Exploring Machine Learning with YES
Join the Youth Engineering Solutions (YES) team for an interactive webinar exploring how students can meaningfully engage with machine learning in age-appropriate ways through two YES units and their corresponding computer science modules:
Engineering Plastic Filters + Photo Classification (Upper Elementary) Students act as environmental engineers to tackle plastic pollution and use Google’s Teachable Machine to train a model that distinguishes animals from trash—learning how data quality and variety affect accuracy.
Engineering Eco-friendly Slippers +User Reviews Analysis (Middle School) Students design sustainable slippers and use MATLAB Live Scripts to see how computers analyze user reviews, exploring how data bias and selection shape outcomes.
Together, these experiences demonstrate how YES’s Computer Science Framework supports authentic, ethical, and engaging uses of technology in the engineering classroom. We’ll discuss:
How YES integrates machine learning in hands-on, age-appropriate ways
The connections between engineering and computational thinking
How the YES computer science modules encourage students to consider bias, data quality, and social context
How exposure to machine learning helps students become informed creators, not just consumers, of technology
Source: Museum of Science, Boston
