When curiosity is sparked...

Today in neuroscience class, I introduced the students to an EV3 robotic input-output system, aiming to draw parallels between robotics and the human nervous system.

I set up the robot with three sensors—touch, ultrasonic, and light—and programmed it with four input-output triggers. If students pushed the button, the motor would move. If they placed an object within three inches of the ultrasonic sensor, the robot would "growl." The light sensor triggered a heart display when a white surface was placed over it, and "angry eyes" when a black surface was detected.

While the button and ultrasonic sensor triggers were relatively easy for students to find, the light sensor triggers posed more of a challenge, encouraging deeper exploration.

Afterward, I prompted a discussion about how this robot system is similar to the human nervous system. We compared each robot part to neuron types—sensory, interneurons, and motor neurons—and talked about the implications of mimicking life through neural networks versus the simplicity of robotic code.

This exploration set the stage for future lessons on sensory-stimulus pathways, reflexes, and reactions, helping students understand the complexity of human input-output systems compared to robotic ones.
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Check out some photos of the robot in action below!

The more I teach students in my Biochemistry class about the intricacies of Protein Folding, the more certain I become that it is a perfect learning medium for uniting various disciplines. From protein translation in biology, to intermolecular forces in chemistry, to applications of AI in computer science, developing an appreciation for the structure-function relationship in biology via investigating the elegant nature of how proteins fold is a powerful way to unite STEM disciplines. Below are a few activities I am currently using with my students in chemistry, biology, and engineering courses. 

• FoldIt (Engineering/Computer Science Application): Free software that teachings protein folding through online gaming. 
• Mini Toobers (Chemistry Application): Excellent way to teach intermolecular forces (via amino acid hydrogen bonding) and covalent bonding (via disulfide bridges). 
• Hydrophobic Packing Simulation (Chemistry/Biology Application): Visual method for observing effects of polarity on protein structure. 
• Paper Models (Engineering/Biology): Excellent way to physically interact with the protein secondary and tertiary structure. 
• AlphaFold (Computer Science): System that uses AI to solve the "Protein Folding Problem". 

The video below shows how I used ChatGPT (inspired by a student request) to create an program capable of translating an mRNA sequence into a protein sequence using HTML, CSS, and JavaScript files that run locally on my browser. Click here for files. 

Recently I have been exploring ways of using ChatGPT and p5.js together to create animations formy physics and chemistry classes. Below is my first attempt at generating a code for a bouncing ball in ChatGPT then using p5.js to model the code. In the future I would like to generate position, velocity, and acceleration vs. time graphs within the animation, as well as develop methods for modeling ideal gas behavior. So much potential. Stay tuned!