#3907 Google AI Studio STEM Apps
#3907 Google AI Studio STEM Apps
#3907 List and describe 15 great STEM web applications to be created by students in Google AI Studio
Here are 15 innovative STEM web application ideas that students can prototype and build using Google AI Studio.
These projects are categorized by discipline (Science, Technology, Engineering, Math) and leverage the Gemini API's multimodal capabilities (text, code, and vision). Students can design the prompts and logic in AI Studio, then export the code to build a functional web interface.
Science
1. The "Leaf Doctor" (Biology & Botany)
Concept: A web app where users upload a photo of a sick houseplant or garden crop. The app identifies the plant species, diagnoses the likely disease (fungus, pest, nutrient deficiency), and recommends an eco-friendly treatment.
Google AI Studio Implementation: Use Gemini Pro Vision (multimodal). The prompt should instruct the model to act as an "expert botanist," analyzing image textures for specific pathology markers.
Student Learning: Image recognition, biological classification, and prompt engineering for specific diagnostic criteria.
2. Lab Safety Sentinel (Chemistry)
Concept: A real-time safety assistant for chemistry labs. Students can type in a list of chemicals they plan to mix. The app analyzes the combination for potential hazards (e.g., "Do not mix bleach and ammonia") and generates a safety protocol checklist.
Google AI Studio Implementation: Use Gemini Pro (text). Upload a "knowledge base" of chemical safety data sheets (SDS) into the context or prompt to ground the AI's answers in factual safety data.
Student Learning: Chemical interactions, safety protocols, and "grounding" AI responses to prevent hallucinations.
3. The Carbon Footprint "Receipt" Scanner (Environmental Science)
Concept: Users take a picture of a grocery receipt or a meal. The app estimates the carbon footprint of the items listed/shown and suggests 3 sustainable alternatives for the highest-impact items.
Google AI Studio Implementation: Use Gemini Pro Vision. The model needs to perform OCR (Optical Character Recognition) on the receipt text, match items to a general carbon impact knowledge base, and generate comparative recommendations.
Student Learning: Data extraction, environmental impact analysis, and sustainability metrics.
4. Astro-explainer (Astronomy)
Concept: An app that simplifies complex astronomical abstracts. Users paste a dense paragraph from a NASA technical report, and the app rewrites it for a 5th-grade reading level, using analogies (e.g., explaining a black hole using a bathtub drain analogy).
Google AI Studio Implementation: Use Gemini Pro with a "System Instruction" that sets the persona to "Science Communicator for Kids." Use few-shot prompting (giving 3 examples of good simplifications) to train the style.
Student Learning: Technical writing, natural language processing, and complex physics concepts.
Technology
5. Regex Wizard (Computer Science)
Concept: Regular Expressions (Regex) are notoriously hard for students to learn. This app lets users describe a text pattern in plain English (e.g., "Find all email addresses that end in .edu"), and the app generates the correct Regex string and explains how it works.
Google AI Studio Implementation: Use Gemini Pro optimized for coding. The prompt should demand a specific output format: The Code, followed by a breakdown of each symbol's function.
Student Learning: Pattern matching, syntax logic, and translating natural language to code.
6. The Phishing Detective (Cybersecurity)
Concept: A safety tool where users paste the text of a suspicious email or SMS. The AI analyzes the text for psychological triggers (urgency, fear, greed) and technical red flags (mismatched domains), assigning a "Suspicion Score."
Google AI Studio Implementation: Use Gemini Pro. The prompt should instruct the model to identify social engineering tactics specifically.
Student Learning: Cybersecurity awareness, social engineering patterns, and text classification.
7. Accessibility Alt-Text Generator (Web Design)
Concept: A tool for web developers to ensure their sites are accessible. Users upload an image intended for a website, and the AI generates descriptive, screen-reader-friendly "Alt Text" that accurately describes the visual context.
Google AI Studio Implementation: Use Gemini Pro Vision. The prompt must be tuned to avoid flowery language and focus on descriptive, functional text required by W3C standards.
Student Learning: Web accessibility standards (WCAG), visual analysis, and inclusive design.
8. Pseudocode-to-Python Converter (Programming)
Concept: Helps beginner coders understand logic. Users write out an algorithm in loose pseudocode or bullet points, and the app converts it into clean, commented Python code.
Google AI Studio Implementation: Use Gemini Pro with a high "temperature" setting for creativity or low for strict syntax. The output should include comments explaining why certain Python functions were chosen.
Student Learning: Algorithmic thinking, syntax translation, and code structure.
Engineering
9. Breadboard Debugger (Electronics)
Concept: Students upload a photo of their physical Arduino or breadboard circuit. The AI attempts to trace the connections and identify common errors like short circuits, backwards LEDs, or missing resistors.
Google AI Studio Implementation: Use Gemini Pro Vision. This is a stress test for the model's spatial reasoning. The prompt needs to ask the model to "trace the wire from pin 13" and verify connections against a provided logic description.
Student Learning: Circuit logic, component identification, and troubleshooting hardware.
10. 3D Print Fail Fixer (Manufacturing)
Concept: Users upload a photo of a failed 3D print (e.g., spaghetti mess, layer shifting). The app diagnoses the likely cause (bed leveling, temperature too high/low) and suggests slicer setting adjustments.
Google AI Studio Implementation: Use Gemini Pro Vision. Train the prompt with examples of common failures (spaghetti = adhesion issue) to act as a "3D Printing Technician."
Student Learning: Manufacturing processes, error analysis, and visual diagnostics.
11. Structural Load Visualizer (Civil Engineering)
Concept: Users describe a bridge design or upload a simple sketch. The AI describes where the tension and compression forces would theoretically be highest, offering a "text-based simulation" of structural integrity.
Google AI Studio Implementation: Use Gemini Pro Vision for sketches. The model provides a qualitative physics analysis based on statics principles.
Student Learning: Statics, force distribution, and structural design concepts.
12. The "Parts Picker" Assistant (Mechanical Engineering)
Concept: A user describes a machine they want to build (e.g., "a robot that can lift a 5lb box"). The app suggests the necessary motors (torque requirements), battery size, and material strength needed.
Google AI Studio Implementation: Use Gemini Pro. This requires the model to perform basic physics calculations (Force = mass x acceleration) to recommend components.
Student Learning: System integration, component sizing, and mechanical design requirements.
Mathematics
13. Real-World Geometry Hunter (Geometry)
Concept: A scavenger hunt app. The app challenges the user: "Find an example of an isosceles triangle in your room." The user uploads a photo, and the AI verifies if the object in the photo matches the geometric criteria.
Google AI Studio Implementation: Use Gemini Pro Vision. The prompt must strictly evaluate the geometric properties of the main object in the image.
Student Learning: Geometric properties, observation skills, and applying math to the real world.
14. Data Pattern Scout (Statistics)
Concept: Users paste a raw CSV dataset (small scale). The AI acts as a data analyst, identifying outliers, trends, and suggesting which type of graph (bar, line, scatter) would best represent the data.
Google AI Studio Implementation: Use Gemini Pro (text). The model analyzes the text-based data array to find minimums, maximums, and frequency distributions.
Student Learning: Data literacy, statistical analysis, and data visualization best practices.
15. The Socratic Math Tutor (Algebra/Calculus)
Concept: Unlike a calculator that gives the answer, this app refuses to solve the problem. Instead, users upload a math problem, and the AI provides a hint or asks a guiding question to help the student solve it themselves.
Google AI Studio Implementation: Use Gemini Pro Vision or Text. The "System Instructions" are critical here: "You are a tutor. Never give the final answer. Only ask guiding questions to lead the user to the solution."
Student Learning: Critical thinking, problem-solving steps, and meta-cognition.
Relevant Resource
This video demonstrates how to take a project from a Google AI Studio prototype to a fully functional, deployed web application, which is the exact workflow students would need to bring the ideas above to life. Google Gemini AI Studio is ABSOLUTELY INSANE (FREE)
From <https://gemini.google.com/app/> Google Gemini 3.0. Pro Thinking
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