A INFLUÊNCIA DAS PRÁTICAS PEDAGÓGICAS DOCENTES E DAS BARREIRAS DISCENTES SOBRE O DESENVOLVIMENTO DA CRIATIVIDADE DO FUTURO ADMINISTRADOR

As empresas que almejam garantir e melhorar sua posição dentro de em um mercado cada vez mais competitivo precisam estar sempre atualizadas e em constante evolução. Na busca contínua por essa evolução, investem em projetos de Pesquisa & Desenvolvimento (P&D) e em seu capital humano para promover a criatividade e a inovação organizacional. As pessoas têm papel fundamental no desenvolvimento da inovação, mas para que isso possa florescer de forma constante é preciso comprometimento e criatividade para a geração de ideias. Criatividade é pensar o novo; inovação é fazer acontecer. Porém, encontrar pessoas com essas qualidades nem sempre é tarefa fácil e muitas vezes é preciso estimular essas habilidades e características para que se tornem efetivamente criativas. Os cursos de graduação podem ser uma importante ferramenta para trabalhar esses aspectos, características e habilidades, usando métodos e práticas de ensino que auxiliem no desenvolvimento da criatividade, pois o ambiente ensino-aprendizagem pesa significativamente na formação das pessoas. O objetivo deste estudo é de identificar quais fatores têm maior influência sobre o desenvolvimento da criatividade em um curso de graduação em administração, analisando a influência das práticas pedagógicas dos docentes e as barreiras internas dos discentes. O referencial teórico se baseia principalmente nos trabalhos de Alencar, Fleith, Torrance e Wechsler. A pesquisa transversal de abordagem quantitativa teve como público-alvo os alunos do curso de Administração de uma universidade confessional da Grande São Paulo, que responderam 465 questionários compostos de três escalas. Para as práticas docentes foi adaptada a escala de Práticas Docentes em relação à Criatividade. Para as barreiras internas foi adaptada a escala de Barreiras da Criatividade Pessoal. Para a análise da percepção do desenvolvimento da criatividade foi construída e validada uma escala baseada no referencial de características de uma pessoa criativa. As análises estatísticas descritivas e fatoriais exploratórias foram realizadas no software Statistical Package for the Social Sciences (SPSS), enquanto as análises fatoriais confirmatórias e a mensuração da influência das práticas pedagógicas e das barreiras internas sobre a percepção do desenvolvimento da criatividade foram realizadas por modelagem de equação estrutural utilizando o algoritmo Partial Least Squares (PLS), no software Smart PLS 2.0. Os resultados apontaram que as práticas pedagógicas e as barreiras internas dos discentes explicam 40% da percepção de desenvolvimento da criatividade, sendo as práticas pedagógicas que exercem maior influencia. A pesquisa também apontou que o tipo de temática e o período em que o aluno está cursando não têm influência sobre nenhum dos três construtos, somente o professor influencia as práticas pedagógicas.

ANALISANDO A RELAÇÃO DOS VOLUMES DE EXPORTAÇÃO E DE IMPORTAÇÃO, PIB, TAXAS DE CÂMBIO E INFLAÇÃO NO PERÍODO DE 2004 A 2014. SÃO BERNARDO DO CAMPO 2015

As empresas que almejam garantir e melhorar sua posição dentro de em um mercado cada vez mais competitivo precisam estar sempre atualizadas e em constante evolução. Na busca contínua por essa evolução, investem em projetos de Pesquisa & Desenvolvimento (P&D) e em seu capital humano para promover a criatividade e a inovação organizacional. As pessoas têm papel fundamental no desenvolvimento da inovação, mas para que isso possa florescer de forma constante é preciso comprometimento e criatividade para a geração de ideias. Criatividade é pensar o novo; inovação é fazer acontecer. Porém, encontrar pessoas com essas qualidades nem sempre é tarefa fácil e muitas vezes é preciso estimular essas habilidades e características para que se tornem efetivamente criativas. Os cursos de graduação podem ser uma importante ferramenta para trabalhar esses aspectos, características e habilidades, usando métodos e práticas de ensino que auxiliem no desenvolvimento da criatividade, pois o ambiente ensino-aprendizagem pesa significativamente na formação das pessoas. O objetivo deste estudo é de identificar quais fatores têm maior influência sobre o desenvolvimento da criatividade em um curso de graduação em administração, analisando a influência das práticas pedagógicas dos docentes e as barreiras internas dos discentes. O referencial teórico se baseia principalmente nos trabalhos de Alencar, Fleith, Torrance e Wechsler. A pesquisa transversal de abordagem quantitativa teve como público-alvo os alunos do curso de Administração de uma universidade confessional da Grande São Paulo, que responderam 465 questionários compostos de três escalas. Para as práticas docentes foi adaptada a escala de Práticas Docentes em relação à Criatividade. Para as barreiras internas foi adaptada a escala de Barreiras da Criatividade Pessoal. Para a análise da percepção do desenvolvimento da criatividade foi construída e validada uma escala baseada no referencial de características de uma pessoa criativa. As análises estatísticas descritivas e fatoriais exploratórias foram realizadas no software Statistical Package for the Social Sciences (SPSS), enquanto as análises fatoriais confirmatórias e a mensuração da influência das práticas pedagógicas e das barreiras internas sobre a percepção do desenvolvimento da criatividade foram realizadas por modelagem de equação estrutural utilizando o algoritmo Partial Least Squares (PLS), no software Smart PLS 2.0. Os resultados apontaram que as práticas pedagógicas e as barreiras internas dos discentes explicam 40% da percepção de desenvolvimento da criatividade, sendo as práticas pedagógicas que exercem maior influencia. A pesquisa também apontou que o tipo de temática e o período em que o aluno está cursando não têm influência sobre nenhum dos três construtos, somente o professor influencia as práticas pedagógicas.

An incremental tri-partite approach to ontology learning

In this paper we present a new approach to ontology learning. Its basis lies in a dynamic and iterative view of knowledge acquisition for ontologies. The Abraxas approach is founded on three resources, a set of texts, a set of learning patterns and a set of ontological triples, each of which must remain in equilibrium. As events occur which disturb this equilibrium various actions are triggered to re-establish a balance between the resources. Such events include acquisition of a further text from external resources such as the Web or the addition of ontological triples to the ontology. We develop the concept of a knowledge gap between the coverage of an ontology and the corpus of texts as a measure triggering actions. We present an overview of the algorithm and its functionalities.

Time trials on second-order and variable-learning-rate algorithms

The performance of seven minimization algorithms are compared on five neural network problems. These include a variable-step-size algorithm, conjugate gradient, and several methods with explicit analytic or numerical approximations to the Hessian.

Adaptive back-propagation in on-line learning of multilayer networks

An adaptive back-propagation algorithm is studied and compared with gradient descent (standard back-propagation) for on-line learning in two-layer neural networks with an arbitrary number of hidden units. Within a statistical mechanics framework, both numerical studies and a rigorous analysis show that the adaptive back-propagation method results in faster training by breaking the symmetry between hidden units more efficiently and by providing faster convergence to optimal generalization than gradient descent.

Using ancillary statistics in on-line learning algorithms

Neural networks are usually curved statistical models. They do not have finite dimensional sufficient statistics, so on-line learning on the model itself inevitably loses information. In this paper we propose a new scheme for training curved models, inspired by the ideas of ancillary statistics and adaptive critics. At each point estimate an auxiliary flat model (exponential family) is built to locally accommodate both the usual statistic (tangent to the model) and an ancillary statistic (normal to the model). The auxiliary model plays a role in determining credit assignment analogous to that played by an adaptive critic in solving temporal problems. The method is illustrated with the Cauchy model and the algorithm is proved to be asymptotically efficient.

GTM: A principled alternative to the self-organizing map

The Self-Organizing Map (SOM) algorithm has been extensively studied and has been applied with considerable success to a wide variety of problems. However, the algorithm is derived from heuristic ideas and this leads to a number of significant limitations. In this paper, we consider the problem of modelling the probability density of data in a space of several dimensions in terms of a smaller number of latent, or hidden, variables. We introduce a novel form of latent variable model, which we call the GTM algorithm (for Generative Topographic Mapping), which allows general non-linear transformations from latent space to data space, and which is trained using the EM (expectation-maximization) algorithm. Our approach overcomes the limitations of the SOM, while introducing no significant disadvantages. We demonstrate the performance of the GTM algorithm on simulated data from flow diagnostics for a multi-phase oil pipeline.

Magnification factors for the GTM algorithm

The Generative Topographic Mapping (GTM) algorithm of Bishop et al. (1997) has been introduced as a principled alternative to the Self-Organizing Map (SOM). As well as avoiding a number of deficiencies in the SOM, the GTM algorithm has the key property that the smoothness properties of the model are decoupled from the reference vectors, and are described by a continuous mapping from a lower-dimensional latent space into the data space. Magnification factors, which are approximated by the difference between code-book vectors in SOMs, can therefore be evaluated for the GTM model as continuous functions of the latent variables using the techniques of differential geometry. They play an important role in data visualization by highlighting the boundaries between data clusters, and are illustrated here for both a toy data set, and a problem involving the identification of crab species from morphological data.

Noisy fitness evaluation in genetic algorithms and the dynamics of learning

A theoretical model is presented which describes selection in a genetic algorithm (GA) under a stochastic fitness measure and correctly accounts for finite population effects. Although this model describes a number of selection schemes, we only consider Boltzmann selection in detail here as results for this form of selection are particularly transparent when fitness is corrupted by additive Gaussian noise. Finite population effects are shown to be of fundamental importance in this case, as the noise has no effect in the infinite population limit. In the limit of weak selection we show how the effects of any Gaussian noise can be removed by increasing the population size appropriately. The theory is tested on two closely related problems: the one-max problem corrupted by Gaussian noise and generalization in a perceptron with binary weights. The averaged dynamics can be accurately modelled for both problems using a formalism which describes the dynamics of the GA using methods from statistical mechanics. The second problem is a simple example of a learning problem and by considering this problem we show how the accurate characterization of noise in the fitness evaluation may be relevant in machine learning. The training error (negative fitness) is the number of misclassified training examples in a batch and can be considered as a noisy version of the generalization error if an independent batch is used for each evaluation. The noise is due to the finite batch size and in the limit of large problem size and weak selection we show how the effect of this noise can be removed by increasing the population size. This allows the optimal batch size to be determined, which minimizes computation time as well as the total number of training examples required.

On-line learning with adaptive back-propagation in two-layer networks

An adaptive back-propagation algorithm parameterized by an inverse temperature 1/T is studied and compared with gradient descent (standard back-propagation) for on-line learning in two-layer neural networks with an arbitrary number of hidden units. Within a statistical mechanics framework, we analyse these learning algorithms in both the symmetric and the convergence phase for finite learning rates in the case of uncorrelated teachers of similar but arbitrary length T. These analyses show that adaptive back-propagation results generally in faster training by breaking the symmetry between hidden units more efficiently and by providing faster convergence to optimal generalization than gradient descent.

Efficient Bayesian inference for learning in the Ising linear perceptron and signal detection in CDMA

Efficient new Bayesian inference technique is employed for studying critical properties of the Ising linear perceptron and for signal detection in code division multiple access (CDMA). The approach is based on a recently introduced message passing technique for densely connected systems. Here we study both critical and non-critical regimes. Results obtained in the non-critical regime give rise to a highly efficient signal detection algorithm in the context of CDMA; while in the critical regime one observes a first-order transition line that ends in a continuous phase transition point. Finite size effects are also studied. © 2006 Elsevier B.V. All rights reserved.

A Bayesian approach to on-line learning

Online learning is discussed from the viewpoint of Bayesian statistical inference. By replacing the true posterior distribution with a simpler parametric distribution, one can define an online algorithm by a repetition of two steps: An update of the approximate posterior, when a new example arrives, and an optimal projection into the parametric family. Choosing this family to be Gaussian, we show that the algorithm achieves asymptotic efficiency. An application to learning in single layer neural networks is given.

Inquiring how a lecturer keeps learning about their teaching:a personal case history on reflective imagination

In order to reverse the use of lecture-based teaching, it is argued that personal reflection can be used as part of the quality assurance process. This paper proposes one response to personal reflection - reflective imagination, which is summarised as an action plan with six activities. It combines two conceptual issues raised in the US, the need to think creatively about learning and the reflective mindset, and one issue raised in the UK, cultivating the entrepreneurial imagination. Reflective imagination is linked to wider social science research, the place of self and reflexivity in scholarship. Finally, a personal history case study is presented which records a visit to Harvard Business School. The visit implements the six activities associated with reflective imagination. This is a method paper exploring reflective imagination.

Comparing different approach and avoidance models of learning and personality in the prediction of work, university, and leadership outcomes

Jackson (2005) developed a hybrid model of personality and learning, known as the learning styles profiler (LSP) which was designed to span biological, socio-cognitive, and experiential research foci of personality and learning research. The hybrid model argues that functional and dysfunctional learning outcomes can be best understood in terms of how cognitions and experiences control, discipline, and re-express the biologically based scale of sensation-seeking. In two studies with part-time workers undertaking tertiary education (N=137 and 58), established models of approach and avoidance from each of the three different research foci were compared with Jackson's hybrid model in their predictiveness of leadership, work, and university outcomes using self-report and supervisor ratings. Results showed that the hybrid model was generally optimal and, as hypothesized, that goal orientation was a mediator of sensation-seeking on outcomes (work performance, university performance, leader behaviours, and counterproductive work behaviour). Our studies suggest that the hybrid model has considerable promise as a predictor of work and educational outcomes as well as dysfunctional outcomes.

Retail multinational learning:a case study of Tesco

Purpose - This article examines the internationalisation of Tesco and extracts the salient lessons learned from this process. Design/methodology/ approach - This research draws on a dataset of 62 in-depth interviews with key executives, sell- and buy-side analysts and corporate advisers at the leading investment banks in the City of London to detail the experiences of Tesco's European expansion. Findings - The case study of Tesco illuminates a number of different dimensions of the company's international experience. It offers some new insights into learning in international distribution environments such as the idea that learning is facilitated by uncertainty or "shocks" in the international retail marketplace; the size of the domestic market may inhibit change and so disable international learning; and learning is not necessarily facilitated by step-by-step incremental approaches to expansion. Research limitations/implications - The paper explores learning from a rather broad perspective, although it is hoped that these parameters can be used to raise a new set of more detailed priorities for future research on international retail learning. It is also recognised that the data gathered for this case study focus on Tesco's European operations. Practical implications - This paper raises a number of interesting issues such as whether the extremities of the business may be a more appropriate place for management to experiment and test new retail innovations, and the extent to which retailers take self-reflection seriously. Originality/value - The paper applies a new theoretical learning perspective to capture the variety of experiences during the internationalisation process, thus addressing a major gap in our understanding of the whole internationalisation process. © Emerald Group Publishing Limited.