Using AI Tools to Construct, Revise, and Evaluate Scientific Models

Scientific models are vital tools that scientists use to describe, explain, or predict scientific phenomena. Through inquiry and data analysis, scientists evaluate and refine these models by supporting or refuting them based on new evidence. Scientific models can take various forms, including diagrams, chemical equations, or computer simulations. For example, the atomic model evolved significantly from Thomson’s “Plum Pudding” model to Rutherford’s model and later to Bohr’s model, reflecting ongoing scientific discoveries and revisions.

Artificial Intelligence (AI) tools greatly assist in scientific modeling by processing complex datasets, identifying key variables, and assessing prediction accuracy probabilistically. Teachers can design learning activities using platforms, such as "Machine Learning for Kids", enabling students to experience the entire modeling process—constructing, testing, revising, and evaluating scientific predictive models. Students will learn to handle data, select appropriate variables, and build predictive models. Such activities enhance students’ skills in data analysis, pattern recognition, scientific reasoning, and problem-solving, thereby laying a solid foundation for future scientific inquiry.

Explore the teacher guides and resources below to learn effective strategies for integrating AI tools into your classroom to support students in constructing, revising, and evaluating scientific models.

• Teacher's Guide

• Reference materials (Chinese version only)
• Sample lesson worksheet (Chi / Eng)
• Example on the Use of Lesson Planning Tool (PDF)

• Lesson Planning Tool (Trial Version) (XLS)

Mr. NG Ka-wo (Concordia Lutheran School)

Mr. LEUNG Pui-hong, Wilfred (Sacred Heart Canossian College)