Opening the AI “black box”
The punchline is that young children (4-6) are completely equipped to learn about AI algorithms from systems like PopBots. Developmental factors like age and perspective-taking skills sometimes made a difference in what children understood. However, the biggest differences occurred when we looked at how different children used the toolkit. Children who explored the activities more thoroughly did better on tricky questions that other children usually got wrong. This suggests that a further improvement to this system would be more personalized to each child, helping them explore new ideas as they go along.
In terms of children’s perceptions of AI, we saw that children developed an understanding of robots as “learning beings.” After teaching the robot themselves, they saw the robot as an object of dual nature: something that was alive, yet a machine; and something that had a mind, but no independent motivations.
Children need a lot more exposure to engineering and technology in the early classroom. For most of the children, this was their first experience with any formal technology education although every child had had a previous experience with robots and interactive virtual agents like Siri, Alexa, and Google. Only a handful of children that I worked with knew what an engineer was, and even those who had some idea did not identify themselves as engineers. Yet, preschool and kindergarten children are arguably the best engineers at in any school—their classrooms are full of little projects and construction sets. Compare this with science; almost all of the children wanted to be scientists because preschool curricula expose children to science and positively reinforces the field. The same needs to be done for engineering.
What PopBots does differently
The coolest thing about this project is how it builds on what’s been done before. PopBots leverage the social robot technology found in Tega. Tega is a powerful platform that the Personal Robots group has used to teach children literacy skills, second languages, socioemotional skills, and even programming. We have seen over and over how a social robot learning companion helps children learn through interactive play.
PopBots also build on existing computational thinking platforms like Scratch and ScratchJr. that made it possible for children all over the world to embrace programming creatively. We also learned a lot from AI curricula designed for students in high school and above. Over the past two years we have been excited to see AI education gain traction, but very little exists for younger children. PopBots uniquely empower children to learn about AI before they can even read or have learned any complex math. It uses a social robot as a window into the machine, allowing children to use social interaction to explore AI.
We believe this unique approach is important because it comes at computer science topics from a completely different angle than programming. Any non-programming, non-technical person can benefit from the metaphors we present to understand the AI algorithms that are all around them.
This spring, we are training local teachers to deliver this curriculum in their classrooms. One of the most difficult problems in tech education, besides funding, is equipping teachers to deliver the material. We are very excited to take this next step.
If you are interested in ways to explore AI with your child today then check out this list of resources compiled by Blakeley Hoffman.
I would like to acknowledge my advisor, Cynthia Breazeal, my labmates in the Personal Robots Group, and my professors and role models who contributed to this work including Marina Bers and Paul Harris. Without their knowledge, creativity, support, advice, and encouragement PopBots would not exist. Thank you!