Students capture and examine air particles to gain an appreciation of how …
Students capture and examine air particles to gain an appreciation of how much dust, pollen and other particulate matter is present in the air around them. Students place "pollution detectors" at various locations to determine which places have a lot of particles in the air and which places do not have as many. Quantifying and describing these particles is a first step towards engineering methods of removing contaminants from the air.
Students develop an understanding of air pressure by using candy or cookie …
Students develop an understanding of air pressure by using candy or cookie wafers to model how it changes with altitude, by comparing its magnitude to gravitational force per unit area, and by observing its magnitude with an aluminum can crushing experiment.
Students develop their understanding of the effects of invisible air pollutants with …
Students develop their understanding of the effects of invisible air pollutants with a rubber band air test, a bean plant experiment and by exploring engineering roles related to air pollution. In an associated literacy activity, students develop visual literacy and write photograph captions. They learn how images are manipulated for a powerful effect and how a photograph can make the invisible (such as pollutants) visible. Note: You may want to set up the activities for Air Pollution unit, Lessons 2 and 3, simultaneously as they require extended data collection time and can share collection sites.
In this activity, students will simulate the equal and unequal distribution of …
In this activity, students will simulate the equal and unequal distribution of our renewable resources. Also, they will consider the impact of our increasing population upon these resources and how engineers develop technologies to create resources.
A slide deck of mathematical questions that revolve around an image. Contains …
A slide deck of mathematical questions that revolve around an image. Contains six grade level aligned questions, standards alignment across related domains to demonstrate a potential progression of questions across grade, and related “After the Image” questions and activities to do at home.
This task illustrates the process of rearranging the terms of an expression …
This task illustrates the process of rearranging the terms of an expression to reveal different aspects about the quantity it represents, precisely the language being used in standard A-SSE.B.3.
This rich task is an excellent example of geometric concepts in a …
This rich task is an excellent example of geometric concepts in a modeling situation and is accessible to all students. In this task, students will provide a sketch of a paper ice cream cone wrapper, use the sketch to develop a formula for the surface area of the wrapper, and estimate the maximum number of wrappers that could be cut from a rectangular piece of paper.
The purpose of this task is to engage students, probably working in …
The purpose of this task is to engage students, probably working in groups, in a substantial and open-ended modeling problem. Students will have to brainstorm or research several relevant quantities, and incorporate these values into their solutions.
Students examine how the power output of a photovoltaic (PV) solar panel …
Students examine how the power output of a photovoltaic (PV) solar panel is affected by temperature changes. Using a 100-watt lamp and a small PV panel connected to a digital multimeter, teams vary the temperature of the panel and record the resulting voltage output. They plot the panel's power output and calculate the panel's temperature coefficient.
This art history video discussion looks at an "Icon of the Triumph …
This art history video discussion looks at an "Icon of the Triumph of Orthodoxy (Byzantine)", c. 1400, tempera and gold on wood, 39 cm x 31 cm (British Museum, London).
This course provides a broad theoretical basis for system identification, estimation, and …
This course provides a broad theoretical basis for system identification, estimation, and learning. Students will study least squares estimation and its convergence properties, Kalman filters, noise dynamics and system representation, function approximation theory, neural nets, radial basis functions, wavelets, Volterra expansions, informative data sets, persistent excitation, asymptotic variance, central limit theorems, model structure selection, system order estimate, maximum likelihood, unbiased estimates, Cramer-Rao lower bound, Kullback-Leibler information distance, Akaike's information criterion, experiment design, and model validation.
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