2 resultados para Software process improvement

em Digital Commons - Michigan Tech


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The Modeling method of teaching has demonstrated well--‐documented success in the improvement of student learning. The teacher/researcher in this study was introduced to Modeling through the use of a technique called White Boarding. Without formal training, the researcher began using the White Boarding technique for a limited number of laboratory experiences with his high school physics classes. The question that arose and was investigated in this study is “What specific aspects of the White Boarding process support student understanding?” For the purposes of this study, the White Boarding process was broken down into three aspects – the Analysis of data through the use of Logger Pro software, the Preparation of White Boards, and the Presentations each group gave about their specific lab data. The lab used in this study, an Acceleration of Gravity Lab, was chosen because of the documented difficulties students experience in the graphing of motion. In the lab, students filmed a given motion, utilized Logger Pro software to analyze the motion, prepared a White Board that described the motion with position--‐time and velocity--‐time graphs, and then presented their findings to the rest of the class. The Presentation included a class discussion with minimal contribution from the teacher. The three different aspects of the White Boarding experience – Analysis, Preparation, and Presentation – were compared through the use of student learning logs, video analysis of the Presentations, and follow--‐up interviews with participants. The information and observations gathered were used to determine the level of understanding of each participant during each phase of the lab. The researcher then looked for improvement in the level of student understanding, the number of “aha” moments students had, and the students’ perceptions about which phase was most important to their learning. The results suggest that while all three phases of the White Boarding experience play a part in the learning process for students, the Presentations provided the most significant changes. The implications for instruction are discussed.

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Waste effluents from the forest products industry are sources of lignocellulosic biomass that can be converted to ethanol by yeast after pretreatment. However, the challenge of improving ethanol yields from a mixed pentose and hexose fermentation of a potentially inhibitory hydrolysate still remains. Hardboard manufacturing process wastewater (HPW) was evaluated at a potential feedstream for lignocellulosic ethanol production by native xylose-fermenting yeast. After screening of xylose-fermenting yeasts, Scheffersomyces stipitis CBS 6054 was selected as the ideal organism for conversion of the HPW hydrolysate material. The individual and synergistic effects of inhibitory compounds present in the hydrolysate were evaluated using response surface methodology. It was concluded that organic acids have an additive negative effect on fermentations. Fermentation conditions were also optimized in terms of aeration and pH. Methods for improving productivity and achieving higher ethanol yields were investigated. Adaptation to the conditions present in the hydrolysate through repeated cell sub-culturing was used. The objectives of this present study were to adapt S. stipitis CBS6054 to a dilute-acid pretreated lignocellulosic containing waste stream; compare the physiological, metabolic, and proteomic profiles of the adapted strain to its parent; quantify changes in protein expression/regulation, metabolite abundance, and enzyme activity; and determine the biochemical and molecular mechanism of adaptation. The adapted culture showed improvement in both substrate utilization and ethanol yields compared to the unadapted parent strain. The adapted strain also represented a growth phenotype compared to its unadapted parent based on its physiological and proteomic profiles. Several potential targets that could be responsible for strain improvement were identified. These targets could have implications for metabolic engineering of strains for improved ethanol production from lignocellulosic feedstocks. Although this work focuses specifically on the conversion of HPW to ethanol, the methods developed can be used for any feedstock/product systems that employ a microbial conversion step. The benefit of this research is that the organisms will the optimized for a company's specific system.