Physical Education in Colorado: Status And Stakeholders’ Perceptions

This dissertation includes two studies, aiming to explore the status of physical education and stakeholders’ perceptions of physical education in Colorado. In study one, using the PE for All Colorado model policy as a guiding framework, the purpose of this study was to explore the status of physical education in Colorado. Research questions included: (a) what is the status of physical education in Colorado based on the PE for All model policy’s recommendations? and (b) what are the facilitators and barriers to implementing physical education in schools? A sequential explanatory mixed method design was utilized in this study consisting of two phases: the administration of a survey (Phase 1); and a semi-structured interview (Phase 2; Creswell, 2009). Participants in this study were 201 physical education teachers (n = 98 elementary schools, n = 95 secondary schools, and n = 8 K-12 schools) from urban (n = 122), suburban (n = 54), and rural (n = 25) areas in Phase 1, and 12 teachers (n = 5 female and n = 7 male) in Phase 2. The quantitative survey data were analyzed using descriptive statistics through SPSS. Qualitative survey data (i.e., the open-ended responses) and teachers’ responses to interview questions were analyzed with open and axial coding approach, and ultimately, the survey and interview data were combined to interpret the status of physical education. Results are presented in two sections: the status of physical education and the facilitators and barriers to its implementation. Most physical education programs met the recommendations for most components: assessment (90.0%), school funding (71.1%), etc. Some programs only partially met the following components: district funding (57.2%), waivers for physical education (Level 1), etc. Six facilitators and seven barriers related to the implementation of physical education at schools were identified. Facilitators include: requirements for physical education, adequate facilities and equipment in secondary schools, administrator support, parent support, access to community resources, and professional development for physical education teachers. Barriers include: negative perceptions of physical education, marginalization of physical education, limited instruction time in elementary, large class sizes in secondary, lack of attention to policy, limited funding, and lack of a rubric for teacher evaluation. In conclusion, Colorado is a local-control state, so physical education programs in Colorado schools vary widely. The findings of this study have the potential to act as a reference or guidepost for efforts to improve physical education in Colorado, creating a baseline from which to work. The state, schools, and physical education teachers should consider the PE for All model policy when implementing physical education and should advocate for a quality program. Study two was to explore the perceptions of students, parents, classroom teachers, and administrators on physical education at school. The social ecological model served as the theoretical framework for this study, incorporating environmental considerations for the development of physical education within schools (Bronfenbrenner, 1992). This study employed an interpretive qualitative research design to explore stakeholders’ perceptions on “typical” physical education which focused on what physical education was like prior to the global pandemic that started in March 2020 (Merriam & Tisdell, 2016). Participants (N = 28) in this study included students (n = 8), parents (n = 8), classroom teachers (n = 9), principals (n = 2) and one assistant principal. Data sources included interviews (i.e., focus group interviews or individual interviews) and artifacts consisting of physical education documents (i.e., class schedule, curriculum documents, syllabi, budget plan, etc.), policy documents (e.g., district policy in physical education), the PE for All Colorado physical education model policy (Colorado Health Foundation, 2016), and the Colorado state profile of physical education (SHAPE America, 2016). To understand each group of stakeholders’ insights on physical education, the researcher employed open and axial coding to analyze the interview data by groups and used document analysis for artifacts. The results of this study are presented based on the perceptions of four groups of stakeholders--students, parents, classroom teachers, and administrators--on physical education at their/their children’s school. Their perceptions included four categories: the purpose of physical education, the impact of physical education on children, the learning environment, and suggestions to improve physical education. Understanding stakeholders’ insights has the potential to improve the implementation of physical education when schools and physical education teachers are designing physical education programs. Overall, this dissertation provides the current state of physical education and stakeholders’ insights of physical education in Colorado. The results of the studies provide a baseline to assist policy makers in building feasible legislation to implement physical education, have the potential to find creative ways to tackle the challenges of implementing and improving physical education, and offer pedagogical and curriculum implications that schools and physical education teachers can take into consideration stakeholders’ perceptions of physical education

Distributed D3: A web-based distributed data visualisation framework for Big Data

The influx of Big Data has created an ever-growing need for analytic tools targeting towards the acquisition of insights and knowledge from large datasets. Visual perception as a fundamental tool used by humans to retrieve information from the outside world around us has its unique ability to distinguish patterns pre-attentively. Visual analytics via data visualisations is therefore a very powerful tool and has become ever more important in this era. Data-Driven Documents (D3.js) is a versatile and popular web-based data visualisation library that has tended to be the standard toolkit for visualising data in recent years. However, the library is technically inherent and limited in capability by the single thread model of a single browser window in a single machine, and therefore not able to deal with large datasets. The main objective of this thesis is to overcome this limitation and address possible challenges by developing the Distributed D3 framework that employs distributed mechanism to enable the possibility of delivering web-based visualisations for large-scale data, which also allows to effectively utilise the graphical computational resources of the modern visualisation environments. As a result, the first contribution is that the integrated version of Distributed D3 framework has been developed for the Data Observatory. The work proves the concept of Distributed D3 is feasible in reality and also enables developers to collaborate on large-scale data visualisations by using it on the Data Observatory. The second contribution is that the Distributed D3 has been optimised by investigating the potential bottlenecks for large-scale data visualisation applications. The work finds the key performance bottlenecks of the framework and shows an improvement of the overall performance by 35.7% after optimisations, which improves the scalability and usability of Distributed D3 for large-scale data visualisation applications. The third contribution is that the generic version of Distributed D3 framework has been developed for the customised environments. The work improves the usability and flexibility of the framework and makes it ready to be published in the open-source community for further improvements and usages.Open Acces

A data-driven game theoretic strategy for developers in software crowdsourcing: a case study

Crowdsourcing has the advantages of being cost-effective and saving time, which is a typical embodiment of collective wisdom and community workers’ collaborative development. However, this development paradigm of software crowdsourcing has not been used widely. A very important reason is that requesters have limited knowledge about crowd workers’ professional skills and qualities. Another reason is that the crowd workers in the competition cannot get the appropriate reward, which affects their motivation. To solve this problem, this paper proposes a method of maximizing reward based on the crowdsourcing ability of workers, they can choose tasks according to their own abilities to obtain appropriate bonuses. Our method includes two steps: Firstly, it puts forward a method to evaluate the crowd workers’ ability, then it analyzes the intensity of competition for tasks at Topcoder.com—an open community crowdsourcing platform—on the basis of the workers’ crowdsourcing ability; secondly, it follows dynamic programming ideas and builds game models under complete information in different cases, offering a strategy of reward maximization for workers by solving a mixed-strategy Nash equilibrium. This paper employs crowdsourcing data from Topcoder.com to carry out experiments. The experimental results show that the distribution of workers’ crowdsourcing ability is uneven, and to some extent it can show the activity degree of crowdsourcing tasks. Meanwhile, according to the strategy of reward maximization, a crowd worker can get the theoretically maximum reward

Topic-based integrator matching for pull request

Pull Request (PR) is the main method for code contributions from the external contributors in GitHub. PR review is an essential part of open source software developments to maintain the quality of software. Matching a new PR for an appropriate integrator will make the PR reviewing more effective. However, PR and integrator matching are now organized manually in GitHub. To make this process more efficient, we propose a Topic-based Integrator Matching Algorithm (TIMA) to predict highly relevant collaborators(the core developers) as the integrator to incoming PRs . TIMA takes full advantage of the textual semantics of PRs. To define the relationships between topics and collaborators, TIMA builds a relation matrix about topic and collaborators. According to the relevance between topics and collaborators, TIMA matches the suitable collaborators as the PR integrator

An oil painters recognition method based on cluster multiple kernel learning algorithm

A lot of image processing research works focus on natural images, such as in classification, clustering, and the research on the recognition of artworks (such as oil paintings), from feature extraction to classifier design, is relatively few. This paper focuses on oil painter recognition and tries to find the mobile application to recognize the painter. This paper proposes a cluster multiple kernel learning algorithm, which extracts oil painting features from three aspects: color, texture, and spatial layout, and generates multiple candidate kernels with different kernel functions. With the results of clustering numerous candidate kernels, we selected the sub-kernels with better classification performance, and use the traditional multiple kernel learning algorithm to carry out the multi-feature fusion classification. The algorithm achieves a better result on the Painting91 than using traditional multiple kernel learning directly

Shaking Table Tests of Seismic Pile-Soil-Pier Structure Interaction

The limited strong earthquake database on structure and pile performance obstructs obtaining further progress in soil-pile structure interaction problem. Model test in laboratory is one of the best ways to expand the database of structure and pile performance during earthquake. In this paper, the problem of pile-soil-pier-structure interaction is investigated by shake table test approach, and on the development of the sandy box for SPSSI test is firstly introduced. Through free field test, the validation of the model container was evaluated by comparisons of soil acceleration records with those numerically calculated by SHAKE91. Secondly, four specimen to simulate friction pile response were employed: single column pile pier, one column pier model with 2x2 piles, two-column piers model with 2x2 piles and two-column piers model with 3x2 piles. The characteristic behaviors of single pier and two piers were comparatively experimented and analyzed under the same condition of pile groups and input motion