UM ESTUDO DA APLICAÇÃO DO MODELO DE ACEITAÇÃO DE TECNOLOGIAS NA EDUCAÇÃO SUPERIOR COM FOCO NOS AMBIENTES VIRTUAIS DE APRENDIZAGEM

Resumo Este trabalho oferece uma análise sobre estudos que focam a aceitação de tecnologias digitais no contexto do Ensino Superior. São abordados os fatores que favorecem a aceitação de tais tecnologias por parte de estudantes e docentes, com foco nos ambientes virtuais de aprendizagem (AVAs). Foram consultados oito estudos sobre o tema, realizados em contextos educacionais de diferentes culturas ao redor do mundo. Adicionalmente, revisamos uma meta-análise que mapeou outros quarenta e dois estudos sobre aceitação de tecnologias diversas na Educação. Após a descrição e discussão das pesquisas, é apresentado um quadro que elenca os principais fatores relacionados à aceitação de AVAs no Ensino Superior, segundo sua influência direta ou indireta no processo de apropriação. Foi identificado que a percepção em relação à praticidade, facilidade de uso e a atitude positiva despertada por um AVA são os principais fatores que favorecem sua aceitação. Neste artigo é apresentado o Technology Acceptance Model, modelo teórico preferencial para esse tipo de estudo; os resultados dessa pesquisa, com suas implicações e possibilidades futuras de investigações nesse campo, também são discutidos.Palavras-chave: Educação a Distância. Aceitação da tecnologia. Ambiente virtual de aprendizagem. Mídias

Abordagens e Teorias de Aprendizagem Propostos pelos Projetos dos Cursos de Pedagogia a Distância para o Desenvolvimento de Tecnologias Educacionais

O presente trabalho traz os resultados de uma pesquisa que procurou identificar de quais abordagens e teorias de aprendizagem provêm os princípios didático-pedagógicos que os Projetos Pedagógicos de Curso (PPCs) dos cursos de Pedagogia a distância oferecidos por universidades federais da Região Nordeste propõem para o planejamento e desenvolvimento de suas tecnologias educacionais (ambientes, materiais e atividades). Após a revisão de literatura sobre abordagens e teorias de aprendizagem, seguida das análises documental e de conteúdo dos PPCs, identificamos que preponderam princípios escolanovistas, construtivistas e socioconstrutivistas. Contudo: a) a forma de operacionalização de tais princípios no planejamento e desenvolvimento dos ambientes, materiais e atividades é pouco objetiva; e b) os processos de avaliação da aprendizagem (e instrumentos utilizados) não são descritos ou o são de forma imprecisa. Tais achados sugerem que os PPCs, documentação balizadora dos cursos, não são utilizados como referência para o planejamento e o desenvolvimento das tecnologias educacionais empregadas nos cursos investigados. Palavras-chave: Educação a distância, Pedagogia, Teorias de aprendizagem, Tecnologias educacionais, Projeto pedagógico de curso. Approaches and Theories of Learning Proposed by the Projects of Pedagogy Distance Education Course for the Development of Educational TechnologiesAbstractThis paper presents the results of a study that aimed to identify from which learning approaches and theories come the didactic and pedagogical principles that the Courses Pedagogical Project o (PPCs) of Pedagogy distance courses offered by federal universities in the Northeast region propose to design and develop their educational technologies (environments, materials and activities). After a literature review of approaches and learning theories, followed by the documentary and content analysis of PPCs, we identified that the prevail principles come from New School, Constructivist and Socioconstrutivism. However: a) the documents are not objectives on how to operationalize these principles in designing and developing environments, materials and activities, and; b) the learning evaluation processes (and instruments) are not described or are inaccurate. These findings suggest that the PPCs, the basic documentation of the courses, are not used as references for designing and developing the educational technologies used in the investigated courses.Keywords: Distance education, Pedagogy, Learning theories, Educational technologies, Course projects

Aspectos epidemiológicos do Câncer Infantojuvenil em Porto Velho-RO no período de 2018 a 2020 / Epidemiological aspects of childhood cancer in Porto Velho-RO from 2018 to 2020

A presente pesquisa tem como objetivo determinar a prevalência do câncer infantojuvenil no Município de Porto Velho-RO no período de 2018 a 2020. Para tanto, utilizou-se método descritivo de dados quantitativos que teve como base de dados o Departamento de Informática do Sistema Único de Saúde (DATASUS). Verificou-se 389 casos registrados entre o período de 2018 a 2020, sendo 31 casos diagnosticados em 2018, 196 em 2019 e 162 em 2020. Foi possível observar que o câncer mais predominante na faixa etária de 0 a 5 anos é a leucemia linfóide, em contrapartida o carcinoma in situ de pele foi o tipo de câncer mais frequente no grupo etário entre 15 a 19 anos. Sendo assim, conclui-se que a incidência dos mais variados tipos de tumores na população pediátrica é diferente em relação à faixa etária e ao sexo, tornando seu perfil epidemiológico bastante diversificado. O câncer infantojuvenil no município de Porto Velho-RO apresenta informações epidemiológicas específicas a respeito da maior frequência do tipo de câncer, maior prevalente e a distribuição do gênero mais acometido. Com essas informações, este estudo abre uma perspectiva para a realização de novos trabalhos apresentando uma descrição da situação epidemiológica atualizada e da atenção a esta patologia, evidenciando o fato de haver poucos estudos e pesquisas em relação ao tema nas demais regiões do estado, sendo, portanto, de extrema relevância

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Genomics and epidemiology for gastric adenocarcinomas (GE4GAC): a Brazilian initiative to study gastric cancer

Abstract Gastric cancer (GC) is the fifth most common type of cancer worldwide with high incidences in Asia, Central, and South American countries. This patchy distribution means that GC studies are neglected by large research centers from developed countries. The need for further understanding of this complex disease, including the local importance of epidemiological factors and the rich ancestral admixture found in Brazil, stimulated the implementation of the GE4GAC project. GE4GAC aims to embrace epidemiological, clinical, molecular and microbiological data from Brazilian controls and patients with malignant and pre-malignant gastric disease. In this letter, we summarize the main goals of the project, including subject and sample accrual and current findings

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Rationale, study design, and analysis plan of the Alveolar Recruitment for ARDS Trial (ART): Study protocol for a randomized controlled trial

Background: Acute respiratory distress syndrome (ARDS) is associated with high in-hospital mortality. Alveolar recruitment followed by ventilation at optimal titrated PEEP may reduce ventilator-induced lung injury and improve oxygenation in patients with ARDS, but the effects on mortality and other clinical outcomes remain unknown. This article reports the rationale, study design, and analysis plan of the Alveolar Recruitment for ARDS Trial (ART). Methods/Design: ART is a pragmatic, multicenter, randomized (concealed), controlled trial, which aims to determine if maximum stepwise alveolar recruitment associated with PEEP titration is able to increase 28-day survival in patients with ARDS compared to conventional treatment (ARDSNet strategy). We will enroll adult patients with ARDS of less than 72 h duration. The intervention group will receive an alveolar recruitment maneuver, with stepwise increases of PEEP achieving 45 cmH(2)O and peak pressure of 60 cmH2O, followed by ventilation with optimal PEEP titrated according to the static compliance of the respiratory system. In the control group, mechanical ventilation will follow a conventional protocol (ARDSNet). In both groups, we will use controlled volume mode with low tidal volumes (4 to 6 mL/kg of predicted body weight) and targeting plateau pressure <= 30 cmH2O. The primary outcome is 28-day survival, and the secondary outcomes are: length of ICU stay; length of hospital stay; pneumothorax requiring chest tube during first 7 days; barotrauma during first 7 days; mechanical ventilation-free days from days 1 to 28; ICU, in-hospital, and 6-month survival. ART is an event-guided trial planned to last until 520 events (deaths within 28 days) are observed. These events allow detection of a hazard ratio of 0.75, with 90% power and two-tailed type I error of 5%. All analysis will follow the intention-to-treat principle. Discussion: If the ART strategy with maximum recruitment and PEEP titration improves 28-day survival, this will represent a notable advance to the care of ARDS patients. Conversely, if the ART strategy is similar or inferior to the current evidence-based strategy (ARDSNet), this should also change current practice as many institutions routinely employ recruitment maneuvers and set PEEP levels according to some titration method.Hospital do Coracao (HCor) as part of the Program 'Hospitais de Excelencia a Servico do SUS (PROADI-SUS)'Brazilian Ministry of Healt

A dataset of acoustic measurements from soundscapes collected worldwide during the COVID-19 pandemic

Political responses to the COVID-19 pandemic led to changes in city soundscapes around the globe. From March to October 2020, a consortium of 261 contributors from 35 countries brought together by the Silent Cities project built a unique soundscape recordings collection to report on local acoustic changes in urban areas. We present this collection here, along with metadata including observational descriptions of the local areas from the contributors, open-source environmental data, open-source confinement levels and calculation of acoustic descriptors. We performed a technical validation of the dataset using statistical models run on a subset of manually annotated soundscapes. Results confirmed the large-scale usability of ecoacoustic indices and automatic sound event recognition in the Silent Cities soundscape collection. We expect this dataset to be useful for research in the multidisciplinary field of environmental sciences