Effects of Team-Based Computer Interaction: The Media Equation and Game Design Considerations

The current paper applies media equation research to video game de-sign. The paper presents a review of the existing media equation research, de-scribes a specific study conducted by the authors, discusses how the findings of the study can be used to inform future game design, and explores how other media equation findings might be incorporated into game design. The specific study, discussed in detail in the paper, explores the notion of team formation between humans and computer team-mates. The results show that while highly experienced users will accept a computer as a team-mate, they tend to react more negatively towards the computer than to human teammates (a ‘Black Sheep’ Effect

Maps, agents and dialogue for exploring a virtual world

In previous years we have been involved in several projects in which users (or visitors) had to find their way in information-rich virtual environments. 'Information-rich' means that the users do not know beforehand what is available in the environment, where to go in the environment to find the information and, moreover, users or visitors do not necessarily know exactly what they are looking for. Information-rich means also that the information may change during time. A second visit to the same environment will require different behavior of the visitor in order for him or her to obtain similar information than was available during a previous visit. In this paper we report about two projects and discuss our attempts to generalize from the different approaches and application domains to obtain a library of methods and tools to design and implement intelligent agents that inhabit virtual environments and where the agents support the navigation of the user/visitor

The media equation and team formation: Further evidence for experience as a moderator

This study extends previous media equation research, which showed that interdependence but not identity leads to team affiliation effects with computers. The current study used an identity manipulation that more closely replicated the manipulation used in traditional team and group formation research than the original media equation research in this area. The study also sought further evidence for the relationship between experience with computers and behaviour reflecting a media equation pattern of results. Sixty students from the University of Queensland voluntarily participated in the study. Participants were assigned to one of three conditions: control, human team (a team made of only humans) or human-computer team (a team made of computers and humans). Questionnaire measures assessing participants’ affective experience, attitudes and opinions were taken. Participants of high experience, but not low experience, when assigned to either of the team conditions enjoyed the tasks completed on the computer more than participants who worked on their own. When assigned to a team that involved a computer, participants of high experience, but not low experience, reacted negatively towards the computer (in comparison to high experience participants working on their own or on a team without a computer as a team member) – rating the information provided by the computer lower, rating themselves as less influenced by the computer and changing their own ratings and rankings to be less like those of the computer. These results are interpreted in light of the ‘Black Sheep’ literature and recognized as a media equation pattern of results

Anthropomorphic Agents as a UI Paradigm: Experimental Findings and a Framework for Research

Research on anthropomorphic agent interfaces has produced widely divergent results. We suggest that this is due to insufficient consideration of key factors that influence the perception and effectiveness of agent-based interfaces. Thus, we propose a framework for studying anthropomorphic agents that can systematize the research. The framework emphasizes features of the agent, the user, and the task the user is performing. Our initial experiment within this framework manipulated the agent's appearance (lifelike versus iconic) and the nature of the user's task (carrying out procedures versus providing opinions). We found that the perception of the agent was strongly influenced by the task while features of the agent that we manipulated had little effect

Sending an Avatar to Do a Human’s Job: Compliance with Authority Persists Despite the Uncanny Valley

Just as physical appearance affects social influence in human communication, it may also affect the processing of advice conveyed through avatars, computer-animated characters, and other human-like interfaces. Although the most persuasive computer interfaces are often the most human-like, they have been predicted to incur the greatest risk of falling into the uncanny valley, the loss of empathy attributed to characters that appear eerily human. Previous studies compared interfaces on the left side of the uncanny valley, namely, those with low human likeness. To examine interfaces with higher human realism, a between-groups factorial experiment was conducted through the internet with 426 midwestern U.S. undergraduates. This experiment presented a hypothetical ethical dilemma followed by the advice of an authority figure. The authority was manipulated in three ways: depiction (digitally recorded or computer animated), motion quality (smooth or jerky), and advice (disclose or refrain from disclosing sensitive information). Of these, only the advice changed opinion about the ethical dilemma, even though the animated depiction was significantly eerier than the human depiction. These results indicate that compliance with an authority persists even when using an uncannily realistic computer-animated double

Evaluating humanoid embodied conversational agents in mobile guide applications

Evolution in the area of mobile computing has been phenomenal in the last few years. The exploding increase in hardware power has enabled multimodal mobile interfaces to be developed. These interfaces differ from the traditional graphical user interface (GUI), in that they enable a more “natural” communication with mobile devices, through the use of multiple communication channels (e.g., multi-touch, speech recognition, etc.). As a result, a new generation of applications has emerged that provide human-like assistance in the user interface (e.g., the Siri conversational assistant (Siri Inc., visited 2010)). These conversational agents are currently designed to automate a number of tedious mobile tasks (e.g., to call a taxi), but the possible applications are endless. A domain of particular interest is that of Cultural Heritage, where conversational agents can act as personalized tour guides in, for example, archaeological attractions. The visitors to historical places have a diverse range of information needs. For example, casual visitors have different information needs from those with a deeper interest in an attraction (e.g., - holiday learners versus students). A personalized conversational agent can access a cultural heritage database, and effectively translate data into a natural language form that is adapted to the visitor’s personal needs and interests. The present research aims to investigate the information needs of a specific type of visitors, those for whom retention of cultural content is important (e.g., students of history, cultural experts, history hobbyists, educators, etc.). Embodying a conversational agent enables the agent to use additional modalities to communicate this content (e.g., through facial expressions, deictic gestures, etc.) to the user. Simulating the social norms that guide the real-world human-to-human interaction (e.g., adapting the story based on the reactions of the users), should at least theoretically optimize the cognitive accessibility of the content. Although a number of projects have attempted to build embodied conversational agents (ECAs) for cultural heritage, little is known about their impact on the users’ perceived cognitive accessibility of the cultural heritage content, and the usability of the interfaces they support. In particular, there is a general disagreement on the advantages of multimodal ECAs in terms of users’ task performance and satisfaction over nonanthropomorphised interfaces. Further, little is known about what features influence what aspects of the cognitive accessibility of the content and/or usability of the interface. To address these questions I studied the user experiences with ECA interfaces in six user studies across three countries (Greece, UK and USA). To support these studies, I introduced: a) a conceptual framework based on well-established theoretical models of human cognition, and previous frameworks from the literature. The framework offers a holistic view of the design space of ECA systems b) a research technique for evaluating the cognitive accessibility of ECA-based information presentation systems that combine data from eye tracking and facial expression recognition. In addition, I designed a toolkit, from which I partially developed its natural language processing component, to facilitate rapid development of mobile guide applications using ECAs. Results from these studies provide evidence that an ECA, capable of displaying some of the communication strategies (e.g., non-verbal behaviours to accompany linguistic information etc.) found in the real-world human guidance scenario, is not affecting and effective in enhancing the user’s ability to retain cultural content. The findings from the first two studies, suggest than an ECA has no negative/positive impact on users experiencing content that is similar (but not the same) across different locations (see experiment one, in Chapter 7), and content of variable difficulty (see experiment two, in Chapter 7). However, my results also suggest that improving the degree of content personalization and the quality of the modalities used by the ECA can result in both effective and affecting human-ECA interactions. Effectiveness is the degree to which an ECA facilitates a user in accomplishing the navigation and information tasks. Similarly, affecting is the degree to which the ECA changes the quality of the user’s experience while accomplishing the navigation and information tasks. By adhering to the above rules, I gradually improved my designs and built ECAs that are affecting. In particular, I found that an ECA can affect the quality of the user’s navigation experience (see experiment three in Chapter 7), as well as how a user experiences narrations of cultural value (see experiment five, in Chapter 8). In terms of navigation, I found sound evidence that the strongest impact of the ECAs nonverbal behaviours is on the ability of users to correctly disambiguate the navigation of an ECA instructions provided by a tour guide system. However, my ECAs failed to become effective, and to elicit enhanced navigation or retention performances. Given the positive impact of ECAs on the disambiguation of navigation instructions, the lack of ECA-effectiveness in navigation could be attributed to the simulated mobile conditions. In a real outdoor environment, where users would have to actually walk around the castle, an ECA could have elicited better navigation performance, than a system without it. With regards to retention performance, my results suggest that a designer should not solely consider the impact of an ECA, but also the style and effectiveness of the question-answering (Q&A) with the ECA, and the type of user interacting with the ECA (see experiments four and six, in Chapter 8). I found that that there is a correlation between how many questions participants asked per location for a tour, and the information they retained after the completion of the tour. When participants were requested to ask the systems a specific number of questions per location, they could retain more information than when they were allowed to freely ask questions. However, the constrained style of interaction decreased their overall satisfaction with the systems. Therefore, when enhanced retention performance is needed, a designer should consider strategies that should direct users to ask a specific number of questions per location for a tour. On the other hand, when maintaining the positive levels of user experiences is the desired outcome of an interaction, users should be allowed to freely ask questions. Then, the effectiveness of the Q&A session is of importance to the success/failure of the user’s interaction with the ECA. In a natural-language question-answering system, the system often fails to understand the user’s question and, by default, it asks the user to rephrase again. A problem arises when the system fails to understand a question repeatedly. I found that a repetitive request to rephrase the same question annoys participants and affects their retention performance. Therefore, in order to ensure effective human-ECA Q&A, the repeat messages should be built in a way to allow users to figure out how to ask the system questions to avoid improper responses. Then, I found strong evidence that an ECA may be effective for some type of users, while for some others it may be not. I found that an ECA with an attention-grabbing mechanism (see experiment six, in Chapter 8), had an inverse effect on the retention performance of participants with different gender. In particular, it enhanced the retention performance of the male participants, while it degraded the retention performance of the female participants. Finally, a series of tentative design recommendations for the design of both affecting and effective ECAs in mobile guide applications in derived from the work undertaken. These are aimed at ECA researchers and mobile guide designers