Innovative High School Curriculum: Bridging Color Chemistry and Artificial Intelligence


  • North Carolina State University introduces a groundbreaking high school curriculum.
  • The curriculum seamlessly blends color chemistry and artificial intelligence (AI).
  • Aims to enhance students’ interest in science while teaching chemistry and AI concepts.
  • The experiment involves pH levels and pH test strips as practical tools.
  • The student-trained AI model outperforms visual pH level predictions by 5.5 times.
  • Students utilize cellphone cameras and machine learning software to process data.
  • Real-world relevance is emphasized, particularly in areas with limited resources.
  • Survey results reveal increased motivation and knowledge among students.
  • Curriculum’s potential to expand and teach similar concepts in color chemistry.
  • Fosters a deeper appreciation for the intersection of technology and science.

Main AI News:

North Carolina State University has introduced an innovative high school curriculum that seamlessly integrates color chemistry and artificial intelligence, fostering students’ enthusiasm for science and their understanding of the world around them. This weeklong program serves as a testament to the power of education in bringing together seemingly disparate fields, all while adhering to a structured format that emphasizes both chemistry and AI.

The curriculum’s objective was to determine the effectiveness of a concise high school science module in imparting knowledge in chemistry, a subject often considered challenging, and artificial intelligence. To achieve this, the researchers designed a straightforward experiment involving pH levels, which gauge the acidity or alkalinity of a liquid solution. pH test strips, along with color conversion charts, served as valuable tools, where color changes on the strips indicated the pH level.

When students conducted tests on pH levels using these strips, the curriculum encouraged them to ponder the question: “Can machine learning offer a more accurate reading of pH strips than human visual interpretation?” Remarkably, the results showed that the AI predictive model, trained by the students, was approximately 5.5 times more precise than visual assessments.

Students engaged in hands-on activities by utilizing their cellphone cameras to capture images of pH test strips immersed in various common liquids, such as beverages, pond or lake water, and cosmetics. They then made visual predictions of the pH values of these substances. Additionally, students received pH test strips from instructors, which were tested using sophisticated instrumentation. They were tasked with visually predicting the pH levels of these strips as well.

The real-world implications of this experiment were not lost on the students. They contemplated scenarios where access to sophisticated instruments might be limited, such as in underdeveloped regions with water quality concerns. In such cases, having a simple and reliable method to determine pH levels becomes critical.

To process the data and train their AI models, students used Orange, a user-friendly machine learning software that requires no coding knowledge. Over time, the machine learning algorithm improved its accuracy by discerning subtle changes in test-strip colors and correlating them with pH values. Ultimately, students compared the pH level predictions made by their AI models with their own visual predictions. While not flawless, the AI predictions proved to be significantly closer to the actual pH values.

The curriculum’s impact extended beyond the laboratory. Before and after participating in the weeklong program, students were surveyed, and the results were telling. They reported heightened motivation to learn and an improved understanding of both chemistry and AI. The practical application of cutting-edge technology to real-world problems and scientific advancements resonated with the students, fostering a deeper appreciation for the convergence of technology and science, particularly in the realm of chemistry.

According to Yang Zhang, assistant professor of textile engineering, chemistry, and science, “On the chemistry side, there are a lot of similar color chemistry concepts we can teach this way. We can also scale this curriculum up to include more students.”


The integration of color chemistry and artificial intelligence in high school education represents an exciting step forward, providing students with the tools to explore and appreciate the dynamic relationship between science and technology. This innovative curriculum opens doors to a world where complex concepts are made accessible, inspiring the scientists and innovators of tomorrow.