At the Shaqfeh Lab, I worked on creating a robot that could easily move through non newtonian fluid. A non newtonian fluid is any type of fluid (gas or liquid) that does not behave like water, i.e. corn syrup, synovial fluid, molasses.
In today's world of technology it is easier than ever to compile large sums of data. But once that data has been collected, it does not do much good if we do not know how to analyze and interpret it.
In this ETP, students will analyze presented data to evaluate and propose solutions to complex real-world problems. Specifically, they will review data and technical considerations related to the design of battery modules.
From the moment we wake up, our brains use data to help us understand the world around us and act accordingly. We don’t only gather data for the sake of it. We don’t even do it with the purpose of analyzing it, but for it’s interpretation and implications that this has.
Many science teachers have had the experience of students attempting to generate the “correct” data that they think the teacher wants. This unfortunately leads to a common practice of students copying data from others or even fabricating it themselves.
In today’s increasingly digital world, we produce (and continue to produce) large amounts of data about things ranging from test scores, to social media posts that we “Like” or “Comment”, to online shopping recommendations, to how safe (or not) a new engineering design could be, to self-driving c
This two to three day lesson allow a students to create a hypothesis on what makes a good Algebra student, then analyze data in order to see if their hypothesis holds.
This ETP is a lesson series that would follow a field trip in which data is collected on ecological values. Students will use Microsoft Excel to organize and graph data collected by their class, previous classes, and scientists.
This ETP is designed to get students ready for inquiry based curriculum. Students will be required to base arguments on evidence provided in tables or graphs, by learning how to read them based on column headings, axis, headings, and best fit lines.