6 resultados para Data-driven knowledge acquisition
em QSpace: Queen's University - Canada
Resumo:
The purpose of this study is to report the knowledge used in training and competition by 17 expert high-performance gymnastic coaches. A qualitative research methodology was used to collect and inductively analyze the data. The knowledge elicited for the competition component was categorized as competition site, competition floor, and trial competitions. These categories indicated that the coaches are minimally involved with the gymnasts in competition. The knowledge of the coaches elicited within the training component were categorized as coach involvement in training, intervention style, technical skills, mental skills, and simulation. Properties of these categories that were extensively discussed by the expert coaches, such as teaching progressions, being supportive, and helping athletes to deal with stress,are consistent with the literature on coaching and on sport psychology. Other aspects considered important in the sport psychology literature, such as developing concentration skills, were not discussed as thoroughly by the expert coaches.
Resumo:
Various sources have sought to consider the educational interventions that foster changes in perception of and attitudes toward nature, with the ultimate intent of understanding how education can be used to encourage environmentally responsible behaviours. With these in mind, the current study identified an outdoor environmental education program incorporating these empirically supported interventions, and assessed its ability to influence environmental knowledge, attitudes, and behaviours. Specifically, this study considered the following research questions: 1) To what degree can participation in this outdoor education program foster environmental knowledge and encourage pro-environmental attitudes and self-reported pro-environmental behaviours? 2) How is this effect different among students of different genders, and those who have different prior experiences in nature? Two motivational frameworks guided inquiry in the current study: the Value-Belief-Norm Model of Environmentalism (VBN) and the Theory of Planned Behaviour (TPB). The study employed a quantitative survey methodology, combining contemporary data measuring knowledge, attitudes, and behaviours with archived data collected by program staff, reflecting frequency of environmentally responsible behaviour. Further, a single qualitative item was included for which students provided “the first three words that [came] to mind when [they] think of the word nature.” Terms provided before and after the program were compared for differences in theme to detect subtle or underlying changes. Quantitative results indicated no significant change in student knowledge or attitudes through the outdoor environmental education program. However, a significant change in self-reported behaviour was identified from both the contemporary and archived data. This agreement in positive findings across the two data sets, collected using different measures and different participants, lends evidence of the program’s ability to encourage self-reported pro-environmental behaviour. Further, qualitative results showed some change in students’ perceptions of nature through the program, providing direction for future research. These findings suggest that this particular outdoor education program was successful in encouraging students’ self-reported environmentally responsible behaviour. This change was achieved without significant change in knowledge or environmental attitudes, suggesting that external factors not measured in this study might have played a role in affecting behaviour.
Resumo:
One of the global phenomena with threats to environmental health and safety is artisanal mining. There are ambiguities in the manner in which an ore-processing facility operates which hinders the mining capacity of these miners in Ghana. These problems are reviewed on the basis of current socio-economic, health and safety, environmental, and use of rudimentary technologies which limits fair-trade deals to miners. This research sought to use an established data-driven, geographic information (GIS)-based system employing the spatial analysis approach for locating a centralized processing facility within the Wassa Amenfi-Prestea Mining Area (WAPMA) in the Western region of Ghana. A spatial analysis technique that utilizes ModelBuilder within the ArcGIS geoprocessing environment through suitability modeling will systematically and simultaneously analyze a geographical dataset of selected criteria. The spatial overlay analysis methodology and the multi-criteria decision analysis approach were selected to identify the most preferred locations to site a processing facility. For an optimal site selection, seven major criteria including proximity to settlements, water resources, artisanal mining sites, roads, railways, tectonic zones, and slopes were considered to establish a suitable location for a processing facility. Site characterizations and environmental considerations, incorporating identified constraints such as proximity to large scale mines, forest reserves and state lands to site an appropriate position were selected. The analysis was limited to criteria that were selected and relevant to the area under investigation. Saaty’s analytical hierarchy process was utilized to derive relative importance weights of the criteria and then a weighted linear combination technique was applied to combine the factors for determination of the degree of potential site suitability. The final map output indicates estimated potential sites identified for the establishment of a facility centre. The results obtained provide intuitive areas suitable for consideration
Resumo:
An investigation into karst hazard in southern Ontario has been undertaken with the intention of leading to the development of predictive karst models for this region. The reason these are not currently feasible is a lack of sufficient karst data, though this is not entirely due to the lack of karst features. Geophysical data was collected at Lake on the Mountain, Ontario as part of this karst investigation. This data was collected in order to validate the long-standing hypothesis that Lake on the Mountain was formed from a sinkhole collapse. Sub-bottom acoustic profiling data was collected in order to image the lake bottom sediments and bedrock. Vertical bedrock features interpreted as solutionally enlarged fractures were taken as evidence for karst processes on the lake bottom. Additionally, the bedrock topography shows a narrower and more elongated basin than was previously identified, and this also lies parallel to a mapped fault system in the area. This suggests that Lake on the Mountain was formed over a fault zone which also supports the sinkhole hypothesis as it would provide groundwater pathways for karst dissolution to occur. Previous sediment cores suggest that Lake on the Mountain would have formed at some point during the Wisconsinan glaciation with glacial meltwater and glacial loading as potential contributing factors to sinkhole development. A probabilistic karst model for the state of Kentucky, USA, has been generated using the Weights of Evidence method. This model is presented as an example of the predictive capabilities of these kind of data-driven modelling techniques and to show how such models could be applied to karst in Ontario. The model was able to classify 70% of the validation dataset correctly while minimizing false positive identifications. This is moderately successful and could stand to be improved. Finally, suggestions to improving the current karst model of southern Ontario are suggested with the goal of increasing investigation into karst in Ontario and streamlining the reporting system for sinkholes, caves, and other karst features so as to improve the current Ontario karst database.
Resumo:
Quantitative methods can help us understand how underlying attributes contribute to movement patterns. Applying principal components analysis (PCA) to whole-body motion data may provide an objective data-driven method to identify unique and statistically important movement patterns. Therefore, the primary purpose of this study was to determine if athletes’ movement patterns can be differentiated based on skill level or sport played using PCA. Motion capture data from 542 athletes performing three sport-screening movements (i.e. bird-dog, drop jump, T-balance) were analyzed. A PCA-based pattern recognition technique was used to analyze the data. Prior to analyzing the effects of skill level or sport on movement patterns, methodological considerations related to motion analysis reference coordinate system were assessed. All analyses were addressed as case-studies. For the first case study, referencing motion data to a global (lab-based) coordinate system compared to a local (segment-based) coordinate system affected the ability to interpret important movement features. Furthermore, for the second case study, where the interpretability of PCs was assessed when data were referenced to a stationary versus a moving segment-based coordinate system, PCs were more interpretable when data were referenced to a stationary coordinate system for both the bird-dog and T-balance task. As a result of the findings from case study 1 and 2, only stationary segment-based coordinate systems were used in cases 3 and 4. During the bird-dog task, elite athletes had significantly lower scores compared to recreational athletes for principal component (PC) 1. For the T-balance movement, elite athletes had significantly lower scores compared to recreational athletes for PC 2. In both analyses the lower scores in elite athletes represented a greater range of motion. Finally, case study 4 reported differences in athletes’ movement patterns who competed in different sports, and significant differences in technique were detected during the bird-dog task. Through these case studies, this thesis highlights the feasibility of applying PCA as a movement pattern recognition technique in athletes. Future research can build on this proof-of-principle work to develop robust quantitative methods to help us better understand how underlying attributes (e.g. height, sex, ability, injury history, training type) contribute to performance.
Resumo:
This dissertation offers a critical international political economy (IPE) analysis of the ways in which consumer information has been governed throughout the formal history of consumer finance (1840 – present). Drawing primarily on the United States, this project problematizes the notion of consumer financial big data as a ‘new era’ by tracing its roots historically from late nineteenth century through to the present. Using a qualitative case study approach, this project applies a unique theoretical framework to three instances of governance in consumer credit big data. Throughout, the historically specific means used to govern consumer credit data are rooted in dominant ideas, institutions and material factors.