85 research outputs found
Department of Social Services Quarterly Report, Fiscal Year 2007 4th Quarter, 4/1/2007 - 6/30/2007
Department of Social Services Quarterly Report, Fiscal Year 2007 2nd Quarter, 10/1/2006 - 12/31/2006
Department of Social Services Quarterly Report, Fiscal Year 2006 2nd Quarter, 10/1/2005 - 12/31/2005
Department of Social Services Quarterly Report, Fiscal Year 2007 1st Quarter, 7/1/2006 - 9/30/2006
Department of Children and Families Quarterly Report, Fiscal Year 2008 4th Quarter, 4/1/2008 - 6/30/2008
Asynchronous student engagement in analysis of climate data achieves learning objectives related to climate change understanding, statistical competence, and climate anxiety
Learning in asynchronous online environments has gained importance over the last several decades, and educational environment shifts from the COVID-19 pandemic appear to have increased this need. Science educators and students need information about which approaches work in the asynchronous environment where informal feedback tends to be reduced, compared to other teaching modalities. In this study, we asynchronously implemented a learning module across 5 institutions that guided students (Nâ=â199) from prescriptive data analysis through guided inquiry and eventually to open inquiry. The module focuses on the science behind climate change. Students work with the same authentic data sets used by professional scientists to examine geologic history and causes of climate change. By analyzing contemporary atmospheric carbon dioxide and temperature data and then using the 800,000-year record available from the Vostok ice core proxy record of atmospheric properties, students identify the causes of climate change and discover the unprecedented nature of recent atmospheric changes. Using a pre/post-module assessment, we demonstrate improvement in studentsâ understanding of climate change processes and statistical methods used to analyze data. However, there was no evidence that the module develops studentsâ scientific reasoning about the relationship between causation and correlation. Students maintained that correlation is not causation, even when a robust causal mechanism (i.e., the greenhouse effect) explains the link between atmospheric carbon dioxide and temperature. Finally, our analysis indicated that generally, anxiety about climate change was reduced during the module, such that students become less anxious about the climate change the more they learn about it. However, science-denying students experienced much higher anxiety about climate change than students who accepted the scientific consensus about climate change. Climate science-dissenting students were so few in this study that a statistical comparison was not possible, but this intriguing finding warrants further investigation of the role of anxiety in science denial. Mainly, this study demonstrates how asynchronous online learning environments can indeed support the achievement of learning objectives related to conducting authentic science, such as increasing understanding of climate change and statistical concepts, all while not provoking anxiety about climate change
Norwalk Virus Shedding after Experimental Human Infection
Noroviruses are shed in feces up to 8 weeks after infection
A New Solution to the Relative Orientation Problem using only 3 Points and the Vertical Direction
This paper presents a new method to recover the relative pose between two
images, using three points and the vertical direction information. The vertical
direction can be determined in two ways: 1- using direct physical measurement
like IMU (inertial measurement unit), 2- using vertical vanishing point. This
knowledge of the vertical direction solves 2 unknowns among the 3 parameters of
the relative rotation, so that only 3 homologous points are requested to
position a couple of images. Rewriting the coplanarity equations leads to a
simpler solution. The remaining unknowns resolution is performed by an
algebraic method using Grobner bases. The elements necessary to build a
specific algebraic solver are given in this paper, allowing for a real-time
implementation. The results on real and synthetic data show the efficiency of
this method
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