The Effects of Displayed Violence and Game Speed in First-Person Shooters on Physiological Arousal and Aggressive Behavior

Many studies have been conducted to examine the effects of displayed violence in digital games on outcomes like aggressive behavior and physiological arousal. However, they often lack a proper manipulation of the relevant factors and control of confounding variables. In this study, the displayed violence and game speed of a recent first-person shooter game were varied systematically using the technique of modding, so that effects could be explained properly by the respective manipulations. Aggressive behavior was measured with the standardized version of the Competitive Reaction Time Task or CRTT (Ferguson et al., 2008}. Physiological arousal was operationalized with four measurements: galvanic skin response (GSR), heart rate (HR), body movement, force on mouse and keyboard. A total of N = 87 participants played in one of four game conditions (low- vs. high-violence, normal- vs. high speed) while physiological measurements were taken with finger clips, force sensors on input devices (mouse and keyboard), and a Nintendo Wii balance board on the chair they sat on. After play, their aggressive behavior was measured with the CRTT. The results of the study do not support the hypothesis that playing digital games increases aggressive behavior. There were no significant differences in GSR and HR, but with a higher game speed, participants showed less overall body movement, most likely to meet the game’s higher demands on cognitive and motor capacities. Also, higher game speed and displayed violence caused an increase in applied force on mouse and keyboard. Previous experience with digital games did not moderate any of these findings. Moreover, it provides further evidence that the CRTT should only be used in a standardized way as a measurement for aggression, if at all. Using all 7 different published (though not validated) ways to calculate levels of aggression from the raw data, “evidence” was found that playing a violent digital game increases, decreases, or does not change aggression at all. Thus, the present study does extend previous research. Firstly, it shows the methodological advantages of modding in digital game research to accomplish the principles of psychological (laboratory) experiments by manipulating relevant variables and controlling all others. It also demonstrates the test-theoretical problems of the highly diverse use of the CRTT. It provides evidence that for a meaningful interpretation of effects of displayed violence in digital games, there are other game characteristics that should be controlled for since they might have an effect on relevant outcome variables. Further research needs to identify more of those game features, and it should also improve the understanding of the different measures for physiological arousal and their interrelatedness

Towards a mood sensitive integrated development environment to enhance the performance of programmers

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.The aim of the research was to analyze the possibility of developing an Integrated Development Environment (IDE) that could improve a programmer‘s performance by considering their current mood. Various experiments were conducted to study this idea. However, the impact of moods on programmer performance was initially examined in the literature. Based on this, a Cognitive Programming Task Model (CPTM) was developed showing that various cognitive functions and programming activities are interrelated. A second model derived from the literature, the Cognitive Mood Model (CMM), suggested that moods are also interrelated with various cognitive functions. Combining these two models indirectly suggests a relation between moods and programming tasks, which was presented as the Mood Programming Model (MPM). As direct empirical support was lacking for this relation, two experiments were conducted to study the effect mood could have on performance in a debug task. Validated mood-inducing movie clips were used to induce specific moods along two-mood dimensions: valence and arousal. The first study was conducted online. The results showed that arousal is a significant factor when considering programmer performance whereas valence was found to have no significant effect. The second study was a continuation study to validate the findings from the first study within lab conditions. The results were not able to confirm the findings of the first experiment. The reasons for these findings were explained accordingly. As mood was found to have an effect on a programmer‘s coding and debugging performance, this factor might be considered when developing a support system. The next step in the research was therefore to consider mood measuring in a non-interruptive way. The next two experiments were based around the hypothesis that ―moods can be measured from the keyboard and mouse interaction of the computer user‖. In the first experiment an application was installed on participants‘ computers to record their key presses and mouse clicks in a log file. Their self reported moods in intervals of 20 minutes were also stored in the same file over an average period of eight days. Correlations between participants‘ self reported moods and their keyboard and mouse use revealed that it might be possible to measure moods of the some of the participants. The second experiment took place in the lab, where participants were asked to perform programming like tasks while listening to ii mood inducing background music. Their moods were measured with a Galvanic Skin Response (GSR) meter whereas key presses and mouse clicks again were recorded in log files. The correlations between GSR measurements and keyboard and mouse interaction validated the findings of the experiment in the field that it might be possible to measure the mood of some users from their computer use. Analyzing participants‘ personality traits showed dutifulness and self discipline as indicators that a person‘s mood correlates with his/her interaction behaviour. Considering that mood has an effect on programmer performance and that it might be possible to measure mood in a non-intrusive manner, the last question to focus on was whether a computer-generated intervention could change a programmer‘s mood and consequently improve their performance. In the final experiment programmers had to dry run algorithms for 16 minutes with the expectation that a level of boredom would set in. After this the video clip instructed them to participate in some physical exercises. Participants continued tracing algorithms for 8 minutes after the intervention. Results showed that the mood change after the intervention coincided with a programmers improved ability to provide the correct output of the algorithms. Together these findings lay the foundation for developing an IDE that can measure the programmer mood in a non-intrusive way and make effective interventions to improve programmer performance

Towards estimating computer users' mood from interaction behaviour with keyboard and mouse

The purpose of this exploratory research was to study the relationship between the mood of computer users and their use of keyboard and mouse to examine the possibility of creating a generic or individualized mood measure. To examine this, a field study (n = 26) and a controlled study (n = 16) were conducted. In the field study, interaction data and self-reported mood measurements were collected during normal PC use over several days. In the controlled study, participants worked on a programming task while listening to high or low arousing background music. Besides subjective mood measurement, galvanic skin response (GSR) data was also collected. Results found no generic relationship between the interaction data and the mood data. However, the results of the studies found significant average correlations between mood measurement and personalized regression models based on keyboard and mouse interaction data. Together the results suggest that individualized mood prediction is possible from interaction behaviour with keyboard and mouse

Interaction platform-orientated perspective in designing novel applications

The lack of HCI offerings in the invention of novel software applications and the bias of design knowledge towards desktop GUI make it difficult for us to design for novel scenarios and applications that leverage emerging computational technologies. These include new media platforms such as mobiles, interactive TV, tabletops and large multi-touch walls on which many of our future applications will operate. We argue that novel application design should come not from user-centred requirements engineering as in developing a conventional application, but from understanding the interaction characteristics of the new platforms. Ensuring general usability for a particular interaction platform without rigorously specifying envisaged usage contexts helps us to design an artifact that does not restrict the possible application contexts and yet is usable enough to help brainstorm its more exact place for future exploitation

A Content-Analysis Approach for Exploring Usability Problems in a Collaborative Virtual Environment

As Virtual Reality (VR) products are becoming more widely available in the consumer market, improving the usability of these devices and environments is crucial. In this paper, we are going to introduce a framework for the usability evaluation of collaborative 3D virtual environments based on a large-scale usability study of a mixedmodality collaborative VR system. We first review previous literature about important usability issues related to collaborative 3D virtual environments, supplemented with our research in which we conducted 122 interviews after participants solved a collaborative virtual reality task. Then, building on the literature review and our results, we extend previous usability frameworks. We identified twelve different usability problems, and based on the causes of the problems, we grouped them into three main categories: VR environment-, device interaction-, and task-specific problems. The framework can be used to guide the usability evaluation of collaborative VR environments

An Evaluation of Mouse and Keyboard Interaction Indicators towards Non-intrusive and Low Cost Affective Modeling in an Educational Context

AbstractIn this paper we propose a series of indicators, which derive from user's interactions with mouse and keyboard. The goal is to evaluate their use in identifying affective states and behavior changes in an e-learning platform by means of non-intrusive and low cost methods. The approach we have followed study user's interactions regardless of the task being performed and its presentation, aiming at finding a solution applicable in any domain. In particular, mouse movements and clicks, as well as keystrokes were recorded during a math problem solving activity where users involved in the experiment had not only to score their degree of valence (i.e., pleasure versus displeasure) and arousal (i.e., high activation versus low activation) of their affective states after each problem by using the Self-Assessment-Manikin scale, but also type a description of their own feelings. By using that affective labeling, we evaluated the information provided by these different indicators processed from the original user's interactions logs. In total, we computed 42 keyboard indicators and 96 mouse indicators