6 resultados para Multiple methods framework

em Digital Commons at Florida International University


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The school curriculum is a matter mandated by the educational system rather than determined by the school stakeholders of a community, as Freire (1993) suggests. At the present time, one significant vision of school is challenging the current order of curriculum practice. It focuses on school as a liberating agency grounded on the belief that the abilities to access information and to think critically about it will educate an individual capable of making independent decisions. This dissertation investigates teacher's beliefs concerning curriculum. It was assumed that there is a discrepancy between what has been the position proposed by critical theorists including Freire (1998a, 1993); Apple (1979); Giroux (1998), and the position on curriculum which school systems are typically advancing. ^ There were four purposes of this study. The major purpose of this study was to determine whether or not Brazilian and American Teachers believe that a school curriculum based on Freirean principles could be implemented in the schools in which they worked. Also, this study sought to determine the differences found between teachers' beliefs in the Brazilian and American contexts. Another purpose was to determine how Brazilian and American teachers justify their beliefs and actions when these may represent conflicting values. Finally, this study sought to determine if these teachers believe that the curriculum is in need of change or if they accept the current curriculum as adequate. This study consisted of quantitative and qualitative data collection through multiple methods involving surveys and interviews. The study involved 171 teachers (88 Brazilian and 83 American) from multiple settings with the majority working for public systems. Overall, it seems that Brazilian and American teachers believe that a curriculum based on Freirean principles of education can be implemented in their schools, if ongoing education is provided. The majority of Brazilian teachers believe a curriculum change is necessary while half of the American teachers believe a curriculum change is needed and the other half seems to believe curriculum is adequate. Teachers explain that it is hard to implement a curriculum they believe to be most appropriate for students because the current curriculum is mandated by the school system or by national guidelines. The majority of Brazilian teachers and those American teachers who believed a curriculum change is necessary explained their rationale for change in terms of social justice, problem-solving, collective work, student-centered and context-based curriculum. American teachers, who believed that the curriculum is adequate, explained that they are satisfied with their student's achievements. They stated that their students are doing well on tests and are learning what is required. ^

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To stay competitive, many employers are looking for creative and innovative employees to add value to their organization. However, current models of job performance overlook creative performance as an important criterion to measure in the workplace. The purpose of this dissertation is to conduct two separate but related studies on creative performance that aim to provide support that creative performance should be included in models of job performance, and ultimately included in performance evaluations in organizations. Study 1 is a meta-analysis on the relationship between creative performance and task performance, and the relationship between creative performance and organizational citizenship behavior (OCB). Overall, I found support for a medium to large corrected correlation for both the creative performance-task performance (ρ = .51) and creative performance-OCB (ρ = .49) relationships. Further, I also found that both rating-source and study location were significant moderators. Study 2 is a process model that includes creative performance alongside task performance and OCB as the outcome variables. I test a model in which both individual differences (specifically: conscientiousness, extraversion, proactive personality, and self-efficacy) and job characteristics (autonomy, feedback, and supervisor support) predict creative performance, task performance, and OCB through engagement as a mediator. In a sample of 299 employed individuals, I found that all the individual differences and job characteristics were positively correlated with all three performance criteria. I also looked at these relationships in a multiple regression framework and most of the individual differences and job characteristics still predicted the performance criteria. In the mediation analyses, I found support for engagement as a significant mediator of the individual differences-performance and job characteristics-performance relationships. Taken together, Study 1 and Study 2 support the notion that creative performance should be included in models of job performance. Implications for both researchers and practitioners alike are discussed.

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To stay competitive, many employers are looking for creative and innovative employees to add value to their organization. However, current models of job performance overlook creative performance as an important criterion to measure in the workplace. The purpose of this dissertation is to conduct two separate but related studies on creative performance that aim to provide support that creative performance should be included in models of job performance, and ultimately included in performance evaluations in organizations. Study 1 is a meta-analysis on the relationship between creative performance and task performance, and the relationship between creative performance and organizational citizenship behavior (OCB). Overall, I found support for a medium to large corrected correlation for both the creative performance-task performance (ρ = .51) and creative performance-OCB (ρ = .49) relationships. Further, I also found that both rating-source and study location were significant moderators. Study 2 is a process model that includes creative performance alongside task performance and OCB as the outcome variables. I test a model in which both individual differences (specifically: conscientiousness, extraversion, proactive personality, and self-efficacy) and job characteristics (autonomy, feedback, and supervisor support) predict creative performance, task performance, and OCB through engagement as a mediator. In a sample of 299 employed individuals, I found that all the individual differences and job characteristics were positively correlated with all three performance criteria. I also looked at these relationships in a multiple regression framework and most of the individual differences and job characteristics still predicted the performance criteria. In the mediation analyses, I found support for engagement as a significant mediator of the individual differences-performance and job characteristics-performance relationships. Taken together, Study 1 and Study 2 support the notion that creative performance should be included in models of job performance. Implications for both researchers and practitioners alike are discussed.^

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The main challenges of multimedia data retrieval lie in the effective mapping between low-level features and high-level concepts, and in the individual users' subjective perceptions of multimedia content. ^ The objectives of this dissertation are to develop an integrated multimedia indexing and retrieval framework with the aim to bridge the gap between semantic concepts and low-level features. To achieve this goal, a set of core techniques have been developed, including image segmentation, content-based image retrieval, object tracking, video indexing, and video event detection. These core techniques are integrated in a systematic way to enable the semantic search for images/videos, and can be tailored to solve the problems in other multimedia related domains. In image retrieval, two new methods of bridging the semantic gap are proposed: (1) for general content-based image retrieval, a stochastic mechanism is utilized to enable the long-term learning of high-level concepts from a set of training data, such as user access frequencies and access patterns of images. (2) In addition to whole-image retrieval, a novel multiple instance learning framework is proposed for object-based image retrieval, by which a user is allowed to more effectively search for images that contain multiple objects of interest. An enhanced image segmentation algorithm is developed to extract the object information from images. This segmentation algorithm is further used in video indexing and retrieval, by which a robust video shot/scene segmentation method is developed based on low-level visual feature comparison, object tracking, and audio analysis. Based on shot boundaries, a novel data mining framework is further proposed to detect events in soccer videos, while fully utilizing the multi-modality features and object information obtained through video shot/scene detection. ^ Another contribution of this dissertation is the potential of the above techniques to be tailored and applied to other multimedia applications. This is demonstrated by their utilization in traffic video surveillance applications. The enhanced image segmentation algorithm, coupled with an adaptive background learning algorithm, improves the performance of vehicle identification. A sophisticated object tracking algorithm is proposed to track individual vehicles, while the spatial and temporal relationships of vehicle objects are modeled by an abstract semantic model. ^

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The primary aim of this dissertation is to develop data mining tools for knowledge discovery in biomedical data when multiple (homogeneous or heterogeneous) sources of data are available. The central hypothesis is that, when information from multiple sources of data are used appropriately and effectively, knowledge discovery can be better achieved than what is possible from only a single source. ^ Recent advances in high-throughput technology have enabled biomedical researchers to generate large volumes of diverse types of data on a genome-wide scale. These data include DNA sequences, gene expression measurements, and much more; they provide the motivation for building analysis tools to elucidate the modular organization of the cell. The challenges include efficiently and accurately extracting information from the multiple data sources; representing the information effectively, developing analytical tools, and interpreting the results in the context of the domain. ^ The first part considers the application of feature-level integration to design classifiers that discriminate between soil types. The machine learning tools, SVM and KNN, were used to successfully distinguish between several soil samples. ^ The second part considers clustering using multiple heterogeneous data sources. The resulting Multi-Source Clustering (MSC) algorithm was shown to have a better performance than clustering methods that use only a single data source or a simple feature-level integration of heterogeneous data sources. ^ The third part proposes a new approach to effectively incorporate incomplete data into clustering analysis. Adapted from K-means algorithm, the Generalized Constrained Clustering (GCC) algorithm makes use of incomplete data in the form of constraints to perform exploratory analysis. Novel approaches for extracting constraints were proposed. For sufficiently large constraint sets, the GCC algorithm outperformed the MSC algorithm. ^ The last part considers the problem of providing a theme-specific environment for mining multi-source biomedical data. The database called PlasmoTFBM, focusing on gene regulation of Plasmodium falciparum, contains diverse information and has a simple interface to allow biologists to explore the data. It provided a framework for comparing different analytical tools for predicting regulatory elements and for designing useful data mining tools. ^ The conclusion is that the experiments reported in this dissertation strongly support the central hypothesis.^

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Along with the accumulation of evidence supporting the role of entrepreneurship in economic development (Acs & Armington, 2006; Kuratko, 2005, Reynolds, 2007), governments have persisted in encouraging people to become entrepreneurs (Acs & Stough, 2008; Brannback & Carsrud, 2008). These efforts have tried to reproduce the conditions under which entrepreneurship emerges. One of these conditions is to develop entrepreneurial skills among students and scientists (Fan & Foo, 2004). Entrepreneurship education within higher education has experienced a remarkable expansion in the last 20 years (Green, 2008). To develop entrepreneurial skills among students, scholars have proposed different teaching approaches. However, no clear relationship has been demonstrated between entrepreneurship education, learning outcomes, and business creation (Hostager & Decker, 1999). Despite policy makers demands for more accountability from educational institutions (Klimoski, 2007) and entrepreneurship instructors demands for consistency about what should be taught and how (Maidment, 2009), the appropriate content for entrepreneurship programs remains under constant discussion (Solomon, 2007). Entrepreneurship education is still in its infancy, professors propose diverse teaching goals and radically different teaching methods. This represents an obstacle to development of foundational and consistent curricula across the board (Cone, 2008). Entrepreneurship education is in need of a better conceptualization of the learning outcomes pursued in order to develop consistent curriculum. Many schools do not have enough qualified faculty to meet the growing student demand and a consistent curriculum is needed for faculty development. Entrepreneurship instructors and their teaching practices are of interest because they have a role in producing the entrepreneurs needed to grow the economy. This study was designed to understand instructors’ perspectives and actions related to their teaching. The sample studied consisted of eight college and university entrepreneurship instructors. Cases met predetermined criteria of importance followed maximum variation strategies. Results suggest that teaching content were consistent across participants while different teaching goals were identified: some instructors inspire and develop general skills of students while others envision the creation of a real business as the major outcome of their course. A relationship between methods reported by instructors and their disciplinary background, teaching perspective, and entrepreneurial experience was found.