AI Chef Trainer: Introducing Students to the Importance of Data in Machine Learning

Abstract

The AI Chef Trainer is an educational web app that introduces children to the role of data in machine learning (ML) through the engaging task of recipe recommendation. Initially, students tested the AI Chef's capabilities by selecting from a list of ingredients to see what the system recommended as possible recipes. After observing the recommendations, they contributed by adding their own recipes—each being a set of ingredients and a corresponding recipe-name—which were used to retrain the model and finally re-tested recipe suggestions. This cyclical process of testing, contributing, retraining, and post-training testing provided students with hands-on experience in how AI systems learn and adapt over time based on new data. We tested our software with middle school students. The results indicated that students recognized the importance of both data quantity and specificity in the training process. 45 of 52 students entered recipes, and 26 of the 52 tested their own recipes using the specific ingredients they entered. Students were introduced to the concept of confidence percentages via the AI recipe suggestions. Even as the primary focus was the role of data in machine learning, the AI Chef Trainer software also served as a window into students' cultural expression and personal preferences.