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Mental model development, deeper levels of information processing, and elaboration are critical to learning. More so, individuals' metacomprehension accuracy is integral to making improvements to their knowledge base. In other words, without an accurate perception of their knowledge on a topic, learners may not know that knowledge gaps or misperceptions exist and, thus, would be less likely to correct them. Therefore, this study offered a dual-process approach that aimed at enhancing metacomprehension. One path aimed at advancing knowledge structure development and, thus, mental model development. The other focused on promoting a deeper level of information processing through processes like elaboration. It was predicted that this iterative approach would culminate in improved metacomprehension and increased learning. Accordingly, using the Graduated Concept Model Development (GCMD) approach, the role of learner-generated concept model development in facilitating metacomprehension and knowledge acquisition was examined. Concept maps have had many roles in the learning process as mental model assessment tools and advanced organizers. However, this study examined the process of concept model building as an effective training tool. Whereas, concept maps functioning as advanced organizers are certainly beneficial, it would seem that the benefits of having a learner examine and amend the current state of their knowledge through concept model development would prove more effective for learning. In other words, learners looking at an advanced organizer of the training material may feel assured that they have a thorough understanding of it. Only when they are forced to create a representation of the material would the gaps and misperceptions in their knowledge base likely be revealed. In short, advanced organizers seem to rely on recognition, where concept model development likely requires recalling and understanding 'how' and 'why' the interrelationships between concepts exist. Therefore, the Graduated Concept Model Development (GCMD) technique offered in this study was based on the theory that knowledge acquisition improves when learners integrate new information into existing knowledge, assign elaborated meanings to concepts, correct misperceptions, close knowledge gaps, and strengthen accurate connections between concepts by posing targeted questions against their existing knowledge structures. This study placed an emphasis on meaningful learning and suggested a process by which newly introduced concepts would be manipulated for the purpose of improving metacomprehension by strengthening accurate knowledge structures and mental model development, and through deeper and elaborated information processing. Indeed, central to improving knowledge deficiencies and misunderstandings is metacomprehension, and the constructing of concepts maps was hypothesized to improve metacomprehension accuracy and, thus, learning. This study was a one-factor between-groups design with concept map type as the independent variable, manipulated at four levels: no concept map, concept map as advanced organizer, learner-built concept map with feedback, and learner-built concept map without feedback. The dependent variables included performance (percent correct) on a declarative and integrative knowledge assessment, mental model development, and metacomprehension accuracy. Participants were 68 (34 female, 34 male, ages 18-35, mean age = 21.43) undergraduate students from a major southeastern university. Participants were randomly assigned to one of the four experimental conditions, and analysis revealed no significant differences between the groups. Upon arrival, participants were randomly assigned to one of the four experimental conditions. Participants then progressed through the three stages of the experiment. In Stage I, participants completed forms regarding informed consent, general biographical information, and task self-efficacy. In Stage II, participants completed the self-paced tutorial based on the Distributed Dynamic Decision Making (DDD) model, a simulated military command and control environment aimed at creating events to encourage team coordination and performance (for a detailed description, see Kleinman & Serfaty, 1989). The manner by which participants worked through the tutorial was determined by their assigned concept map condition. Upon finishing each module of the tutorial, participants then completed a metacomprehension prediction question. In Stage III, participants completed the computer-based knowledge assessment test, covering both declarative and integrative knowledge, followed by the metacomprehension postdiction question. Participants then completed the card sort task, as the assessment of mental model development. Finally, participants completed a general study survey and were debriefed as to the purpose of the study. The entire experiment lasted approximately 2 to 3 hours. Results indicated that the GCMD condition showed a stronger indication of metacomprehension accuracy, via prediction measures, compared with the other three conditions (control, advanced organizer, and feedback), and, specifically, significantly higher correlations than the other three conditions in declarative knowledge. Self-efficacy measures also indicated that the higher metacomprehension accuracy correlation observed in the GCMD condition was likely the result of the intervention, and not due to differences in self-efficacy in that group of participants. Likewise, the feedback and GCMD conditions led to significantly high correlations for metacomprehension accuracy based on levels of understanding on the declarative knowledge tutorial module (Module 1). The feedback condition also showed similar responses for the integrative knowledge module (Module 2). The advanced organizer, feedback, and GCMD conditions were also found to have significantly high correlation of self-reported postdiction of performance on the knowledge assessment and the actual results of the knowledge assessment results. However, results also indicated that there were no significant findings between the four conditions in mental model assessment and knowledge assessment. Nevertheless, results support the relevance of accurate mental model development in knowledge assessment outcomes. Retrospectively, two opposing factors may have complicated efforts to detect additional differences between groups. From one side, the experimental measures may not have been rigorous enough to filter out the effect from the intervention itself. Conversely, software usability issues and the resulting limitations in experimental design may have worked negatively against the two concept mapping conditions and, inadvertently, suppressed effects of the intervention. Future research in the GCMD approach will likely review cognitive workload, concept mapping software design, and the sensitivity of the measures involved.

The purpose of this study was to empirically test the oft-noted hypothesis that shared mental models lead to implicit coordination. Specifically, this dissertation investigated the underlying mechanisms of implicit coordination and how different aspects of shared mental models affect the process. The research questions tested in this study were (a)how perceptions of sharedness affect the initiation of implicit coordination, (b) how actual levels of sharedness affect the process of implicit coordination, and (c) how quality of task mental models affects successful implicit coordination. Sixty same-gender, two-person teams engaged in a complex military reconnaissance planning task in which the team members were required to work together by exchanging information to plan routes for one unmanned aerial vehicle (UAV) and one unmanned ground vehicle (UGV). The results provided partial support for the influence of different facets of shared mental models on the process of implicit coordination. Specifically, individual mental model quality, not perceptions of sharedness or actual mental model sharedness, was the biggest predictor of the initiation of implicit coordination. Additionally, perceptions of sharedness and actual mental model sharedness interacted with one another, such that teams in mismatched conditions (high perceptions of sharedness but low actual sharedness [false consensus], or low perceptions of sharedness and high actual sharedness, [pluralistic ignorance]) tended to increase their communications. The implications and recommendations for future research on implicit coordination and shared mental models are discussed. Additionally, the implications for operators of unmanned vehicles are also discussed.

The transition in robotics from tools to teammates has begun. However, the benefit autonomous robots provide will be diminished if human teammates misinterpret robot behaviors. Applying mental model theory as the organizing framework for human understanding of robots, the current empirical study examined the influence of task-role mental models of robots on the interpretation of robot motion behaviors, and the resulting impact on subjective ratings of robots. Observers (N = 120) were exposed to robot behaviors that were either congruent or incongruent with their task-role mental model, by experimental manipulation of preparatory robot task-role information to influence mental models (i.e., security guard, groundskeeper, or no information), the robot's actual task-role behaviors (i.e., security guard or groundskeeper), and the order in which these robot behaviors were presented. The results of the research supported the hypothesis that observers with congruent mental models were significantly more accurate in interpreting the motion behaviors of the robot than observers without a specific mental model. Additionally, an incongruent mental model, under certain circumstances, significantly hindered an observer's interpretation accuracy, resulting in subjective sureness of inaccurate interpretations. The strength of the effects that mental models had on the interpretation and assessment of robot behaviors was thought to have been moderated by the ease with which a particular mental model could reasonably explain the robot's behavior, termed mental model applicability. Finally, positive associations were found between differences in observers' interpretation accuracy and differences in subjective ratings of robot intelligence, safety, and trustworthiness. The current research offers implications for the relationships between mental model components, as well as implications for designing robot behaviors to appear more transparent, or opaque, to humans.

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The main goal of this study was to identify some determinants of collective efficacy in small groups. A multilevel approach was used to posit hypotheses and research questions relating individual and shared beliefs of collective efficacy to collective cognition activities, task interdependence, self-efficacy for group work, and collective orientation. A two-phase longitudinal design was employed. The sample comprised 270 university students, enrolled in seven courses and involved in 86 work groups in both phases of the study. All groups were required to perform interdependent academic tasks. The results of multiple regression analysis of aggregated variables provided some evidence that the more group members perceived themselves to be interdependent in the early stages of group work and assigned their tasks interdependently during group processes, the more likely they developed high collective efficacy in the final stages of group work. Collective efficacy was also related to the group average of self-efficacy for group work when task interdependence was high. Multilevel analysis was also used. These results showed that variation at the individual level was considerable, and there was significant but relatively little variation at the group level, with small effect sizes, for a few variables including collective efficacy. Structural equation modelling was used to confirm the theoretical framework at the individual level after accounting for group level variation. The results suggested that integration and constructive evaluation of ideas during group processes and self-efficacy for group work may have been determinants of collective efficacy at the individual level. Moreover, collective efficacy at the individual level was related to an interdependent perception of self in relation to other group members. The results suggest that helping group members learn how to evaluate and integrate each other???s ideas during group activities, and perceive themselves to be interdependent may enhance group capabilities for performing tasks. In addition, improving students??? self-efficacy for group work was identified as a key factor, as it may enhance a sense of interdependence among group members, improve the extent to which group members participate in integrating and evaluating ideas, and increase the whole group???s capabilities for performing tasks.

The main goal of this study was to identify some determinants of collective efficacy in small groups. A multilevel approach was used to posit hypotheses and research questions relating individual and shared beliefs of collective efficacy to collective cognition activities, task interdependence, self-efficacy for group work, and collective orientation. A two-phase longitudinal design was employed. The sample comprised 270 university students, enrolled in seven courses and involved in 86 work groups in both phases of the study. All groups were required to perform interdependent academic tasks. The results of multiple regression analysis of aggregated variables provided some evidence that the more group members perceived themselves to be interdependent in the early stages of group work and assigned their tasks interdependently during group processes, the more likely they developed high collective efficacy in the final stages of group work. Collective efficacy was also related to the group average of self-efficacy for group work when task interdependence was high. Multilevel analysis was also used. These results showed that variation at the individual level was considerable, and there was significant but relatively little variation at the group level, with small effect sizes, for a few variables including collective efficacy. Structural equation modelling was used to confirm the theoretical framework at the individual level after accounting for group level variation. The results suggested that integration and constructive evaluation of ideas during group processes and self-efficacy for group work may have been determinants of collective efficacy at the individual level. Moreover, collective efficacy at the individual level was related to an interdependent perception of self in relation to other group members. The results suggest that helping group members learn how to evaluate and integrate each other???s ideas during group activities, and perceive themselves to be interdependent may enhance group capabilities for performing tasks. In addition, improving students??? self-efficacy for group work was identified as a key factor, as it may enhance a sense of interdependence among group members, improve the extent to which group members participate in integrating and evaluating ideas, and increase the whole group???s capabilities for performing tasks.

The human cognitive biases that result in anthropomorphism, the moral confusion surrounding the status of robots, and wider societal concerns related to the deployment of artificial intelligence at scale all motivate the study of robot transparency --- the design of robots such that they may be fully understood by humans. Based on the hypothesis that robot transparency leads to better (in the sense of more accurate) mental models of robots, I investigate how humans perceive and understand a robot when they encounter it, both in online video and direct physical encounter. I also use Amazon Mechanical Turk as a platform to facilitate online experiments with larger population samples. To improve transparency I use a visual real-time transparency tool providing a graphical representation of the internal processing and state of a robot. I also describe and deploy a vocalisation algorithm for transparency. Finally, I modify the form of the robot with a simple bee-like cover, to investigate the effect of appearance on transparency. I find that the addition of a visual or vocalised representation of the internal processing and state of a robot significantly improves the ability of a naive observer to form an accurate model of a robot's capabilities, intentions and purpose. This is a significant result across a diverse, international population sample and provides a robust result about humans in general, rather than one geographic, ethnic or socio-economic group in particular. However, all the experiments were unable to achieve a Mental Model Accuracy (MMA) of more than 59%, indicating that despite improved transparency of the internal state and processing, naive observers' models remain inaccurate, and there is scope for further work. A vocalising, or 'talking', robot greatly increases the confidence of naive observers to report that they understand a robot's behaviour when observed on video. Perhaps we might be more easily deceived by talking robots than silent ones. A zoomorphic robot is perceived as more intelligent and more likeable than a very similar mechanomorphic robot, even when the robots exhibit almost identical behaviour. A zoomorphic form may attract closer visual attention, and whilst this results in an improved MMA, it also diverts attention away from transparency measures, reducing their efficacy to further increase MMA. The trivial embellishment of a robot to alter its form has significant effects on our understanding and attitude towards it. Based on the concerns that motivate this work, together with the results of the robot transparency experiments, I argue that we have a moral responsibility to make robots transparent, so as to reveal their true machine nature. I recommend the inclusion of transparency as a fundamental design consideration for intelligent systems, particularly for autonomous robots. This research also includes the design and development of the 'Instinct' reactive planner, developed as a controller for a mobile robot of my own design. Instinct provides facilities to generate a real-time 'transparency feed'--- a real-time trace of internal processing and state. Instinct also controls agents within a simulation environment, the 'Instinct Robot World'. Finally, I show how two instances of Instinct can be used to achieve a second order control architecture.

Este trabalho tem por objetivo buscar, no discurso de Diogo Mainardi, regularidades que nos permitam reconhecer a construção de um modelo mental específico de representação do Presidente da República, Luis Inácio Lula da Silva, e de integrantes do Partido dos Trabalhadores (PT). O corpus compreende três crônicas, publicadas na Revista VEJA no período entre junho de 2006 e janeiro de 2007, Alicerçamos nossos estudos na Teoria Sociocognitiva e na Análise Crítica do Discurso (ACD), a partir do que indica Teun van Dijk (1983; 1991; 2004; 2005). Nossa pesquisa concluiu que Mainardi, por meio de manipulação contextual e da atribuição de características socialmente desfavoráveis, como corrupção, incompetência, incapacidade crítica e apego à noção de povo/popular, cria um modelo mental negativo do Presidente Lula e de integrantes do PT. / The aim of this work is to identify, in the discourse of Diogo Mainardi, patterns that might allow us to recognize the construction of a specific mental model of representation of the President of the Federal Republic of Brazil, Luis Inácio Lula da Silva, and of members of the Workers Party (PT). The corpus contains three chronicles published in the VEJA magazine, between June 2006 and January 2007. We based our studies on the principles of the Social Cognitive Theory and the Critical Discourse Analysis, as defined in the writings of Teun A. van Dijk (1983; 1991; 2004; 2005). Through our research, we come to the conclusion that Mainardi created a negative mental model of President Lula and of the members of PT, by using contextual manipulation and unfavorable social characteristics, such as corruption, incompetence, critical incapacity and attachment to the notion of people/popular.

Este trabalho tem por objetivo buscar, no discurso de Diogo Mainardi, regularidades que nos permitam reconhecer a construção de um modelo mental específico de representação do Presidente da República, Luis Inácio Lula da Silva, e de integrantes do Partido dos Trabalhadores (PT). O corpus compreende três crônicas, publicadas na Revista VEJA no período entre junho de 2006 e janeiro de 2007, Alicerçamos nossos estudos na Teoria Sociocognitiva e na Análise Crítica do Discurso (ACD), a partir do que indica Teun van Dijk (1983; 1991; 2004; 2005). Nossa pesquisa concluiu que Mainardi, por meio de manipulação contextual e da atribuição de características socialmente desfavoráveis, como corrupção, incompetência, incapacidade crítica e apego à noção de povo/popular, cria um modelo mental negativo do Presidente Lula e de integrantes do PT. / The aim of this work is to identify, in the discourse of Diogo Mainardi, patterns that might allow us to recognize the construction of a specific mental model of representation of the President of the Federal Republic of Brazil, Luis Inácio Lula da Silva, and of members of the Workers Party (PT). The corpus contains three chronicles published in the VEJA magazine, between June 2006 and January 2007. We based our studies on the principles of the Social Cognitive Theory and the Critical Discourse Analysis, as defined in the writings of Teun A. van Dijk (1983; 1991; 2004; 2005). Through our research, we come to the conclusion that Mainardi created a negative mental model of President Lula and of the members of PT, by using contextual manipulation and unfavorable social characteristics, such as corruption, incompetence, critical incapacity and attachment to the notion of people/popular.