5 resultados para conceptual data modelling

em Brock University, Canada


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The purpose of this study was to assess the effects of changing a nursing documentation system, developed from King's Conceptual Framework, on the use of the nursing process. The null hypothesis was that there would be no significant increase in the reflection of the use of the nursing process on the nursing care plan or nurses' notes, as a result of using a nursing documentation system developed using King's Conceptual Framework (1981). The design involved the development of a questionnaire that was used to review health records pre and post implementation of a documentation system developed based on King's Conceptual Framework and Theory of Goal Attainment (1981). A Record Completeness Score was obtained from some of the questions. The null hypothesis was rejected. The results of the study have implications for nursing administration and the evaluation of nursing practice. If the use of a documentation system developed from a conceptual framework increases the reflection of the nursing process on the patient's health record, nursing will have the means to measure patient outcomes/goal attainment. All health care organizations and levels of government are focusing on methods to monitor and control the health-care dollar. In order for nursing to clearly determine the costs associated with nursing care, measurement of patient outcomes/goal attainment will need to be possible. In order to measure patient outcomes/goals attainment nurses will need to be able to collect data on their practice. It will be critical that nursing have a documentation system in place which facilitates the reflection of the nursing process within a theoretical framework.

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This thesis describes research in which genetic programming is used to automatically evolve shape grammars that construct three dimensional models of possible external building architectures. A completely automated fitness function is used, which evaluates the three dimensional building models according to different geometric properties such as surface normals, height, building footprint, and more. In order to evaluate the buildings on the different criteria, a multi-objective fitness function is used. The results obtained from the automated system were successful in satisfying the multiple objective criteria as well as creating interesting and unique designs that a human-aided system might not discover. In this study of evolutionary design, the architectures created are not meant to be fully functional and structurally sound blueprints for constructing a building, but are meant to be inspirational ideas for possible architectural designs. The evolved models are applicable for today's architectural industries as well as in the video game and movie industries. Many new avenues for future work have also been discovered and highlighted.

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Behavioral researchers commonly use single subject designs to evaluate the effects of a given treatment. Several different methods of data analysis are used, each with their own set of methodological strengths and limitations. Visual inspection is commonly used as a method of analyzing data which assesses the variability, level, and trend both within and between conditions (Cooper, Heron, & Heward, 2007). In an attempt to quantify treatment outcomes, researchers developed two methods for analysing data called Percentage of Non-overlapping Data Points (PND) and Percentage of Data Points Exceeding the Median (PEM). The purpose of the present study is to compare and contrast the use of Hierarchical Linear Modelling (HLM), PND and PEM in single subject research. The present study used 39 behaviours, across 17 participants to compare treatment outcomes of a group cognitive behavioural therapy program, using PND, PEM, and HLM on three response classes of Obsessive Compulsive Behaviour in children with Autism Spectrum Disorder. Findings suggest that PEM and HLM complement each other and both add invaluable information to the overall treatment results. Future research should consider using both PEM and HLM when analysing single subject designs, specifically grouped data with variability.

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Mobile augmented reality applications are increasingly utilized as a medium for enhancing learning and engagement in history education. Although these digital devices facilitate learning through immersive and appealing experiences, their design should be driven by theories of learning and instruction. We provide an overview of an evidence-based approach to optimize the development of mobile augmented reality applications that teaches students about history. Our research aims to evaluate and model the impacts of design parameters towards learning and engagement. The research program is interdisciplinary in that we apply techniques derived from design-based experiments and educational data mining. We outline the methodological and analytical techniques as well as discuss the implications of the anticipated findings.

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Mobile augmented reality applications are increasingly utilized as a medium for enhancing learning and engagement in history education. Although these digital devices facilitate learning through immersive and appealing experiences, their design should be driven by theories of learning and instruction. We provide an overview of an evidence-based approach to optimize the development of mobile augmented reality applications that teaches students about history. Our research aims to evaluate and model the impacts of design parameters towards learning and engagement. The research program is interdisciplinary in that we apply techniques derived from design-based experiments and educational data mining. We outline the methodological and analytical techniques as well as discuss the implications of the anticipated findings.