Research

The objective of PrimaryAI is to significantly advance theoretical and practical understanding of how to introduce upper-elementary students to artificial intelligence with a curriculum integrating AI and life science. Using problem-based learning as a pedagogical strategy, PrimaryAI seamlessly integrates computational thinking, artificial intelligence, and life science concepts, creating deeply engaging learning experiences for upper elementary science education.

Learning Sciences

Using design-based research, the project is investigating three key research questions:

1. How can we create engaging learning experiences integrating artificial intelligence and life science for upper elementary students by leveraging immersive problem-based learning? 

2. How can we design a teacher professional development model for integrating artificial  intelligence and life science in upper elementary classrooms? (a) How do teachers adapt the learning activities for local contexts? (b) What kinds of professional development support do teachers need to work with content that is both unfamiliar and complex?

3.  In what ways does engagement with immersive problem-based learning support upper elementary students’ learning artificial intelligence and life science? 

Learning Environment

PrimaryAI engages students in immersive problem-based learning experiences that integrate artificial intelligence and life science. In the immersive learning environment, students utilize an in-game semi-autonomous robot, disguised as a penguin, to remotely collect images and other data to serve as evidence for explaining recent changes to the penguin population and surrounding habitat. Based on authentic science approaches in which scientists use camouflaged robots to infiltrate and investigate penguin colonies in real-world ecological research. PrimaryAI is developed to run on PCs (Windows and macOS) and Chromebooks. Supporting these platforms enables implementing the learning environment in a broad range of school contexts.