Background: The quality of team-based care impacts patient post-hospitalization outcomes, yet there is a gap in our understanding of how specific team processes impact patient post-hospitalization outcomes. Shared Mental Models (SMMs) is a team process from organizational psychology; it provides an understanding of how providers coordinate complex tasks as a team. SMMs are the team members’ organized knowledge needed for effective team performance. Military research shows that teams with more convergent SMMs have higher performance and better outcomes. In healthcare, patient discharge exemplifies an activity that requires a high level of coordination among interprofessional team members. Two relevant domains of SMMs are Taskwork SMM (team assessment of patient’s readiness for hospital discharge) and Teamwork SMM (quality of day of discharge teamwork). Because of the newness of SMM to healthcare, we lack measures to understand SMMs among interprofessional discharge teams. Study Purpose & Aims: The purpose was to pilot a novel measurement approach assessing SMMs of discharge teams, and explore their relationships to patient 30-day post-hospitalization outcomes (quality of care transition and utilization of unplanned medical services). Aim 1 determined the content and degree of convergence of discharge teams’ SMMs (taskwork and teamwork). Aim 2 examined the relationship between discharge team SMMs and patient post-hospitalization outcomes. Methods: A prospective longitudinal pilot study was used to examine the SMMs of 64 unique discharge events in three inpatient units at a single hospital. Discharge team members independently completed a questionnaire measuring the Teamwork SMM (using the Shared Mental Model Scale) and the Taskwork SMM (using the Discharge Provider-Readiness for Hospital Discharge Scale). Data were collected from the patient 30 days post-discharge to determine the quality of transition (using the Care Transition Measure or CTM-15) and use of unplanned utilization of medical services (unplanned readmission or ED visit). Interrater Agreement (r*wg(j)) was used to determine the SMM convergence (or level of agreement) among the discharge team. The relationship between SMMs and the quality of transition outcome (n = 42) was determined using standard regression analysis. Logistic regression was used determine the relationship of SMMs with utilization of unplanned medical services (n = 56). Results: Overall, discharge teams reported high levels of Taskwork SMMs (M = 8.46, SD =.91) and Taskwork SMM Convergence (M = .90, SD =.10), indicating that the discharge team perceived and agreed that patients had high levels of readiness for hospital discharge. Discharge teams also reported having high-quality Teamwork SMMs (M = 6.11, SD = 0.39) and Teamwork SMM Convergence (M = .85, SD = .10), suggesting that most discharge teams perceived and agreed that high quality teamwork was provided during the discharge process. Discharge events from the three inpatient units significantly differed in their Teamwork and Teamwork SMM content and convergence scores. Discharge teams’ Teamwork SMMs and Taskwork SMMs were positively associated with the CTM-15 score, while controlling for key contextual factors (t = 3.94, p = .001; t = 3.94, p = .001, respectively). Conclusion : Discharge teams’ Taskwork SMM and Teamwork SMM was positively associated with patient-reported quality of transition from the hospital. There was insufficient evidence to support that utilization of unplanned medical services is related to discharge teams’ SMMs. Measuring the SMMs of the discharge team provides a method for assessing a team process critical to safe patient discharges.

This research was conducted to determine if students receiving complex systems instruction in the form of software simulations recognize patterns and underlying elements of complex systems more effectively than students receiving traditional instruction. Complex systems were investigated with an analytic (reductive) approach in a control group and with a synthesis approach in the treatment group. Exploration of this top-down approach to learning complex systems counters traditional bottom-up methodologies, investigating systems and subsystems at the component level. The hypothesis was that students experiencing complex systems scenarios in a computer-based learning environment would outperform their counterparts by constructing a greater number of explanations with emergent-like responses. A mixed method experimental, pretest posttest, control group triangulation design research study was designed for high school students enrolled in an Introduction to Technology and Engineering course. A pretest consisting of one open-ended near transfer problem and one far transfer problem was administered, investigating the generation of reductive (clockwork) and complex (emergent-like) mental models. A stratified sampling procedure was used to assign students to control or treatment groups. Following treatment, an analysis of covariance failed to reveal statistically significant evidence supporting the hypothesis. However, qualitative data in the form of student transcriptions, daily lab reports, and data entry worksheets revealed evidence of emergent-like response and behaviors.

This thesis consists of a series of internationally published, peer reviewed, conference research papers and one journal paper. The papers evaluate and further develop two modelling methods for use in Information Technology (IT) design and for the educational and training needs of students within the area of computer and network technology. The IT age requires technical talent to fill positions such as network managers, web administrators, e-commerce consultants and network security experts as IT is changing rapidly, and this is placing considerable demands on higher educational institutions, both within Australia and internationally, to respond to these changes.

This thesis explores the application of personal construct psychology and the repertory grid to performance management in a technical consulting organisation. The research examines what is important for a manager in assessing work performance and how each manager's mental model for performance compares with his/her peers. Managers acting as raters are the critical link in the observation and assessment of performance and in the feedback process. Rater observations and judgements are affected by their personal mental models regarding what is important. These views may or may not accord with those of their peers, resulting in inconsistency and unfair assessments, or with what the organisation's strategy demands. Understanding rater views on what is important, and how well these align with strategy, is a key to ensure that the appraisal process supports, rather than hinders, both individual and organisational needs. Each manager's personal constructs relating to appraisal were elicited through a repertory grid interview. The elicited constructs were taken together and categorised to derive broad performance categories summarising the views of the entire management team. Each individual's personal constructs were then allocated to the relevant common category to develop a view of how each manager related to the group's overall approach to appraisal. A measure for the importance of each category in making performance judgments (importance score) was derived based on the correlation of the constructs in each category with an overall performance construct. A second measure of a manager's preparedness to discriminate between levels of performance was also derived (discriminant score) based on the variation in each manager's construct structure. In keeping with the personal construct psychology approach, the process emphasizes the importance of discussion with the individual concerned to verify the sorting and ranking pro cess. A ranking process to establish the overall management group priorities for judging performance (team mental models) was demonstrated and a charting process was developed to facilitate presentation and discussion of the results. The research has demonstrated the strength of the repertory grid process as a means of getting at a rater's framework for thinking about appraisal and provides a way to identify possible voids or blind spots in a rater's approach. Understanding the most important categories of performance used by raters provides an opportunity for management to determine whether these are likely to achieve the objectives of the company, and if necessary, to introduce and inculcate different approaches.

<p>The spread of influenza A subtype H5N1 has recently heightened pandemic concern and preparedness for a pandemic influenza virus has become a global priority. Research in risk communication emphasizes the importance of providing the recipients with information they need to make informed independent judgments. This entails understanding how these judgments are made, and what kind of information that serves this purpose. Decisions have been examined in a wide variety of scientific disciplines and produced several interesting methods and models to understand judgment and decisions. These methods and models were investigated and compared with regard to their fit to these conditions.</p><p>The work in this thesis was oriented toward three main questions. The first question was how to find out how people would react during an emergency. The second question was what kind of research in decision theory could explain and be used to predict these results. The third question was whether a mental model of the threat of pandemic influenza can be described, and what is its implication on risk communication.</p><p>A mental model approach to explore risk communications was used with qualitative interviews with health care workers in Östergötland, Sweden. The transcripts were analyzed according to methods drawn from mental models research and risk communication to extract influence diagrams. These influence diagrams serves as an abstract representation of the respondents’ mental model of the threat of pandemic influenza. This influence diagram was compared to a corresponding expert mental model developed from literature and interviews with influenza experts.</p><p>The mental models approach has been shown to provide a description of comprehension with several benefits. One benefit is that the method is a relatively easy way to gather notions in the target population which can be used for drafting risk information. Another benefit is that the existing notions and sense of causal patterns can be described, instead of merely memorized facts.</p><p>The comparison between the mental models of health care workers and influenza experts revealed both functional and destructive misconceptions. Unrelated information received by the respondents was also shown to be linked together in a way that is in conflict with expert knowledge. This tendency to create causal connections in order to organize knowledge may be important to consider in risk communication.</p>

Solving physics problem in university physics education with a computational approach requires knowledge and skills in several domains, for example, physics, mathematics, programming, and modelling. These competences are in turn related to students' beliefs about these domains as well as about learning, and their motivation to learn. The purpose of this thesis was to investigate the role of university physics students' knowledge, beliefs and motivation when solving and visualizing a physics problem using a computational approach. The results showed that expert-like beliefs about physics and learning physics together with prior knowledge were important predictors of the quality of performance. Feelings corresponding to control and concentration, i.e., emotions that are expected to be good indicators of students' motivation were also good predictors of performance. However, intrinsic motivation, as indicated by enjoyment and interest, together with beliefs expressing students' personal interest and utility value, did not predict performance to any higher extent. Instead, my results indicate that integration and identification of expert-like beliefs about learning and concentration and control emotions during learning are more influential on the quality of performance. Thus, the results suggest that the development of students' epistemological beliefs is important for students' ability to learn from realistic problem-solving situations with many degrees of freedom in physics education. In order to investigate knowledge and beliefs structures network modeling has been applied as a novel tool for analysis. Students' epistemic frames are analyzed before and after the task in computational physics using a network analysis approach on interview transcripts, producing visual representations of mental models. The results show that students change their epistemic framing from a modelling task, with expectancies about learning programming, to a physics task, in which they are challenged to use physics principles and conservation laws in order to troubleshoot and understand their simulations. This implies that the task, even though it is not introducing any new physics, helped the students to develop a more consistent view of the importance of using physics principles in problem solving. When comparing students' framing with teachers,' it is shown that although teachers and students agree on the main features of simulation competence in physics, differences in their epistemic networks can be distinguished. For example, while teachers believe that numerical problem solving facilitates fundamental understanding of physics and mathematics, this is not obvious to students. This implies that university teachers need to be aware of these differences as well as students' beliefs in order to challenge students' expectations and to give support concerning the learning objectives of the assignment.

In general academic research and discussion on stand-alone games or the broader computer games, scholars often use questionnaires and quantitative methods to analyze consumers' perceptions and opinions of game-related issues. Due to the limitations in research methods, previous research results are somewhat difficulty to make marketing companies or decision-making departments deeply understand consumers' ultimate mental imagery and consensus mode. Therefore, nowadays stand-alone game companies often spent a lot of expenses, but can not produce the games that meet consumers' core demand. According to the report released on September 7 2011 by the U.S. market survey center, DFC Intelligence, which specializes in the video game market, it estimates that the scale of the global market of video games will grow to 81 billion U.S. dollars in 2016 from 66 billion U.S. dolloars in 2010. This figure not only symbolizes the boom and huge business opportunities of game market but also affects the changes of the next-generation video game industry, which highlights the importance of conducting related research. This study uses a mental image mode, ZMET metaphor extraction techniques, invented by Harvard University Professor Zaltman as the research method, trying to elicit contruct factors of six senior consumers for the stand-alone game, FINAL FANTASY VII, through image analysis. Research results can provide marketing implications to stand-alone game companies so that they can understand consumer needs and expectations by the imagery constructs and mental models of the senior players. The results of ZMET technical analysis got a total of 122 different constructs from six respondents, from which 49 common constructs were further extracted. This study found HVM hierarchical value consensus mental map among the six senior players and clarified the evolution of the six respondents' imagery constructs of the game and consensus model. As to the final structure constructs in HVM hierarchical value map, five ultimate values are identified, "players' favorability", "looking to the future," "witness", "dreams come true", and "classic". The ultimate values combined by the five non-verbal information can provide marketers and game designers in stand-alone game companies, a reference for future marketing decisions. Additionally, based on the research findings, marketers can design better stand-alone games that meet consumer demands, in order to effectively increase the sales and economic benefits for game companies.

In today’s competitive market, it is essential to be innovative and creative for an industry to sustain. Industry need to introduce new products to the market. Engineering idea generation plays a vital role in the development of new products. This research study is focused on the engineering idea generation. The representations of ideas have an important impact on the idea generation process. Design concepts may be represented in a variety of forms like sketches, physical models or computer based models. The goal of this research is to understand how these various representations affect design cognition. In this thesis, three studies showing the effects of two different representations in the idea generation process are presented. The first study focuses on the effects of physical models in engineers’ design cognition. This preliminary study investigates two different hypotheses: (1) Physical models supplement and improve designer’s mental models and (2) Physical models induce design fixation. The results show that physical models supplement the designer’s mental models but fail to enhance them. No evidence of design fixation is observed. The second and third studies investigate the effects of computer-based idea generation software on design cognition. The research questions investigated in this study are: (1) How does the use of this software tool assist design cognition? (2) How can the software interface be improved so that designers can generate ideas more easily? To answer these questions, a between-subjects idea generation experiment is conducted. In the experiment, the participants are asked to generate ideas to solve a design problem with and without the software. The results show that participants who generated ideas with the help of the software tool have less quantity of ideas compared to the control group. This may be due to the design fixation induced by the concepts presented. In the third study, the opinions of the participants for the improvements of the software interface are collected. Results show that participants do not have any preference of one way of clustering the concepts over the other. The results of this study also provide creative input for the future improvement of the software.

The purpose of the current study was to assess the efficacy of mental models as a predictor of driving outcomes. In contrast to more traditional measures of knowledge, mental models capture the configural property of knowledge, that is, an individual's understanding of the interrelationships that exist among critical concepts within a particular knowledge domain. Given that research has consistently shown the usefulness of mental models for the prediction of performance in a number of settings, it was hypothesized that the development of accurate driving mental models would also play an important role in the prediction of driving outcomes, especially in comparison to traditional measures of driving knowledge—such as the multiple-choice type tests typically required to obtain a driver license. Mental models of 130 college students (52 percent females) between 17 and 21 years-old (M = 18.68, SD = 0.80) were analyzed and compared to a subject matter expert (SME) referent structure using Pathfinder. A statistically significant correlation was found for mental model accuracy and moving violations (r = –.18, p <.05), but not for at-fault crashes. Evidence of incremental validity of mental models over commonly used predictors of moving violations (but not for at-fault crashes) was also found. Exploratory analyses revealed that driving knowledge, general mental ability (GMA), and emotional stability were the best predictors of mental model accuracy. Issues related to the measurement of mental models were extensively addressed. First, statistically significant correlations between GMA and several mental model properties (i.e., accuracy scores, within participant similarity, and within participant correlation) suggest that challenges inherent to the task for eliciting mental models may influence mental model scores which, in turn, may lower mental model reliability estimates. Also, the selection of model components (i.e., terms) and the identification of the "best" reference structure for deriving mental model accuracy scores are undoubtedly critical aspects of mental model-related research. Along with illustrating the decisions made in the context of this particular study, some suggestions for conducting mental model-related research are provided.

The primary purpose of this study was to determine the effectiveness of implementing desktop 3-dimensional (3D) stereo images of human anatomy into an undergraduate human anatomy distance laboratory. User perceptions of 2D and 3D images were gathered via questionnaire in order to determine ease of use and level of satisfaction associated with the 3D software in the online learning environment. Mayer's (2001, p. 184) principles of design were used to develop the study materials that consisted of PowerPoint presentations and AVI files accessed via Blackboard. The research design employed a mixed-methods approach. Volunteers each were administered a demographic survey and were then stratified into groups based upon pre-test scores. A total sample size of 62 pairs was available for combined data analysis. Quantitative research questions regarding the effectiveness of 2D versus the 3D treatment were analyzed using a doubly-multivariate repeated measures (Doubly- MANOVA) design. Paired test scores achieved by undergraduates on a laboratory practical of identification and spatial relationships of the bones and features of a human skull were used in the analysis. The questionnaire designed to gather user perceptions consisted of quantitative and qualitative questions. Response frequencies were analyzed for the two groups and common themes were noted. Results revealed a statistically significant difference in group means for the main effect of the treatment groups 2D and 3D and for the variables of identification and relationship with the 3D group outperforming the 2D group on both dependent variables. Effect sizes were determined to be small, 0.215 for the identification variable and 0.359 for the relationship variable. Overall, all students liked the convenience of using PowerPoint and AVI files online. The 3D group felt their PowerPoint was more realistic than did the 2D group and both groups appreciated the detailed labeling of the online images. One third of the volunteers in the 3D group indicated that "eye strain" was what they liked least about working with the 3D images. Results indicate that desktop, stereo imaging may be incorporated effectively into online anatomy and physiology courses, but that more work needs to be done to ensure less eye strain.