Computer Science

Engineering Plastic Filters: Photo Classification

Upper Elementary Impacts of Computing Data & Analysis Algorithms & Programming In Classrooms

Students train and test an online photo classification model to distinguish between photos of animals and photos of trash.

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unit Overview

This computer science module can be taught independently but is intended to be taught after the YES Elementary Engineering Plastic Filters unit. Students consider how a machine learning model could be used to classify objects in photos as either animals or trash. They learn that the model uses patterns in training data to make predictions about new data. Groups then add to the existing training data to improve classification results.

3 lessons
45 minutes per lesson
Student materials available in Spanish
Computational tools used: Teachable Machine (free and web-based)
Materials needed: Materials kits are not available for purchase for computer science modules

Standards Alignment

YES units align with state and national science standards, integrating seamlessly with popular elementary science curricula.

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unit Resources

Digital Resources (FREE)

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Module Map

Students work in groups to test an imperfect machine learning photo classification model. They are introduced to the concept of training data.

Students recognize and apply visual patterns to classify photos as a computer would. They discover that patterns that work for one set of photos may not work well for another.

Students work in groups to select new training data to add to the machine learning model. They retrain the computer to improve the model’s accuracy.