led to its rapidly expanding production use for national and international scientific collaborations in more than 60 countries. We are also in the process of creating a 'testbed video network' and developing the necessary middleware to support a set of new and essential requirements for rapid data exchange, and a high level of interactivity in large-scale scientific collaborations. These include a set of tunable, scalable differentiated network services adapted to each of the data streams associated with a large number of collaborative sessions, policy-based and network state-based resource scheduling, authentication, and optional encryption to maintain confidentiality of inter-personal communications. High performance testbed video networks will be established in ESnet and Internet2 to test and tune the implementation, using a few target application-sets.

Cited by 0Open access

Communication process and collaborative work in Web 2.0 environment

Eun‐Jin Kim, JoongHo Ahn, Dongwon Lee · 2009

Because the higher level of media richness improves the performance of collaborative works such as knowledge sharing, efforts to raise media richness are encouraged. The Channel Expansion Theory argues that individuals' perceptions of media richness vary according to each individual's knowledge base built from prior experiences related to the communication situation. This study explored the channel expansion effects in the new CMC environment, Web 2.0. In particular, we considered communication process modes (i.e., conveyance and convergence) as a factor moderating the effects. The research model was verified by an experiment with student subjects.

Cited by 0

Dynamics of Collaborative Work in Global Software Development Environment

Swigger, Kathleen, Alpaslan, Ferda Nur, Brazile, Robert et al. · OpenMETU (Middle East Technical University) · 2009

This study aims to explore the dynamics of collaborative work in global software development projects. The study explored the nature of collaboration, the patterns of collaborative behaviors in different tasks in computer science, and the impact of the tasks to the collaboration among students. Four different collaborative software development tasks were assigned to the globally distributes teams. The study used data from 230 students from five universities, namely Atilim University (Turkey), Middle East Technical University (Turkey), Universidad Tecnologica de Panama (Panama), University of North Texas (US), and Middlesex University (UK). The findings involve the recommendations for building effective collaborative working environments and guidelines for building collaborative virtual communities.

Cited by 0

Intelligent support in group work in online collaborative learning environment

Maina, Elizaphan M. · University of Nairobi Research Archive (University of Nairobi) · 2015

The increased demand for higher education has made online learning popular and
\nappealing to many stakeholders including working staff and students. Though online
\nlearning has gained popularity, it is still being criticized for being a faceless medium
\nthat does little to support social interaction. Social constructivist argue that knowledge
\nis constructed through social activities and therefore, knowledge developed using
\ncollaboration is more than what can be achieved by an individual alone. Online
\nlearning, if supported by a good collaborative strategy like discussion forums, can be
\nat par with social constructivist view of learning in terms of learning achievement.
\nLearning Management Systems such as Modular Object-Oriented Dynamic Learning
\nEnvironment (Moodle) supports online tools that include discussion forums, chat
\nrooms, e-mails, newsgroups, workshops, etc. These tools provide new opportunities for
\nstudents to collaborate online and construct knowledge through peer learning. Despite
\nthe pedagogical advantages of collaborative learning, online learners can perceive the
\ncollaborative learning process as challenging. Although a number of challenges have
\nbeen mentioned in the literature, they do not have empirically grounded evidence
\nand therefore overcoming these challenges remains an issue. In light of this and the
\nincreasing demand for online learning, this research aimed at investigating the current
\nstatus of online collaborative learning in Higher Learning Institutions in Kenya, identify
\nperceived challenges, and explore strategies for improving online collaborative learning
\nthrough intelligent support techniques such as machine learning.
\nTo that end, this research was designed using a Multi-Methodological approach in
\norder to develop and validate a prototype which provided a novel approach through
\nintelligent support techniques for group formation based on students’ collaboration
\ncompetence level and a platform to provide immediate feedback in Moodle. The
\nfirst part of the methodology was a cross-sectional survey which was used to carry
\nout a pre-study to investigate the current status of online collaborative learning
\nand students’ perceived challenges in an online collaborative learning environment
\nv
\nin Higher Learning Institutions in Kenya. This pre-study informed the system
\ndevelopment and the validation processes for the prototype. The second part of
\nmethodology was the system development methodology which guided the development
\nof the prototype. The final part of the methodology an experimental design that was
\ncarried out to evaluate the effectiveness of the intelligent module on the formation of
\ndiverse groups and the impact of the group formation method on group performance
\nin an online collaborative learning environment. In this study three groups were used,
\nwhere in group one students were assigned into groups using grade point average scores
\n, in group two students were assigned into groups using intelligent grouping algorithm
\nand in group three students were assigned into groups using the random method.
\nThe novel approach for group formation using machine learning techniques was
\nfound capable of forming heterogeneous groups that tended to perform effectively
\nand efficiently at the same level as the random method and the grade point average
\nmethod. There was no statistical significance in differences associated with the
\nthree methods of group formation and performance in a group task. Furthermore,
\nall the three groups had similar positive learning experiences and had few common
\nchallenges. With the understanding that random assignment method only increases the
\nlikelihood of heterogeneity in the group and grade point average method involves the
\ninstructors and it is not dynamic, our proposed intelligent grouping algorithm has the
\nadvantage of guaranteeing heterogeneity based on learner’s collaboration competence
\nlevel, dynamism in grouping students and less instructor involvement. Due to these
\nadvantages, instructors are more likely to adopt our intelligent grouping technique.
\nFurther studies should also be conducted to compare the intelligent grouping with other
\ngroup assignment methods which were not studied in this study.

Cited by 0

Intelligent Support in Group Work In Online Collaborative Learning Environment

Muuro Maina Elizaphan · 2015

The increased demand for higher education has made online learning popular and appealing to many stakeholders including working staff and students. Though online learning has gained popularity, it is still being criticized for being a faceless medium that does little to support social interaction. Social constructivist argue that knowledge is constructed through social activities and therefore, knowledge developed using collaboration is more than what can be achieved by an individual alone. Online learning, if supported by a good collaborative strategy like discussion forums, can be at par with social constructivist view of learning in terms of learning achievement. Learning Management Systems such as Modular Object-Oriented Dynamic Learning Environment (Moodle) supports online tools that include discussion forums, chat rooms, e-mails, newsgroups, workshops, etc. These tools provide new opportunities for students to collaborate online and construct knowledge through peer learning. Despite the pedagogical advantages of collaborative learning, online learners can perceive the collaborative learning process as challenging. Although a number of challenges have been mentioned in the literature, they do not have empirically grounded evidence and therefore overcoming these challenges remains an issue. In light of this and the increasing demand for online learning, this research aimed at investigating the current status of online collaborative learning in Higher Learning Institutions in Kenya, identify perceived challenges, and explore strategies for improving online collaborative learning through intelligent support techniques such as machine learning. To that end, this research was designed using a Multi-Methodological approach in order to develop and validate a prototype which provided a novel approach through intelligent support techniques for group formation based on students’ collaboration competence level and a platform to provide immediate feedback in Moodle. The first part of the methodology was a cross-sectional survey which was used to carry out a pre-study to investigate the current status of online collaborative learning and students’ perceived challenges in an online'-collaborative learhing environment in Higher Learning Institutions in Kenya. This pre-study informed the system development and the validation processes for the prototype. The second part of methodology was the system development methodology which guided the development of the prototype. The final part of the methodology an experimental design that was carried out to evaluate the effectiveness of the intelligent module on the formation of diverse groups and the impact of the group formation method on group performance in an online collaborative learning environment. In this study three groups were used, where in group one students were assigned into groups using grade point average scores , in group two students were assigned into groups using intelligent grouping algorithm and in group three students were assigned into groups using the random method. The novel approach for group formation using machine learning techniques was found capable of forming heterogeneous groups that tended to perform effectively and efficiently at the same level as the random method and the grade point average method. There was no statistical significance in differences associated with the three methods of group formation and performance in a group task. Furthermore, all the three groups had similar positive learning experiences and had few common challenges. With the understanding that random assignment method only increases the likelihood of heterogeneity in the group and grade point average method involves the instructors and it is not dynamic, our proposed intelligent grouping algorithm has the advantage of guaranteeing heterogeneity based on learner’s collaboration competence level, dynamism in grouping students and less instructor involvement. Due to these advantages, instructors are more likely to adopt our intelligent grouping technique. Further studies should also be conducted to compare the intelligent grouping with other group assignment methods which were not studied in this study.

Cited by 0

TeamBuilder: a hyper-information environment for augmenting global collaborative work

Achim P. Karduck · 2002

In this paper, the design and use of TeamBuilder, a new CSCW concept and prototype that demonstrates how to support team building and teamwork by combining elements of network-wide hypermedia, group user interfaces and coordination technology, is described. TeamBuilder enables the building of hyper-information networks as a group activity, and offers coordination support that is flexible in terms of human involvement. It takes advantage of the shift from centralized to decentralized configurations of systems architectures, where information generation and structuring can be done in the user's personal working environment.

Cited by 3

Research on a developing environment for computer supported collaborative work

NI Xiao-hong · 2012

Collaborative product development is an engineering process that involves decision-making through iterative communication and coordination among product designers throughout the lifecycle of product. In order to increasing openness and flexibility, a framework of distributed platform for collaborative design based on Web services and Agent technology is proposed. Web services are the foundation of system, and Agent technology is applied to accessing and updating information. Subsequently, the structure and communication of Agent is studied, and dynamic behavior of system is described and designed. Finally, deployment and achievement of a system prototype shows the feasibility of this method.

Cited by 0