Hi, my name is Duri Long, and today I'm going to be quickly presenting our paper The Role
of Collaboration, Creativity, and Embodiment in AI Learning Experiences. "AI literacy"
is something that's becoming increasingly more important as we engage with AI in all
aspects of our everyday lives--in workplaces, homes, and schools. It's important that we
are able to critically engage with and understand the technologies that we interact with and
how they work.
We are interested in designing museum exhibits to communicate competencies related to AI
literacy as a skillset, and we are interested in designing these exhibits for museums and
science centers that have historically played an important role in public science communication
but which have sort of been focused on less in the existing literature on AI education.
We focus on incorporating three key design considerations in the exhibits that we develop
and we go into more detail in the paper about why these three, but in short--embodied interaction,
collaboration and creativity have all been shown to promote engaging and effective museum
learning experiences, and they've also been shown to be important inroads for learning
about computer science and other abstract concepts.
So our hypothesis is that interactions with embodied, collaborative, and/or creative exhibits
in informal learning spaces is able to promote interest and improve understanding of AI.
In order to test this hypothesis, we designed three exhibit prototypes and conducted a study
to evaluate whether our key, three key design features contributed to learning and interest
development.
Due to COVID 19 we had to make some modifications to our study so we ended up developing box
sized exhibits that we delivered to families' homes where they interacted with them. This
enabled us to maintain the collaborative, embodied nature of interaction, but within
a, you know, even outside of a museum.
The first prototype that we developed was called Knowledge Net, which was focused on
communicating AI literacy competencies related to knowledge representations and decision
making. Learners were able to build a semantic network using concepts and tiles that were
provided to them. They could creatively build whatever network they wanted, take a picture
of it, upload it to a web app that we developed, and interact with an AI chatbot that used
the network that they developed in order to to answer questions.
The second prototype we developed was Creature Features which was focused on communicating
competencies related to machine learning by allowing learners to build datasets using
provided card decks and explore how different datasets that they developed would influence
an AI algorithm that tried to classify a creature as a bird or not a bird.
And finally, the third prototype that we developed, LuminAI, was focused on taking an existing
research project and expanding it with explainable features in order to make it into an educational
experience. So we took the existing LuminAI research project--which involved a co-creative
dance partner--and we added features to it that allowed learners to explore the agent's
reasoning and decision making modes, switch out databases of different dance gestures,
and interactively explore a three dimensional visualization of the agent's gesture memory,
where they could see how the agent clustered different gestures together based on their
similarity using machine learning.
In order to evaluate these three prototypes, we conducted a study with 14 families and
38 total participants. We collected audio and video data as well as survey data of the
families' interactions. This paper focuses mostly on the survey data.
Returning to the hypothesis, we assessed all of the sort of key concepts in bold. So we
looked at whether the exhibits facilitated embodied, collaborative, creative interaction,
as well as whether they facilitated interest development and learning about AI.
And I won't go into too much depth about the results here, but we found that the exhibits
did indeed foster interest development and improve understanding, including the three
design features--embodied interaction, collaboration, and creativity.
We also found that LuminAI did not lead to any notably larger creativity outcomes or
interest or learning gains than the other exhibits, which was a little surprising, but
we think may potentially be because LuminAI didn't lead to sort of a lasting creative
artifact, since dance is sort of of an ephemeral nature.
And finally we found that incorporating opportunities for meta cognition, such as an iterative testing
and revision cycle could facilitate deeper engagement with the learning goals of the
exhibits. We saw this in LuminAI--er not in Luminai--in Knowledge Net as well as Creature
Features, but not in LuminAI.
Thank you so much and please let me know if you have any questions.