This project introduces high school students to programming concepts through writing a Python script that finds and counts sunspots in real images of the Sun.
In the age of AI, data literacy is one of the most critical skills we can teach our students. As a STEM educator, data analysis is a constant thread in both my professional and personal life.
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.
Given the rise of information and data in today’s world, we need various methods and approaches to analyze them, whether it is to make predictions from given information or to categorize them into different groups based on observed trends.
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.
Python is commonly used for processing and visualizing large amounts of data.
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.
In order to make informed decisions, students must know how to properly analyze and interpret data. This is one of the main learning goals in my physics classes.