AI at ʻIolani School

To prepare for future exploration of AI and machine learning in Upper School, K-6 teachers design a wide range of activities to develop computational thinking and digital citizenship skills needed for responsible and safe technology use. In our K-6 Design & Tech classes, students not only learn to code but engage in multi-step project-based learning in which students use various technologies in tandem with their own creativity. Teachers utilize age-appropriate, vetted AI-enabled tools, such as adaptive learning platforms and educationally-aligned chatbots (e.g. MagicSchool) to provide personalized practice, resources and feedback.

Students who begin with AI Literacy in Grades 7 and 9 can continue their journey in our state-of-the-art AI Lab through Introduction to AI. Those eager to go further can pursue the Computer Science track, culminating in Honors Machine Learning Foundations. Together, these courses give students a strong foundation in how artificial intelligence works, starting with basic programming and key concepts and progressing to more advanced systems, where students design, train, and deploy real-world AI applications using industry-standard tools and cutting-edge infrastructure. Guided by faculty and industry mentors on independent projects, students focus on deeply understanding the algorithms behind AI while practicing a human-in-the-loop approach. This emphasis moves them beyond simple automation, fostering the agency, innovation, and ethical discernment essential for leadership in an AI-enabled world. Sample student projects include:

• Smart Order AI: Predictive Analytics for Retail Distributor Buyback Reduction
  This machine learning system addresses retail inventory issues by analyzing historical data to predict demand and prevent stockouts and food waste.
• Video Virality Predictor: Content Virality Prediction Model for Content Creators
  Students proposed a deep learning tool to predict a video's virality pre-upload. This data-driven approach aims to help content creators overcome the trial-and-error in navigating search engine algorithms and forecast reach.
• Intelligent Optimization of ʻIolani School Traffic Flow
  This project proposes a machine learning solution to campus traffic congestion, aiming for smoother, safer routes for daily commutes, benefiting the school community.

Our robotics and engineering pathway bridges mechanical systems and intelligent design. Starting in Engineering Principles, students are exposed to fundamental engineering fields including electronics, mechanical design, sensors and programming. Following, students have the opportunity to dive deeper into more advanced courses such as Smart Robotics and Machines in Motion, incorporating AI and vision processing tools for real-time decision-making and navigation. In the Engineering Innovation Studio, students focus on developing innovative solutions to real-world problems. Working in teams, students propose challenging projects that push the students to design, prototype and build large scale systems that mirror industry practice and the ability to develop or bring a product to market. Relevant industry tools and hardware advance their capabilities as they leave ‘Iolani School.

A recent sample project:

• ​​AI-Integrated Automated Screw Sorter
  This project uses a custom-trained YOLOv11 AI model to instantly identify and sort hardware by length and type. By combining computer vision with an Arduino-controlled mechanical system, the machine provides an efficient, automated solution for organizing robotics components.

In Design and Fabrication classes, students learn how to use familiar and new tools to design, visualize, prototype, and take their ideas from sketches to realized pieces. Working in a variety of mediums and materials including woods, metal, plastics, resin, and composites, students gain an understanding of strengths and constraints of real-world fabrication techniques. In an unprecedented time where AI can produce and draw from creatives in the field, students are equipped with the know-how to use cutting-edge machinery and the care to responsibly wield the digital tools that connect them to other creatives.

Sample student projects include building a full acoustic guitar, an outrigger canoe paddle, a kayak rudder and furniture items from locally sourced wood. 

Students develop their data literacy and data management skills through Intro to Data Science and Bioinformatics, applying statistical analyses to biological datasets. In AP Research and Honors Independent Research, they conduct year-long investigations that can incorporate machine learning/AI as a field or as a tool for research or analysis. Students learn to analyze complex data ethically, producing scholarly work presented at a variety of community venues. Sample projects include:

• Investigating The Extent of Hawaii’s Regional Economic Resilience Through a Machine Learning Approach, Anaïs Ortega '26: Uses Machine Learning to predict Hawaiʻi's economic resilience.
• Utilization of Seawater Coolant in AI Datacenters: Conserving Electricity Consumption and Increasing Heat Removal Efficiency, Lily Jin '27: Investigates using seawater for cooling AI data centers to save electricity.
• Agentic simulation: A novel introductory philosophical experience for students using LLM game agents, Tata Li, '27: Explores a novel introductory philosophical experience for students using Large Language Model (LLM) game agents.

We seek to teach AI literacy throughout our disciplines so students engage ethically with AI in a variety of contexts. For example, they may use AI to practice a World Language, build a study guide in their Physics class, or expand upon a creative idea in Theatre class. Students are also taught to critically evaluate AI output in History courses, and advocate for ethical development in courses like Race and Social Justice. There are also a wide range of co-curricular clubs that are exploring AI alongside faculty mentors, such as Girls who Code, Digital Literacy Ambassadors and the Investment Club.