<p>Problem framing is an essential stage in engineering design mainly because it is crucial in developing solutions to design problems. Engineers’ ability to frame a problem is naturally attributed to their reasoning abilities and expertise. Traditionally, our understanding of the type of reasoning is originated from cognitive sciences, sociology, and psychological theories of reasoning. Design reasoning models developed from these disciplines contributed significantly to understanding design reasoning. However, a different standpoint for understanding specialized form of knowledge and reasoning that are unique to engineering practices is needed.</p> <p>An important contribution of this dissertation to the body of research is its use of a new theoretical model, Design Reasoning Quadrants, developed to help organize types of design reasoning at the intersection of two axes, the disciplinary-multidisciplinary reasoning axis and theoretical-practical reasoning axis. Further, this dissertation uses the Design Reasoning Quadrants framework to understand first-year engineering students' reasoning while framing design problems. Prior research stated that it is necessary to elicit the forms of reasoning beginner students have while dealing with design problems, to improve problem-solving abilities. Therefore, this dissertation addresses the need to understand first-year engineering students' reasoning, while engaging in problem framing using four design reasoning quadrants: experiential observations, first principles, trade-offs, and complex abstractions.</p> <p>This dissertation examined changes in first-year engineering students’ design reasoning during problem framing across two different design projects students explored within a semester in an engineering course. The main data sources were answers to a questionnaire students completed in the first and final design project as the first-in-lecture activity for problem framing. Students answered each questionnaire individually. The analysis took place in two stages. </p> <p>First, a deductive analysis was conducted to identify types of reasoning in students’ formulated questions to understand a problem. Using a multinomial logit model and descriptive statistics, differences in the theoretical-practical and disciplinary-multidisciplinary reasoning through the time were identified. Second, students’ answers to the design reasoning quadrants’ questions were analyzed deductively and inductively. This analysis aimed to identify students’ design reasoning patterns when elicited in one of the four design reasoning quadrants.</p> <p>The results of the deductive analysis indicated that regardless of the design project, student reasoning in terms of the theoretical-practical reasoning is not significantly different between the two time points. However, students’ reasoning was more heavily disciplinary-focused in the second project and more multidisciplinary in the first design project. The results of the inductive analysis helped further explain this result. This analysis revealed that students were more familiar with the context and disciplinary concepts for the first rather than for the second design project.</p> <p>The results of this dissertation and framework can help researchers further understand how students reason from the perspective of the nature of engineering. In addition, understanding the type of reasoning students use while framing a problem will allow educators to understand the reasoning beginner students employ while framing a problem and to develop better learning experiences to enhance problem-solving skills.</p>

This research explores the potential of retrofitting enhanced or extended-depressed tree pits (ETPs/EDTPs) around existing street trees to bolster pre-development hydrological processes in two Hamiltonian neighbourhoods to help satisfy their social, economic, and environmental needs and work toward the Sustainable Development Goals (SDGs). Using QGIS and openly available data to create catchment areas, establish the feasibility of a 20:1 catchment to pit area ratio, and investigate the performance of five available structured soil cells, the innovative Analytical Probabilistic Model (APM) for Bioretention systems was adapted to conduct a parametric sensitivity analysis and subsequently compute the Road Runoff Reduction Efficiency (RRRE) of the designs under different climatic scenarios. The catchment to pit area ratio, design storage depth, and final infiltration rate were found to have a significant impact on the RRRE while the average evapotranspiration rate did not. Based on a 75% efficiency cut-off, and assuming a 20:1 catchment to pit area ratio, the shallowest two depths were deemed ineffective in all final infiltration rate scenarios while the largest depth provided efficiencies greater than 75% runoff reduction even when faced with the lowest rate of 6 mm hr-1. Comparing the RRRE during current climatic conditions to a simulated 2050s winter suggests that the RRRE of the deepest implementation is impacted only half as much as the shallowest; larger systems are more resilient. This research has reinforced the versatility and efficiency of the Analytical Probabilistic Model for modeling system performance of LIDs and ETPs, supports the prominent findings of the efficacy of enhanced tree pits to significantly contribute to urban stormwater management and re-establish more natural and sustainable hydrologic processes, and promotes them as a key to reaching the SDGs in Hamilton, Ontario. / Thesis / Master of Applied Science (MASc) / The Sustainable Development Goals call for action from every member of society. This research explores the potential Stormwater Management Engineers have to do so by retrofitting street trees with Enhanced or Extended-Depressed Tree Pits, increasing rooting volume and offering the tree more water from the adjacent road to simultaneously meet the natural needs of the tree and reduce urban runoff.