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- Biological and Agricultural Engineering Education Technical Session
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- 2013 ASEE Annual Conference & Exposition
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Chehra Aboukinane; Daniel N. Moriasi, USDA-ARS; Ann L. Kenimer, Texas A&M University; Kim Dooley, Texas A&M University; James DUPE Linder, Texas A&M University
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Biological & Agricultural
Page 23.613.31965 (as listed in Dacey, 1985). The model considers both personal and cognitive traits ofcreative people, characteristics of the products creative individuals often produce, and thereflexive reactions observers usually have to those products (Table1).Table 1-Jackson and Messick’s four characteristics of creativity Traits of the Person Traits of the Product Intellectual Personality Product Reflective Traits Traits Properties Standards Reactions 1.Tolerance of Original Unusualness Norms Surprise incongruity 2. Analysis and Sensitive Appropriateness
- Conference Session
- Biological and Agricultural Engineering Education Technical Session
- Collection
- 2013 ASEE Annual Conference & Exposition
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Abby M Kelly, University of Nebraska, Lincoln; David Jones, University of Nebraska, Lincoln; Roger Michael Hoy, University of Nebraska; Evan Curtis, University of Nebraska, Lincoln; Angela Kaye Pannier, University of Nebraska, Lincoln; Richard R. Stowell P.E., University of Nebraska, Lincoln
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Biological & Agricultural
Page 23.697.7Students complete six assignments prior to the RDC competition to help move them through thedesign process. The assignments guide them to develop a problem statement, user needs,technical specifications, alternative solutions, testing procedures and data, and a final solution.Additionally, as part of their final solution selection assignment, students were required to getdesign approval from their faculty consultant. Finally, students complete an end of project surveyto encourage both individual and group reflection on the overall design process (Appendix I).Unlike at Bucknell University however, students were asked additional questions in the surveyabout the RDC itself to help faculty in the continuous improvement process and to
- Conference Session
- Biological and Agricultural Engineering Education Technical Session
- Collection
- 2013 ASEE Annual Conference & Exposition
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Ernest W. Tollner PE, University of Georgia; Qianqian Ma, University of Georgia; Caner Kazanci, University of Georgia
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Biological & Agricultural
particleattributes based on relationships between time and particular paths through the network taken byindividual particles.Patten and colleagues developed network environ analysis (NEA) [3, 5, 7, 19, 20], a form of EcologicalNetwork Analysis (ENA), to model the networks of complex ecological systems. Affording particularmathematical and ecological interpretive advantages, NEA uniquely represents objects as simultaneouslyparticipating in the dual environments of both their incoming and outgoing networks. NEA reflects theorganic holism of ecological systems and is by nature deterministic. Page 23.925.2Recently, Jørgensen and Nielsen [14], Fath