Towards Intelligent Interfaces for Mixed-Focus Collaboration

Sigitov, Anton; Staadt, Oliver; Hinkenjann, André

doi:10.1145/3213586.3225239

Cited by 3 publications

(5 citation statements)

References 22 publications

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“…A better solution, however, is to utilize a system that can automatically recognize the current state of collaboration tightness and adjust interaction and visualization modalities appropriately. Sigitov et al conducted some initial work in this direction (Sigitov et al, 2018a ).…”

Section: Resultsmentioning

confidence: 99%

“…The findings are important for the design of groupware systems and user interfaces. Ideally, the system should be intelligent enough to recognize users work style and appropriately adjust the interface (e.g., Sigitov et al, 2018a ). For that, researchers have to extract, categorize, and describe patterns of user and group behavior (e.g., in the form of coupling styles or user roles) in a way the system based on sensors' data could recognize them.…”

Section: Discussionmentioning

confidence: 99%

“…Previous work mostly categorizes collaborative coupling into loosely coupled and tightly coupled (Gutwin and Greenberg, 1998 , 2002 ; Tang et al, 2006 ; Isenberg et al, 2012 ). Sigitov et al also investigated transitions between loosely and tightly coupled work for group model building (Sigitov et al, 2018a ). Territoriality, on the other hand, addresses users' behavior that leads to the emergence of different regions with specific semantics and content (Scott et al, 2004 ).…”

Section: Introductionmentioning

confidence: 99%

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Task Dependent Group Coupling and Territorial Behavior on Large Tiled Displays

et al. 2019

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Large display environments are highly suitable for immersive analytics. They provide enough space for effective co-located collaboration and allow users to immerse themselves in the data. To provide the best setting-in terms of visualization and interaction-for the collaborative analysis of a real-world task, we have to understand the group dynamics during the work on large displays. Among other things, we have to study, what effects different task conditions will have on user behavior. In this paper, we investigated the effects of task conditions on group behavior regarding collaborative coupling and territoriality during co-located collaboration on a wall-sized display. For that, we designed two tasks: a task that resembles the information foraging loop and a task that resembles the connecting facts activity. Both tasks represent essential sub-processes of the sensemaking process in visual analytics and cause distinct space/display usage conditions. The information foraging activity requires the user to work with individual data elements to look into details. Here, the users predominantly occupy only a small portion of the display. In contrast, the connecting facts activity requires the user to work with the entire information space. Therefore, the user has to overview the entire display. We observed 12 groups for an average of 2 h each and gathered qualitative data and quantitative data in the form of surveys, field notes, video recordings, tracking data, and system logs. During data analysis, we focused specifically on participants' collaborative coupling (in particular, collaboration tightness, coupling styles, user roles, and task subdivision strategies) and territorial behavior. Our results both confirm and extend findings from the previous tabletop and wall-sized display studies. We could detect that participants tended to subdivide the task to approach it, in their opinion, in a more effective way, in parallel. We describe the subdivision strategies for both task conditions. We also detected and described multiple user roles, as well as a new coupling style that does not fit in either category: loosely or tightly. Moreover, we could observe a territory type that has not been mentioned previously in research. In our opinion, this territory type can affect the collaboration process of groups with more than two collaborators negatively. Finally, we investigated critical display regions in terms of ergonomics. We could detect that users perceived some regions as less comfortable for long-time work. The findings can be valuable for groupware interface design and development of group behavior models for analytical reasoning and decision making.

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Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Task Dependent Group Coupling and Territorial Behavior on Large Tiled Displays

et al. 2019

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“…• EC1b: The publication does not include any kind of system initiative; it is, therefore, situated at the far-right end of Oppermann and Rasher (1997) spectrum of adaptation. Please note that there are publications in our final dataset, where no finalized or prototype system capable of systeminitiated adaptation or personalizaiton is present, but these papers concretely discuss future directions for systeminitiated measures, hence, making them relevant to our research questions, such as the included publication by Sigitov et al (2018).…”

Section: Inclusion and Exclusion Criteriamentioning

confidence: 99%

“…All of these advances are important for future PCS, as they bear the potential to decrease the complexity of collaborative UIs through personalization. Sigitov et al (2018) investigate collaboration processes of dyads and focus on the transitions between collaboration states (i.e., an action of user X followed by a reaction of user Y) and interferences. The authors categorize these transitions based on changes in proximity, verbal communication, visual attention, visual interface, and gestures.…”

Section: User Modelingmentioning

confidence: 99%

A Systematic Review of Personalized Collaborative Systems

Neumayr

Augstein

2020

Front. Comput. Sci.

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Personalization, aiming at supporting users individually, according to their individual needs and prerequisites, has been discussed in a number of domains including learning, search, or information retrieval. In the field of human–computer interaction, personalization also bears high potential as users might exhibit varying and strongly individual preferences and abilities related to interaction. For instance, there is a good amount of work on personalized or adaptive user interfaces (also under the notion of intelligent user interfaces). Personalized human–computer interaction, however, does not only subsume approaches to support the individual user, it also bears high potential if applied to collaborative settings, for example, through supporting the individuals in a group as well as the group itself (considering all of its special dynamics). In collaborative settings (remote or co-located), there generally is a number of additional challenges related to human-to-human collaboration in a group, such as group communication, awareness or territoriality, device or software tool selection, or selection of collaborators. Personalized Collaborative Systems thus attempt to tackle many of these challenges. For instance, there are collaborative systems that recommend tools, content, or team constellations. Such systems have been suggested in different domains and different collaborative settings and contexts. In most cases, these systems explicitly focus on a certain aspect of personalized collaboration support (such as team composition). This article provides a broader, concise overview of existing approaches to Personalized Collaborative Systems based on a systematic literature review considering the ACM Digital Library.

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Side-by-Side vs Face-to-Face: Evaluating Colocated Collaboration via a Transparent Wall-sized Display

Gong

Sun

Chu

et al. 2023

Proc. ACM Hum.-Comput. Interact.

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Traditional wall-sized displays mostly only support side-by-side co-located collaboration, while transparent displays naturally support face-to-face interaction. Many previous works assume transparent displays support collaboration. Yet it is unknown how exactly its afforded face-to-face interaction can support loose or close collaboration, especially compared to the side-by-side configuration offered by traditional large displays. In this paper, we used an established experimental task that operationalizes different collaboration coupling and layout locality, to compare pairs of participants collaborating side-by-side versus face-to-face in each collaborative situation. We compared quantitative measures and collected interview and observation data to further illustrate and explain our observed user behavior patterns. The results showed that the unique face-to-face collaboration brought by transparent display can result in more efficient task performance, different territorial behavior, and both positive and negative collaborative factors. Our findings provided empirical understanding about the collaborative experience supported by wall-sized transparent displays and shed light on its future design.

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Towards Intelligent Interfaces for Mixed-Focus Collaboration

Cited by 3 publications

References 22 publications

Task Dependent Group Coupling and Territorial Behavior on Large Tiled Displays

Task Dependent Group Coupling and Territorial Behavior on Large Tiled Displays

A Systematic Review of Personalized Collaborative Systems

Side-by-Side vs Face-to-Face: Evaluating Colocated Collaboration via a Transparent Wall-sized Display

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