Evaluation of a professional development curriculum in movement education and adapted physical activity for invisible disabilities : a critical cross-case analysis

Movement education and adapted physical activity are content areas not addressed in pre-service education or in-service training for Ontario practitioners working with individuals with disabilities in physical environments. Consequently, physical activity is often overlooked by service providers in programming and intervention for exceptional young learners. A formative evaluation, multiple-case study design was employed in this research in which a purposeful sample of expert practitioners performed a guided, descriptive evaluation of a three-day professional development workshop curriculum designed to supplement these areas lacking in professional preparation within their respective cohorts. Case-by-case and comparative analyses illustrated the inherent assumptions and societal constraints which prioritize the structure of professional development within the education system and other government organizations providing services for school-aged persons with disabilities in Ontario. Findings, discussed from a critical postmodern perspective, illustrate the paradoxical nature of Western values and prevailing mind/body dichotomy that guide professional practice in these fields.

Automatic Structure Generation using Genetic Programming and Fractal Geometry

Three dimensional model design is a well-known and studied field, with numerous real-world applications. However, the manual construction of these models can often be time-consuming to the average user, despite the advantages o ffered through computational advances. This thesis presents an approach to the design of 3D structures using evolutionary computation and L-systems, which involves the automated production of such designs using a strict set of fitness functions. These functions focus on the geometric properties of the models produced, as well as their quantifiable aesthetic value - a topic which has not been widely investigated with respect to 3D models. New extensions to existing aesthetic measures are discussed and implemented in the presented system in order to produce designs which are visually pleasing. The system itself facilitates the construction of models requiring minimal user initialization and no user-based feedback throughout the evolutionary cycle. The genetic programming evolved models are shown to satisfy multiple criteria, conveying a relationship between their assigned aesthetic value and their perceived aesthetic value. Exploration into the applicability and e ffectiveness of a multi-objective approach to the problem is also presented, with a focus on both performance and visual results. Although subjective, these results o er insight into future applications and study in the fi eld of computational aesthetics and automated structure design.

Genetic Programming for Non-Photorealistic Rendering

This thesis focuses on developing an evolutionary art system using genetic programming. The main goal is to produce new forms of evolutionary art that filter existing images into new non-photorealistic (NPR) styles, by obtaining images that look like traditional media such as watercolor or pencil, as well as brand new effects. The approach permits GP to generate creative forms of NPR results. The GP language is extended with different techniques and methods inspired from NPR research such as colour mixing expressions, image processing filters and painting algorithm. Colour mixing is a major new contribution, as it enables many familiar and innovative NPR effects to arise. Another major innovation is that many GP functions process the canvas (rendered image), while is dynamically changing. Automatic fitness scoring uses aesthetic evaluation models and statistical analysis, and multi-objective fitness evaluation is used. Results showed a variety of NPR effects, as well as new, creative possibilities.

Evaluation in Sport for Development: A Case Study of the Gansbaai Project, Football Foundation of South Africa, From A Critical Perspective

The purpose of this case study was to determine the effectiveness of sport for development (SDP) evaluation within one program in Gansbaai, South Africa through critical, independent participant inclusive program evaluation. Qualitative research was conducted on the Football Foundation of South Africa (FFSA), where semi-structured interview data were collected from administrators and participants, as were data from direct participant observations and organizational documents. Data analysis followed, according to Kvale and Brinkman’s (2008) methodology. FFSA goals were found, as were themes of social impact (i.e., regarding coach-player relationships, trust, and coaching impact on social integration). A further theme related to evaluation components and procedures. Further themes included life skill development, competition within programming, participants’ home life and social integration. Findings contribute to the SDP literature relating to program evaluation research and to FFSA administrators by providing an understanding of SDP program shortcomings, limitations, and suggested improvements.

Network Similarity Measures and Automatic Construction of Graph Models using Genetic Programming

A complex network is an abstract representation of an intricate system of interrelated elements where the patterns of connection hold significant meaning. One particular complex network is a social network whereby the vertices represent people and edges denote their daily interactions. Understanding social network dynamics can be vital to the mitigation of disease spread as these networks model the interactions, and thus avenues of spread, between individuals. To better understand complex networks, algorithms which generate graphs exhibiting observed properties of real-world networks, known as graph models, are often constructed. While various efforts to aid with the construction of graph models have been proposed using statistical and probabilistic methods, genetic programming (GP) has only recently been considered. However, determining that a graph model of a complex network accurately describes the target network(s) is not a trivial task as the graph models are often stochastic in nature and the notion of similarity is dependent upon the expected behavior of the network. This thesis examines a number of well-known network properties to determine which measures best allowed networks generated by different graph models, and thus the models themselves, to be distinguished. A proposed meta-analysis procedure was used to demonstrate how these network measures interact when used together as classifiers to determine network, and thus model, (dis)similarity. The analytical results form the basis of the fitness evaluation for a GP system used to automatically construct graph models for complex networks. The GP-based automatic inference system was used to reproduce existing, well-known graph models as well as a real-world network. Results indicated that the automatically inferred models exemplified functional similarity when compared to their respective target networks. This approach also showed promise when used to infer a model for a mammalian brain network.

Inverse Illumination Design with Genetic Programming

Interior illumination is a complex problem involving numerous interacting factors. This research applies genetic programming towards problems in illumination design. The Radiance system is used for performing accurate illumination simulations. Radiance accounts for a number of important environmental factors, which we exploit during fitness evaluation. Illumination requirements include local illumination intensity from natural and artificial sources, colour, and uniformity. Evolved solutions incorporate design elements such as artificial lights, room materials, windows, and glass properties. A number of case studies are examined, including many-objective problems involving up to 7 illumination requirements, the design of a decorative wall of lights, and the creation of a stained-glass window for a large public space. Our results show the technical and creative possibilities of applying genetic programming to illumination design.