Recently Added Curriculum

With a design-thinking approach, students incorporate neuroscience into their robotics learning experiences in this activity. They perform an experiment to design a basic human-robot interface through which electromyography (EMG) signal readings from the muscle movements in their arm are translated to simple movements in their robots. Students brainstorm factors they believe will vary between arm movements, and use these factors to develop a data processing program for the EMG data collected. In doing so, students form an understanding of the considerations that are involved in designing, building, and evaluating a human-machine interface.

Students dive deeper into fear conditioning by exploring the neural pathways involved in tone and shock responses. They review the basics of synapses and neural pathways before using a virtual lab simulation to connect tone and shock pathways in the amygdala, aiming to create a circuit that results in fear conditioning. Throughout the process, students experiment with different firing rates and configurations, troubleshooting through trial and error to find the correct values that activate the neurons. The task culminates in a more advanced exploration of calcium ion plasticity, enhancing students' understanding of how fear conditioning works at multiple levels in the brain.

The brain is a complex computer with its own hardware and ‘software.’ Students are introduced to the brain’s function as an electrical circuit by exploring the similarities between neurons and electrical circuits. Students first learn about neurons, their structure, and how they transmit signals using electrical impulses, much like wires in a circuit. Through interactive activities, they build and analyze simple electrical circuits, drawing parallels to neural pathways in the brain. By understanding how the brain processes information and learns fear, students connect neuroscience concepts to real-world applications such as neuroplasticity, brain-machine interfaces, and biomedical engineering.

Students build on their understanding of how the brain uses circuits to respond to external stimuli, learning about Pavlovian conditioning through the lens of neural circuits. By exploring Pavlov’s dog experiment, students connect their knowledge of neurons and neural pathways to understand how animals, including humans, learn through association. The lesson emphasizes the concept of learning and synaptic plasticity, which are key to understanding how neural circuits control behavior. Students engage in hands-on activities, such as drawing circuits, discussing the Pavlov experiment, and using tools such as Google Colab to explore fear learning and the role of the amygdala. With the help of videos and group discussions, they examine the neural pathways involved in both reward and fear conditioning.

Humans (and all animals) have the fascinating ability to learn and adapt their bodily movements and thoughts as they navigate their lives in a complex world. This three-activity unit introduces how engineers and scientists study the ability of our brain to learn in general, using the classic paradigm of Pavlovian learning where a dog can be subconsciously taught to associate a bell tone with a food reward after an initial training period. Or a rodent can be taught to learn to fear a tone after a training period where the tone is paired with a foot-shock.

Students engage in hands-on activities that provide an opportunity to learn about biological and environmental engineering. Students learn about perfluoroalkyl and polyfluoroalkyl substances (PFAS), and how to remove them from drinking water. Students are given water from a local water source and must create a filtration system. The students will then take the filtered water and attempt to purify that water.

Students use the engineering design process to engage in a hands-on investigation of how atmospheric conditions impact learning while connecting their findings to real-world sustainability goals. By constructing and using an Arduino air quality monitor, students collect and analyze data on factors such as temperature, humidity, carbon dioxide levels, and air particulates. Through this process, they explore how these environmental properties influence cognitive function, concentration, and overall well-being. Students then interpret their data, draw evidence-based conclusions, and relate their findings to the United Nations Sustainable Development Goals (SDGs), particularly those related to health, education, and sustainable cities. Finally, they apply their knowledge by proposing actionable improvements to optimize classroom air quality, fostering healthier, more effective learning environments.

Students use the engineering design process as they work in groups to research one of five genetic disorders and learn about CRISPR-Cas9 using a paper model and an online interactive tool. They adapt the paper model to simulate how CRISPR-Cas9 could potentially cure their assigned disorder. Using their research and models, they create a pitch for research funding in the form of a trifold poster. Finally, the entire class debates and discusses which disease should receive the most funding to develop a CRISPR-based cure, considering humanity’s need for a cure (number of cases, disease severity, availability of other treatments, etc.) and the feasibility of targeting their disease with CRISPR.

Students discover how electric and magnetic fields exert forces on objects by using the engineering design process to design and build a small model maglev train. Students add weight, such as pennies, to test how much their model can hold. Through this hands-on activity, students gain a deeper understanding of magnetic repulsion and attraction. They identify and describe contact and non-contact forces by investigating the properties of magnets and their interactions.

Students use Microsoft Visual Studio Code and GitHub Copilot to master writing functions in Python, actively assessing the effectiveness of these tools to define future success criteria for engineers developing similar technologies. Through hands-on coding activities, they explore the significance of functions, enhancing code readability and enabling more innovative programming approaches. Additionally, students examine the impact of these technologies in programming, offering valuable suggestions to refine and advance engineering tools.

Students learn the basic principles of the humoral immune response and use a model to understand how antibodies and antigens interact in an enzyme-linked immunosorbent assay (ELISA). The ELISA is a laboratory diagnostic tool used to identify and quantify antigens. Through this model, students discover how the interactions between antigens and antibodies can aid in disease diagnosis and provide valuable information for disease management.

Students explore density through hands-on experimentation and collaborative problem-solving. They design and test mixtures using everyday substances, aiming to create the densest solution. Students brainstorm, plan, create, and test their mixtures, recording observations and analyzing results. They then refine their designs and retest to improve outcomes. A final discussion connects the experiment to real-world concepts, such as how density impacts environmental and global challenges.

Students participate in hands-on activities that introduce them to chemical engineering and sustainability. They explore various separation methods, such as distillation, crystallization, and adsorption, and apply these techniques in real-world scenarios. The activity concludes with an engineering design challenge, where students must design a system to separate the components of potting soil and develop strategies to recycle the separated materials, applying their understanding of sustainability and separation processes.

Students explore Young’s Modulus by investigating how materials respond to stress and strain, measuring their stiffness and flexibility using Arduino technology. Through hands-on experimentation, students learn how variations in force application can affect the accuracy of their measurements. Building on this knowledge, they apply the engineering design process to create a device that ensures a consistent pressure and angle during testing, improving the reliability of their results.

Students act as environmental engineers to solve a problem using carbon dioxide (CO2) emissions from cars and wildfires. Wildfires are a timely topic because every year they cause people in many areas to face poor air quality. Students use Microsoft Excel to investigate CO2 emitted from two sources: highway traffic and forest fires. They estimate and graph the CO2 emitted by forest fires and from U.S. highway driving annually from 2004 to 2021. After they analyze these two pieces of data, they analyze a specific fire and evacuation that happened in Saratoga Springs in June 2020, named the Knolls Fire. Finally, using the Excel data and the Knolls Fire data, students decide whether the U.S. should spend money on reducing the number and severity of wildfires, or on reducing CO2 emissions from driving cars. The students design and create a poster based on their decision and present it to the class.