5 research outputs found

    Exploring Motivations for Intercollegiate Debate Participation

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    This study seeks to use qualitative interviewing and grounded theory analytical methods to explore motivations for intercollegiate debate participation, as well as to update and expand existing research on the subject. This study found that students participate for a variety of reasons including an affinity for competition, enjoyment of the process of debate, the acquisition of skills and perspectives, and finding a sense of community within both their debate squads and the broader debate community. Further, this study found that students remain motivated to participate in debate despite competing demands on their time by strategizing completion of coursework, satisfying social needs within debate, and modifying existing extracurricular and familial commitments to best serve their needs. This study is limited by its small sample size and the corresponding limitation of perspectives. Despite its limitations, this study provided useful insights into how debaters communicate their motivation to join and stay involved in debate and offered explanations for motivating factors

    Systems engineering and integration: Cost estimation and benefits analysis

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    Space Transportation Avionics hardware and software cost has traditionally been estimated in Phase A and B using cost techniques which predict cost as a function of various cost predictive variables such as weight, lines of code, functions to be performed, quantities of test hardware, quantities of flight hardware, design and development heritage, complexity, etc. The output of such analyses has been life cycle costs, economic benefits and related data. The major objectives of Cost Estimation and Benefits analysis are twofold: (1) to play a role in the evaluation of potential new space transportation avionics technologies, and (2) to benefit from emerging technological innovations. Both aspects of cost estimation and technology are discussed here. The role of cost analysis in the evaluation of potential technologies should be one of offering additional quantitative and qualitative information to aid decision-making. The cost analyses process needs to be fully integrated into the design process in such a way that cost trades, optimizations and sensitivities are understood. Current hardware cost models tend to primarily use weights, functional specifications, quantities, design heritage and complexity as metrics to predict cost. Software models mostly use functionality, volume of code, heritage and complexity as cost descriptive variables. Basic research needs to be initiated to develop metrics more responsive to the trades which are required for future launch vehicle avionics systems. These would include cost estimating capabilities that are sensitive to technological innovations such as improved materials and fabrication processes, computer aided design and manufacturing, self checkout and many others. In addition to basic cost estimating improvements, the process must be sensitive to the fact that no cost estimate can be quoted without also quoting a confidence associated with the estimate. In order to achieve this, better cost risk evaluation techniques are needed as well as improved usage of risk data by decision-makers. More and better ways to display and communicate cost and cost risk to management are required

    The Faster, Better, Cheaper Approach to Space Missions: An Engineering Management Assessment

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    This paper describes, in viewgraph form, the faster, better, cheaper approach to space missions. The topics include: 1) What drives "Faster, Better, Cheaper"? 2) Why Space Programs are Costly; 3) Background; 4) Aerospace Project Management (Old Culture); 5) Aerospace Project Management (New Culture); 6) Scope of Analysis Limited to Engineering Management Culture; 7) Qualitative Analysis; 8) Some Basic Principles of the New Culture; 9) Cause and Effect; 10) "New Ways of Doing Business" Survey Results; 11) Quantitative Analysis; 12) Recent Space System Cost Trends; 13) Spacecraft Dry Weight Trend; 14) Complexity Factor Trends; 15) Cost Normalization; 16) Cost Normalization Algorithm; 17) Unnormalized Cost vs. Normalized Cost; and 18) Concluding Observations
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