The outbreak of the COVID-19 pandemic has dramatically shaped higher education and seen the distinct rise of e-learning as a compulsory element of the modern educational landscape. Accordingly, this study highlights the factors which have influenced how students perceive their academic performance during this emergency changeover to e-learning. The empirical analysis is performed on a sample of 10,092 higher education students from 10 countries across 4 continents during the pandemic’s first wave through an online survey. A structural equation model revealed the quality of e-learning was mainly derived from service quality, the teacher’s active role in the process of online education, and the overall system quality, while the students’ digital competencies and online interactions with their colleagues and teachers were considered to be slightly less important factors. The impact of e-learning quality on the students’ performance was strongly mediated by their satisfaction with e-learning. In general, the model gave quite consistent results across countries, gender, study fields, and levels of study. The findings provide a basis for policy recommendations to support decision-makers incorporate e-learning issues in the current and any new similar circumstances.
ResumoA zona de transição Amazônia-Cerrado é caracterizada pela alta diversidade de ecossistemas, biodiversidade e condições climáticas. Este trabalho tem como objetivo investigar evidências de mudanças climáticas na precipitação e temperatura no Estado do Maranhão. Os dados de normais climatológicas desde 1977 até 2014 provenientes de 12 estações meteorológicas do Instituto Nacional de Meteorologia, distribuídas no Estado foram utilizados para construir a série temporal de dados climáticos. Os dados foram divididos em dois grupos referentes às estações climáticas, seca e chuvosa. O teste de Mann-Kendall foi aplicado para detecção de tendências de aumento ou decréscimo, tanto na série temporal completa, quanto nos dados referentes aos períodos seco e chuvoso. Os resultados evidenciaram uma forte elevação na temperatura do ar em todas estações do Estado. No bioma amazônico em relação a precipitação, as estações de Bacabal e Zé Doca registraram tendências de aumento e diminuição, respectivamente. No bioma cerrado, as estações de Carolina e Colinas apresentaram tendências de aumento e diminuição, respectivamente. Os resultados apresentados neste trabalho mostraram que as mudanças climáticas ocorrem diferentemente no Estado do Maranhão, não necessariamente influenciada pelo bioma. Palavras-chave: mudanças globais, desastres naturais, sensoriamento remoto.
Evidence of Climate Change in the Amazon-Savanna Transition Region in Maranhão State
AbstractThe Amazon-Savanna transition zone is characterized by high diversity of ecosystems, biodiversity and climatic conditions. This work aims to investigate evidences of climate change on precipitation and temperature in the Maranhão state. The climatological normal data from 1977 to 2014 provided from 12 meteorological stations of National Meteorological Institute distributed in state area was used to build the climatic time series. This dataset was divided in two groups according to climate stations, dry and rain seasons. The Mann-Kendall test was applied to detect increase and decrease trends regarding complete time series and both, dry and rain season series. The results show a strong climate change in air temperature. In the amazon biome, Bacabal and Zé Doca stations registered increase and decrease tendencies, respectively. In the savanna biome, in Carolina and Colinas stations presented increase and decrease tendencies, respectively. The results presented in this work shows that climate change occurred differently in Maranhão state, not influenced necessarily by biome.
Tropical forests provide essential environmental services to human well-being. In the world, Brazil has the largest continuous area of these forests. However, in the state of Maranhão, in the eastern Amazon, only 24% of the original forest cover remains. We integrated and analyzed active fires, burned area, land use and land cover, rainfall, and surface temperature datasets to understand forest fragmentation and forest fire dynamics from a remote sensing approach. We found that forest cover in the Maranhão Amazon region had a net reduction of 31,302 km2 between 1985 and 2017, with 63% of losses occurring in forest core areas. Forest edges extent was reduced by 38%, while the size of isolated forest patches increased by 239%. Forest fires impacted, on average, around 1031 ± 695 km2 year−1 of forest edges between 2003 and 2017, the equivalent of 60% of the total burned forest in this period. Our results demonstrated that forest fragmentation is an important factor controlling temporal and spatial variability of forest fires in the eastern Amazon region. Thus, both directly and indirectly, forest fragmentation can compromise biodiversity and carbon stocks in this Amazon region.
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