Text Classification for AI Education

摘要

In recent years, Artificial Intelligence (AI) has become increasingly prevalent in our lives. Because of this, individuals of all ages need to be aware of how AI works. To introduce middle school students to AI concepts, we built a text classifier extension into a block-based programming interface that allows students to train custom machine learning models. To make the extension more accessible, a translator was incorporated where the language of each input is automatically detected and translated to English. Our classifier's accuracy was comparable to similar classifiers such as Machine Learning for Kids' text classifier and Uclassify's text classifier, and its effectiveness was tested against these classifiers with two test datasets. We piloted the classifier with middle school students in an online AI course. The students first learned the concepts behind the classifier which consisted of word embeddings, K-Nearest-Neighbors, and classification bias. They were then able to use the text classifier to create their own projects. Some of the projects were a snake identifier, a TV show suggester, a chat robot, and a healthcare robot. With this extension, students were able to engage in project-based learning to become more knowledgeable about the ever-growing field of AI and raise their awareness about applications of AI within their own lives.