Search and rescue (SAR), a disaster response activity performed to locate and save victims, primarily involves collective sensemaking and planning. SAR responders learn to search and navigate the environment, process information about buildings, and collaboratively plan with maps. We synthesize data from five sources, including field observations and interviews, to understand the informational components of SAR and how information is recorded and communicated. We apply activity theory, uncovering unforeseen factors that are relevant to the design of collaboration systems and training solutions. Through our analysis, we derive design implications to support collaborative information technology and training systems: mixing physical and digital mapping; mixing individual and collective mapping; building for different levels and sources of information; and building for different rules, roles, and activities.

In multiplayer collaborative games, players need to coordinate their actions and synchronize their efforts effectively to succeed as a team; thus, individual differences can impact teamwork and gameplay. This article investigates the effects of cognitive styles on teams engaged in collaborative gaming activities. Fifty-four individuals took part in a mixed-methods user study; they were classified as field-dependent (FD) or independent (FI) based on a field-dependent–independent (FD-I) cognitive-style-elicitation instrument. Three groups of teams were formed, based on the cognitive style of each team member: FD-FD, FD-FI, and FI-FI. We examined collaborative gameplay in terms of team performance, cognitive load, communication, and player experience. The analysis revealed that FD-I cognitive style affected the performance and mental load of teams. We expect the findings to provide useful insights on understanding how cognitive styles influence collaborative gameplay.

Gesture recognition devices provide a new means for natural human-computer interaction. However, when selecting these devices for games, designers might find it challenging to decide which gesture recognition device will work best. In the present research, we compare three vision-based, hand gesture devices: Leap Motion, Microsoft's Kinect, and Intel's RealSense. We developed a simple hand-gesture based game to evaluate performance, cognitive demand, comfort, and player experience of using these gesture devices. We found that participants' preferred and performed much better using Leap Motion and Kinect compared to using RealSense. Leap Motion also outperformed or was equivalent to Kinect. These findings suggest that not all gesture recognition devices can be suitable for games and that designers need to make better decisions when selecting gesture recognition devices and designing gesture based games to insure the usability, accuracy, and comfort of such games.

Composite wearable computers consist of multiple wearable devices connected together and working as a cohesive whole. These composite wearable computers are promising for augmenting our interaction with the physical, virtual, and mixed play spaces (e.g., mixed reality games). Yet little research has directly addressed how mixed reality system designers can select wearable input devices and how these devices can be assembled together to form a cohesive wearable computer. We present an initial taxonomy of wearable input devices to aid designers in deciding which devices to select and assemble together to support different mixed reality systems. We undertook a grounded theory analysis of 84 different wearable input devices resulting in a design taxonomy for composite wearable computers. The taxonomy consists of two axes: TYPE OF INTERACTIVITY and BODY LOCATION. These axes enable designers to identify which devices fill particular needs in the system development process and how these devices can be assembled together to form a cohesive wearable computer.

In distributed multiplayer games, it can be difficult to communicate strategic information for planning game moves and player interactions. Often, players spend extra time communicating, reducing their engagement in the game. Visual annotations in game maps and in the gameworld can address this problem and result in more efficient player communication. We studied the impact of real-time feedback on planning annotations, specifically two different annotation types, in a custom-built, third-person, multiplayer game and analyzed their effects on player performance, experience, workload, and annotation use. We found that annotations helped engage players in collaborative planning, which reduced frustration, and shortened goal completion times. Based on these findings, we discuss how annotating in virtual game spaces enables collaborative planning and improves team performance.

To date, affective computing research has acknowledged individual differences with regard to detecting affect, yet little research has explored how these individual differences may determine the degree to which affective computing is successful in manipulating the affect of specific computer users. The current study used individual difference measures to predict how much an individual can be influenced by a hedonic computing paradigm: a simple trivia game. Female participants responded in a greater way to positive affective feedback about their performance than did men. Moreover, several personality traits, including neuroticism, narcissism, self-esteem, and extraversion, augmented the degree to which affect changed as a result of playing the game. The results are consistent with the gender differences hypothesis, and the authors conclude that individual differences, particularly gender and personality traits, play a large role in the potential impact of computing platforms and would be useful in personalizing the affective nature of the human–computer interaction.