Contribuição para um estudo sobre a utilização das metas de aprendizagem ; na escola e no trabalho dos professores

RESUMO:As Metas de Aprendizagem (MA) surgem em 2009 como o culminar de várias reformas curriculares, feitas avulsamente e com pouca articulação entre si. Sendo facultativas até 2013, este seria o momento ideal indagar se os professores de Educação Física as conhecem, o que pensam sobre elas, como as integram no seu planeamento individual / de grupo, o que se constitui como objectivo do estudo. Sendo um instrumento de Desenvolvimento Curricular multifacetado, apoiámo-nos numa Literatura que, para além de uma breve contextualização histórica, abordasse três áreas nucleares: as próprias Metas de Aprendizagem, o Planeamento e a Avaliação. Para concretizar os objectivos, foi testado e aplicado um questionário a 45 indivíduos, distribuído aleatoriamente, e cujas respostas foram sujeitas a tratamento estatístico. Não sendo uma amostra representativa, logo, impassível de extrapolação, obtiveram-se as seguintes conclusões: a maioria dos professores conhece e concorda com o documento; a maioria dos 33 indivíduos que conheciam as MA, revelou uma posição crítica muito positiva referindo como vantagens o apoio ao currículo e a uniformização do ensino, afirmou usar as MA no seu planeamento individual / grupo e manifestou-se unanimemente satisfeito com a sua aplicação. Os discordantes focam-se mais em questões de princípio do que na organização do documento.ABSTRACT: The Learning Methods (LM), arise in 2009 as the culmination of several curricular reforms, made piecemeal, with little coordination between them. Optional until 2013, this would be the ideal time to investigate whether the physical education teachers know them, what they think about them, as part of their planning in individual / group, which is the objective of the study. Being a multi-faceted tool for Curriculum Development, we support a literature that, apart from a brief historical background, addresses three core areas: their own Learning Methods, planning and evaluation. To achieve the objectives, it was tested and applied a questionnaire to 45 randomly selected individuals, and the answers were subjected to statistical analysis. Not being a representative sample, so impassive extrapolation, we obtained the following conclusions: most teachers know and agree with the document; most of the 33 individuals who knew the LM revealed a critical position as a very positive advantages referring to the curriculum and support standardization of education, said to use the LM in their planning individual / group and is unanimously expressed satisfaction with their application. The discordant focus more on issues of principle than in the organization of the document.

Incorporating creativity into teachers practice and self-concept of professional identity

The study explores what happens to teachers practice and ’ professional identity when they adopt a collaborative action research approach to teaching and involve external creative partners and a university mentor. The teachers aim to nurture and develop the creative potential of their learners through empowering them to make decisions for themselves about their own progress and learning directions. The teachers worked creatively and collaboratively designing creative teaching and learning methods in support of pupils with language and communication difficulties. The respondents are from an English special school, primary school and girls secondary school. A mixed methods methodology is adopted. Gains in teacher confidence and capability were identified in addition to shifts in values that impacted directly on their self-concept of what it is to be an effective teacher promoting effective learning. The development of their professional identities within a team ethos included them being able to make decisions about learning that are based on the educational potential of learners that they proved resulted in elevated standards achieved by this group of learners. They were able to justify their actions on established educational principles. Tensions however were revealed between what they perceived as their normal required professionalism imposed by external agencies and the enhanced professionalism experienced working through the project where they were able to integrate theory and practice.

Parallel random prism: a computationally efficient ensemble learner for classification

Generally classifiers tend to overfit if there is noise in the training data or there are missing values. Ensemble learning methods are often used to improve a classifier's classification accuracy. Most ensemble learning approaches aim to improve the classification accuracy of decision trees. However, alternative classifiers to decision trees exist. The recently developed Random Prism ensemble learner for classification aims to improve an alternative classification rule induction approach, the Prism family of algorithms, which addresses some of the limitations of decision trees. However, Random Prism suffers like any ensemble learner from a high computational overhead due to replication of the data and the induction of multiple base classifiers. Hence even modest sized datasets may impose a computational challenge to ensemble learners such as Random Prism. Parallelism is often used to scale up algorithms to deal with large datasets. This paper investigates parallelisation for Random Prism, implements a prototype and evaluates it empirically using a Hadoop computing cluster.

Semantic mapping using mobile robots

Robotic mapping is the process of automatically constructing an environment representation using mobile robots. We address the problem of semantic mapping, which consists of using mobile robots to create maps that represent not only metric occupancy but also other properties of the environment. Specifically, we develop techniques to build maps that represent activity and navigability of the environment. Our approach to semantic mapping is to combine machine learning techniques with standard mapping algorithms. Supervised learning methods are used to automatically associate properties of space to the desired classification patterns. We present two methods, the first based on hidden Markov models and the second on support vector machines. Both approaches have been tested and experimentally validated in two problem domains: terrain mapping and activity-based mapping.

Using metrics from complex networks to evaluate machine translation

Establishing metrics to assess machine translation (MT) systems automatically is now crucial owing to the widespread use of MT over the web. In this study we show that such evaluation can be done by modeling text as complex networks. Specifically, we extend our previous work by employing additional metrics of complex networks, whose results were used as input for machine learning methods and allowed MT texts of distinct qualities to be distinguished. Also shown is that the node-to-node mapping between source and target texts (English-Portuguese and Spanish-Portuguese pairs) can be improved by adding further hierarchical levels for the metrics out-degree, in-degree, hierarchical common degree, cluster coefficient, inter-ring degree, intra-ring degree and convergence ratio. The results presented here amount to a proof-of-principle that the possible capturing of a wider context with the hierarchical levels may be combined with machine learning methods to yield an approach for assessing the quality of MT systems. (C) 2010 Elsevier B.V. All rights reserved.

Automatic spiral analysis for objective assessment of motor symptoms in Parkinson's disease

A challenge for the clinical management of advanced Parkinson’s disease (PD) patients is the emergence of fluctuations in motor performance, which represents a significant source of disability during activities of daily living of the patients. There is a lack of objective measurement of treatment effects for in-clinic and at-home use that can provide an overview of the treatment response. The objective of this paper was to develop a method for objective quantification of advanced PD motor symptoms related to off episodes and peak dose dyskinesia, using spiral data gathered by a touch screen telemetry device. More specifically, the aim was to objectively characterize motor symptoms (bradykinesia and dyskinesia), to help in automating the process of visual interpretation of movement anomalies in spirals as rated by movement disorder specialists. Digitized upper limb movement data of 65 advanced PD patients and 10 healthy (HE) subjects were recorded as they performed spiral drawing tasks on a touch screen device in their home environment settings. Several spatiotemporal features were extracted from the time series and used as inputs to machine learning methods. The methods were validated against ratings on animated spirals scored by four movement disorder specialists who visually assessed a set of kinematic features and the motor symptom. The ability of the method to discriminate between PD patients and HE subjects and the test-retest reliability of the computed scores were also evaluated. Computed scores correlated well with mean visual ratings of individual kinematic features. The best performing classifier (Multilayer Perceptron) classified the motor symptom (bradykinesia or dyskinesia) with an accuracy of 84% and area under the receiver operating characteristics curve of 0.86 in relation to visual classifications of the raters. In addition, the method provided high discriminating power when distinguishing between PD patients and HE subjects as well as had good test-retest reliability. This study demonstrated the potential of using digital spiral analysis for objective quantification of PD-specific and/or treatment-induced motor symptoms.

Recursos da tecnologia da informatica no ensino / aprendizagem : a visao dos professores das escolas estaduais de ensino medio de Porto Alegre

Frente às transformações advindas do impacto das tecnologias na sociedade e nas organizações, bem como as novas habilidades e competências a serem adquiridas pelos profissionais no disputado mercado de trabalho atual, faz-se relevante atualizar os processos de ensino/aprendizagem, de forma a qualificar a formação profissional do egresso de ensino médio. O presente estudo tem por objetivo analisar a visão dos professores sobre as implicações da introdução dos recursos de informática nas organizações estaduais de ensino médio de Porto Alegre. Sua investigação tem como dimensão predominante uma abordagem quantitativa, de caráter exploratório sobre as percepções dos professores. Uma segunda dimensão - contextual - identifica as principais políticas educacionais para a área de informática no ensino médio. A dimensão do professor tem, por sua vez, duas subdimensões: o papel do professor frente ao processo de ensino-aprendizagem e suas percepções quanto à introdução dos recursos da tecnologia da informática no ensino médio. A base empírica desta dimensão adveio de dez escolas, selecionadas através de amostragem por cotas, tendo como instrumento de coleta de dados um questionário. Na dimensão contextual, foram realizadas pesquisa documental e entrevistas junto aos ór gãos oficiais responsáveis pelas políticas de informática educacional e direções de escolas e professores. Os resultados mostram que os professores do ensino médio das escolas estaduais de Porto Alegre concordam e percebem como prioritária a introdução dos recursos da tecnologia da informática nas escolas e que, para usufruir adequadamente destes recursos, os docentes devem assumir uma nova postura frente aos métodos de ensino-aprendizagem. Esta postura vem permitir e incentivar que o discente seja o sujeito do processo de construção do seu conhecimento. Esta pesquisa também identificou diretrizes para a formação de professores subsidiando, assim, políticas públicas para a área de educação no Estado.

A modelagem matemática como alternativa de ensino e aprendizagem da geometria na educação de jovens e adultos

This is work itself insert in the mathematics education field of the youth and adult education to aim to practitioners of the educational action into the mathematics area performing to with this is teaching kind, adopting to as parameter the Mathematics Molding approach. The motive of the research is to draw up a application proposal of the molding mathematics as teaching and learning geometry alternative in the youth and adult education. The research it develops in three class of the third level (series 5th and 6th) of he youth and adults education in the one school municipal from the Natal outskirts. Its have qualitative nature with participating observation approach, once performing to directly in to research environment as a mathematics teacher of those same classes. We are used questionnaires, lesson notes and analyses of the officials documents as an basis of claim instruments. The results indicates that activity used the mathematic moldings were appreciated the savoir-faire of the student in to knowledge construction process, when search develop to significant learning methods, helping to student build has mathematics connections with other knowledge areas and inside mathematics himself, so much that enlarges your understanding and assist has in your participation in the other socials place, over there propitiate to change in student and teacher posture with relation to mathematic classroom dynamics

Uso de confiabilidade na rotulação de exemplos em problemas de classificação multirrótulo com aprendizado semissupervisionado

The techniques of Machine Learning are applied in classification tasks to acquire knowledge through a set of data or information. Some learning methods proposed in literature are methods based on semissupervised learning; this is represented by small percentage of labeled data (supervised learning) combined with a quantity of label and non-labeled examples (unsupervised learning) during the training phase, which reduces, therefore, the need for a large quantity of labeled instances when only small dataset of labeled instances is available for training. A commom problem in semi-supervised learning is as random selection of instances, since most of paper use a random selection technique which can cause a negative impact. Much of machine learning methods treat single-label problems, in other words, problems where a given set of data are associated with a single class; however, through the requirement existent to classify data in a lot of domain, or more than one class, this classification as called multi-label classification. This work presents an experimental analysis of the results obtained using semissupervised learning in troubles of multi-label classification using reliability parameter as an aid in the classification data. Thus, the use of techniques of semissupervised learning and besides methods of multi-label classification, were essential to show the results

Concepções de qualidade de ensino dos coordenadores de graduação: uma análise dos cursos de odontologia do Estado de São Paulo

As novas demandas sociais e as diretrizes curriculares brasileiras para os cursos de odontologia colocam desafios à prática docente nas instituições de educação superior. Nesse contexto, investigam-se as concepções de qualidade de ensino universitário de professores que atuam como coordenadores de graduação nas faculdades de odontologia do Estado de São Paulo que possuem pós-graduação stricto-sensu, para refletir sobre os desafios da formação docente na área. Como instrumentos de levantamento de dados utilizou-se questionário, contendo perguntas abertas e fechadas e entrevista semi-estruturada, organizada para possibilitar o aprofundamento da discussão. Os dados foram descritos e discutidos mediante análise quantitativa e qualitativa, a partir das três dimensões da prática docente analisadas por Cunha (1995): político-estrutural, curricular e pedagógica. Para este artigo, focalizaram-se apenas os aspectos da dimensão pedagógica, na qual os pontos que expressam posturas mais contraditórias referem-se a métodos de ensino-aprendizagem, participação do aluno e tutoria. Os resultados apontam para concepções de ensino-aprendizagem que oscilam entre modelos tradicionais e inovadores, sinalizando pontos de conflito em relação a paradigmas que se articulam diretamente a questões curriculares e político-estruturais.

Evaluación de las metodologías de enseñanza-aprendizaje de la bioética en las facultades de odontología Brasileñas

Introduction. Bioethics is present in Dentistry and other health areas, as scientific research that results on profession progress, as in proper clinical attendance. The study consists on valuation of teaching-learning methods of Bioethical on Brazilian Dental Schools. Materials and methods. Data collect occurred by semi-structured questioners send by e-mail and correspondence. It was realized descriptive analysis of quantitative answers, and for qualitative answers, it was used content analysis, by categorical analysis technique in according to Bardin. Results. Among 182 Dental Schools actives in Brazil, only 57 (31.3%) showed bioethical discipline in its curricular grid. It was observed the discipline is teaching on theoretical form (77.8%). Principal forms of evaluation are: writing prove (100%) and seminaries (75%). Just 6.4% of professors use bibliographic references about bioethical faced to Odontology specifically. The majority of interviewed person (74.2%) considered that bioethics is related on the direct and indirect form with all others disciplines. In relation to importance of Bioethical on dental surgeon formation, 64.7% emphasized it in professional-patient relation. Conclusion. The Bioethics show teaching and practice method of conserver evaluation, and so, it's necessary others methods directed to reflection of actual problems in odontology area that contribute significantly on integral formation of dental surgeon. © Viguera Editores SL 2009.

OPF-MRF: Optimum-path forest and Markov random fields for contextual-based image classification

Some machine learning methods do not exploit contextual information in the process of discovering, describing and recognizing patterns. However, spatial/temporal neighboring samples are likely to have same behavior. Here, we propose an approach which unifies a supervised learning algorithm - namely Optimum-Path Forest - together with a Markov Random Field in order to build a prior model holding a spatial smoothness assumption, which takes into account the contextual information for classification purposes. We show its robustness for brain tissue classification over some images of the well-known dataset IBSR. © 2013 Springer-Verlag.

Leitura de O boy da via láctea de Regina Chamlian: por uma 8ª série do Ensino Fundamental

Pós-graduação em Educação - FFC

Elaboração e avaliação de um ambiente virtual para o ensino/aprendizagem de embriologia

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)