Collaboration and Technology

Because collective decision processes are central to the management function of most organizations, it is important to understand them better and to improve them if possible. One common view of group decision processes is that they should offer participants the opportunity to confront and resolve the differences in their points of view. New cognitive and technical tools may help to facilitate the sharing of individuals’ reasoning and preferences, but only if they do not require participants to reveal information that they wish to keep private, perhaps for strategic or personal reasons. The aim of this study is to test experimentally one such approach, contained in the Group Decision Support System, GRUS, which allows decision makers to use a multi-criteria approach to problem structuring that can involve both public (shared) and private criteria.

For enterprises today, in order to create new business, it is becoming more important to understand customers’ business context, their potential problems, and their challenges rather than thinking of ideas to solve widely known problems. In these cases, many companies will provide a special type of facility similar to a showroom which we call a “Co-creation Showroom” in order to understand customers’ business context and challenges.

This work analyzes the communication process of the “Co-creation Showroom” and identifies several key factors for successful dialogue between facilitators and customers. This work also introduces a new communication process using new communication tools as well as evaluations of this process.

In animations and video games, Digital Elevation Maps (DEMs) are commonly used to model geometric assets, e.g., terrains on a landscape. When a DEM is edited by a group of collaborators, they are constrained to access the elevation data from their PC following a turn-taking policy, since most of the applications are essentially single-user. Furthermore, the DEM is visualized in 2D, causing some degree of confusion to new users when imagining the DEM shape in 3D. In this paper, we propose a novel approach to the collaborative modeling of DEMs on mobile devices. Our approach uses Augmented Reality (AR) to help collaborators to easily understand the DEM’s 3D representation and provides them with basic editing tools to modify the DEM shape in an intuitive manner. In addition, we implement an object sharing scheme, in order to support face-to-face interaction in real-time. By means of this approach, it is possible to create an original collaboration setting, in which a group of collocated colleagues, each carrying a mobile device, can concurrently create and modify the same DEM, while visualizing it using AR-technology. As shown by our results, the workload perceived by the users of our DEM editor is small.

In theatrical performance, actors are required to understand the libretto as they act. However, actors often make mistakes in their actions in early stages of practice when they still do not understand the libretto. This stops the flow of the practice. In order to learn action, it is necessary to coordinate a smooth group practice. We propose a system that supports actors in grasping the action. This system detects the actor’s speech, and cues the order of actions for each actor. In the evaluation, both mistakes in order and in speech were decreased. We confirmed that this system can support theatrical performance practice efficiently.

People who have to insert and adapt themselves to a different culture than the one where they grew up usually experience feelings related to anxiety and uncertainty. This is exactly the situation of the students who decide to go abroad to continue their education or make an internship in a foreign country. The number of these students has been constantly increasing during the last years. In order to better adapt themselves to the new culture they are confronted with the Anxiety/Uncertainty Model, states that they have to manage the levels of anxiety and uncertainty in order to communicate effectively with local students and teachers. According to the literature, an effective communication and intercultural adjustment of the foreign students has a direct impact on their academic performance. Therefore, it is a relevant task to support them in this process. This work introduces a geo-collaborative application called EMHC (for Exploring My Host Country) which run son mobile devices and allows exchange students to access contextual information as well as information about cultural behavior which could help them to manage their anxiety and uncertainty levels, thus improving their ability to adapt themselves to the new cultural environment. A preliminary evaluation of the EMHC was performed with a small number of exchange students of a Business School, obtaining encouraging results.

Collaborative work involving teams and individuals distributed across the globe is an inevitable trend. Because of that, the expertise is getting increasingly distributed and we have seen a growing need for technologies to support remote collaboration. Despite this need, the differences of technologies used to support remote collaboration are unknown, especially considering different kinds of physical tasks, such as analytical tasks and construction tasks. In order to better understand their impact on collaborative behaviors, perceptions, and performance, we conducted a lab setting study to evaluate two different arrangements of technology: a handheld model and a hands-free model. These models were compared for both, analytical and construction tasks. Our results suggest us that hands-free setting is more suitable for analytical tasks, while the handheld setting is more suitable for construction tasks. These differences among technological setups for remote collaboration on physical tasks motivate additional studies, especially long-term studies in natural settings, which could investigate aspects of collaboration that may not have been explored on our lab setting study.

Asynchronous participation in volunteering social systems is mainly based on various communication and collaboration tools. Supporting creativity in such groups during the process of concept generation is one major challenge to reach high quality working results. This paper presents a collaboration tool supporting the creative process of concept generation. The solution focuses the support of a concrete social system with loose structures and that aims open participation, as discussed in a case study. At the end, the paper shows an evaluation of the solution itself with regards to the described social system.

In this paper we present an empirical study of the effectiveness of tablet-based interaction for users of a tabletop shared virtual workspace. We built a tabletop interaction environment in which tablet terminals present sliding windows onto a larger, shared virtual workspace, allowing multiple users to view and manipulate objects within the workspace. The environment offers a physical paradigm to support groupwork within the shared virtual space, providing users with good situational awareness of their viewing position with respect both to the viewing positions of other users and to the location of content within the large virtual workspace. We conducted experiments to compare ‘tablet scrolling’ with a more traditional ‘swipe-scroll’ paradigm for the ease remembering the positions of objects, locating the viewable area within the overall workspace, and communicating locations between users during groupwork. The results show that the tabletop interaction environment enables workers to communicate more effectively than ‘swipe-scroll’ paradigms, although difficulties associated with scrolling and physical movement may decrease the efficiency of individual work.

In this paper we propose several new measures to characterize sets of scientific papers that provide an overview of a scientific topic. We present a study in which experts were asked to name such papers for one of their areas of expertise and apply the measures to characterize the paper selections. The results are compared to the measured values for random paper selections. We find that the expert selected sets of papers can be characterized to have a moderately high diversity, moderately high coverage and each paper in the set has on average a high prototypicality.

Through Online Social Networks, like Research Gate, Stack Exchange or Facebook, it’s easy to find a partner for cooperation, because Social Networks have the potential to connect thousands of people. To assist finding the right person for cooperation many of these networks have Recommender-Systems, but these systems mostly rely on the matching of keywords for each individual. This article shows on a conceptual level, that current Recommender-Systems for cooperation on Online Social Networks can be improved by additionally using personality for recommendations. Methods like Language Inquiry and Word Count (LIWC) can help to achieve this goal by presenting methods for an automated calculation of personality from user-generated content in these networks, without the need of questionnaires. Based on personality different cooperation types can be derived to improve recommendations for cooperation partners, leading to a better cooperation and therefore help to increase cooperation in Online Social Networks.

How learning occurs within Free/Libre Open Source (FLOSS) communities and what is the dynamics of such projects (e.g. the life cycle of such projects) are very relevant questions when considering the use of FLOSS projects in a formal education setting. This paper introduces an approach based on the 3C collaboration model (communication, coordination and cooperation) to represent the collaborative learning dynamics within FLOSS communities. To explore the collaborative learning potential of FLOSS communities a number of questionnaires and interviews to selected FLOSS contributors were run. From this study a 3C collaborative model applicable to FLOSS communities was designed and discussed.

This paper presents an approach to group recommender systems that focuses its attention on the group’s social interaction during the formulation, discussion and negotiation of the features the item to be jointly selected should possess. The system supports a collaborative preference elicitation and negotiation process where desired item features can be defined individually, but group consensus is needed for them to become active in the item filtering process. Users can provide feedback on other members’ preferences and change their significance, bringing up new recommendations each time individual settings are modified. The last stage in the decision process is also supported, when users collectively select the final item from the recommendation set. We developed the prototype hotel recommender Hootle+ and evaluated it in a user study involving groups of different size. The results indicate a good overall satisfaction, which increases with group size. However, the success ratio for bigger groups is lower than for small groups, raising questions for follow-up research.

This paper proposes a prototype system that collaborates smartwatches with traditional video surveillance security. By combining concepts of user-centered design, ubiquitous wearable, psychophysiology and Internet of Things (IoTs), we present the upgraded video surveillance system where heart rate-based anomalies can automatically trigger the alarm. As a first prototype, the system was limited to library-like experimental setups and the anomaly was defined by arousal heart rate—unusually high heart beats. Using a smartwatch and a simple three-question questionnaire, we were able to collect referential arousal heart rate data from 25 healthy subjects together with their individual rating scores regarding three habit factors—smoking, drinking alcohol and eating fatty foods. According to our semi-quantitative user testings in a controlled library environment, the prototype was able to wirelessly connect and synchronize all devices, send the alarm, and perform real-time heart rate measurement as well as calculation. Based on confusion matrix evaluation, our anomaly detection gave promising results of 95 % accuracy and 90 % precision. However, major revision was required for the anomaly detection to cover unobserved factors, and there were serious usability problems regarding the smartwatch to be fixed.