Recently Added Curriculum

Students explore the fundamentals of digital logic by building truth tables and designing their own logic circuits. Using a series of scaffolded worksheets, students gain hands-on experience with core logic gates such as AND, OR, NOT, NAND, NOR, XOR, and XNOR. They apply this knowledge by analyzing multi-input circuits and eventually designing their own four-input logic system. On the final day, students use the free online circuit simulator Wokwi to test and verify their custom logic gate designs. Through this activity, students gain foundational experience in binary reasoning, digital electronics, and circuit logic that underpins real-world computing systems.

Students become red team ethical hackers by building a safe hacking lab and learning tools used to test real networks. Students are introduced to ethical hacking, containers, network engineering, wordlist generation, and brute-force password cracking. Using Podman, students create and network their hacker system (Kali Linux) and target system (Metasploitable2 or “Meta2”). With Netcat, they scan the target’s IPs, ports, and services, then design efficient username and password lists with Maskprocessor. Finally, students test vulnerabilities by attempting controlled brute-force attacks on the target and its DVWA web server using Medusa and their custom wordlists. The activity builds practical lab skills and broadens understanding of computer science topics such as cryptography, web apps, networking, containers, and AI/LLMs.

Teams of students become startup car companies aiming to win a contract with Porsche. The project requires them to design and build four prototype vehicles using plastic bricks. They then take on various engineering roles to plan a production floor layout and run a simulated production process. After analyzing their initial performance and making improvements, a second simulation determines which team wins the contract based on the number of high-quality vehicles they produce. The project concludes with each team creating a report using data from both simulations to evaluate their performance and suggest future improvements.

In this high school engineering activity, students use a sound level meter or Arduino microcontrollers to measure sound levels at various locations and then analyze the data. The project begins with identifying constraints and learning to set up and program Arduino devices with sound sensors, while also brainstorming community issues related to noise pollution. Students then collect sound level data over time, analyze it using descriptive statistics, and create graphs and charts to visualize trends. Applying principles of sound insulation and damping, they design and build a soundproofing system, test its effectiveness by measuring sound levels before and after application, and use statistical tests to determine whether the reduction is significant.

Students use Arduino microcontrollers to measure heart rate and blood oxygen levels with the MAX30102 sensor board and to capture electrocardiogram (ECG) signals using the AD8232 sensor board. They analyze the data to detect arrhythmias by comparing results from both sensors. Throughout the activity, students gain hands-on experience with installing the Arduino Integrated Development Environment (IDE), adding libraries, compiling code, and running programs on Arduino microcontrollers.

Students use the engineering design process to investigate radiation and its effects on human health. Students design and build simple Geiger counters, learn about different types of radiation and typical background levels, and gather data from various locations. They then analyze their findings, compare them to accepted safety standards, and refine their devices for improved performance. The activity culminates in a final report where students explain their results, justify conclusions with evidence, and reflect on the strengths and limitations of their investigation and design.

Students learn that 40–50% of carbon emissions contributing to climate change come from energy used in building construction and operation. Using CAD software, they calculate the total energy consumption of a house or building across its entire life cycle. By testing their models, students see the quantitative impact of their design choices and then modify their designs to reduce energy use and minimize environmental impact.

Students tackle a real-world problem by designing and testing plant-based solutions to break down toilet paper. Using the engineering design process, they research, brainstorm, prototype, test, and refine their approaches—just like professional engineers. By experimenting with different plant materials, students develop creative problem-solving skills while considering real constraints faced in global sanitation systems.

Students become fairy tale engineers as they explore the classic tale of The Three Little Pigs through the lens of design and testing. After reading and comparing The Three Little Pigs and The True Story of the 3 Little Pigs, students work in teams to build three model houses using straws, popsicle sticks, and LEGO bricks. They then test the strength of each house by using a leaf blower to simulate the "huff and puff" of the Big Bad Wolf, while measuring wind speed with an anemometer. Students apply engineering principles to investigate which materials provide the most structural strength and learn how real-world engineers use testing and data to improve designs.

Students explore the environmental and human health impacts of microplastics while designing and testing their own filtration solutions. After learning about how microplastics enter the environment and human body through various pathways, potentially leading to serious health issues such as cancer, students work in teams to develop a practical solution to filter microplastics from water. Using readily available and cost-effective materials, students engage in the complete engineering design process: from initial research and brainstorming to prototyping, testing, and presenting their solutions. Students test their filters using water samples containing microplastic particles and evaluate the effectiveness of their designs through visual inspection or microscopic analysis.

Students design and construct a functional, budget-friendly microscope using lenses and a variety of accessible materials. Through this process, they investigate how light behaves as it travels through different media, gaining a deeper understanding of optical principles. As their exploration progresses, students enhance their comprehension of key concepts such as reflection, refraction, absorption, and the wave nature of light.

Students explore the concept of sediment transport and its impact on bayous, which play a vital role in city drainage systems in low-lying areas, such as those found in the southeastern United States. Using the engineering design process, they build bayou models in plastic bins using sand and water, observe how water moves sediment, and investigate the effects of erosion, deposition, and flood risks. To address these challenges, students design and test solutions such as sediment traps and barriers to control sediment buildup and improve water flow.

This unit introduces students to neuroscience through a systems approach with a strong emphasis on computational thinking and data analysis. Students investigate the neural origins of muscle movement by collecting and analyzing electrical signals from surface electrodes placed on the arm during simple hand gestures, such as wrist and finger movements. Using microcontrollers and an inquiry-based approach, students explore how different patterns of neural activation produce specific motions. The unit fosters practical data analysis skills while deepening students’ understanding of the interdisciplinary connections between neuroscience, computer science, and engineering.

This fourth and final activity in the unit allows students to analyze and visualize neural data, providing them with the opportunity to explore patterns in brain signals. Using Python, students interpret neural activity linked to various movements, such as finger and wrist motions, to understand how neural signals correspond to physical actions. The graphics.py library offers an intuitive introduction to data visualization, enabling students to create clear graphical representations of neural data before advancing to more sophisticated tools like matplotlib. By visualizing and analyzing their findings in a report, students deepen their understanding of neural data processing while honing critical skills in data analysis, programming, and scientific communication.

This third activity builds on the data collected from the previous "Decoding Muscle Movement: Analyzing Neuromuscular Signals With EMG" activity. Students now gather electrical data from various groups' experiments using Muscle SpikerBox kits, which save the data in .wav format. They then use Google Colab, a cloud-based Python development environment, to create a shared database for collaborative data analysis. As they convert and process the data, students write Python scripts and engage in data analysis, honing key computational thinking skills such as breaking down complex problems, identifying patterns, abstracting essential details, and designing algorithms. This hands-on activity promotes teamwork, enhances data manipulation proficiency with Python, and deepens students' understanding of neuroscience research methodologies.