| Summary: | Smart assistants like Amazon’s Alexa, Apple’s Siri, and Google’s Google Home have become commonplace in many people’s lives, appearing in their phones and homes. Despite their ubiquity, these conversational AI agents still largely remain a mystery to many, in terms of how they work and what they can do.
To lower the barrier to entry to understanding and creating these conversational AI agents for young students, I expanded on Convo, a conversational programming agent that can respond to both voice and text inputs. I created a simple and intuitive user interface for students to input training data, create programs, and test the conversational AI agents they create. To further assist anyone in using Convo, I also produced a couple of video and PDF tutorials that outline how to use Convo. Additionally, I also developed a curriculum to teach students about key concepts in AI and conversational AI in particular, including the Big 5 AI Ideas and the difference between constrained and unconstrained natural language models.
I ran a 3-day workshop in partnership with MIT’s eSPARK program, with a total of 15 participating middle school students. Through the data collected from the preand post-workshop surveys as well as a mid-workshop brainstorming session, I was able to explore how students’ perceptions, understanding, literacy, and visions of conversational AI agents changed. During the workshop, students were able to create their own conversational AI agents. I also found that after the workshop, students tended to think that conversational AI agents were less intelligent than originally perceived, gained confidence in their abilities to build these agents, and learned some key technical concepts about conversational AI as a whole. Based on these results, I am optimistic about Convo’s ability to teach and empower students to develop conversational AI agents in an intuitive way.
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