Text Classification for AI Education

Randi Williams

March 15, 2021


Tejal Reddy, Randi Williams, Cynthia Breazeal. 2021. Text Classification for AI Education. In Proceedings of the 52nd ACM Technical Symposium on Computer Science Education (SIGCSE’21).


To help middle school students explore Artificial Intelligence (AI), we built a text classifier extension into a block-based programming interface using Tensorflow’s K-Nearest Neighbors and Universal Sentence Encoder libraries. After training a model, students can incorporate it into their own creations. In this paper, we discuss how we taught students the AI concepts behind the classifier and how students used the text classifier to build their own projects. Lastly, we touch on how our classifier works just as well as other text classification platforms. This text classification tool and curriculum is a powerful way to help students become more knowledgeable about the ever-growing field of AI and to raise their awareness about applications of AI within their own lives. 

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