ABSTRACT

Teachers are extraordinarily important to student learning, but researchers have surprisingly little data about what teachers do moment-to-moment with students. What are the instructional moves and improvisational responses that characterize highly effective practice? To better understand and support U.S. K-12 STEM teachers, this Incubator project will develop a network of "tutor observatories." Tutor observatories are learning environments that record teacher engagements with students along with information about the context of the interaction. These observatories can be built in classrooms, in digital simulations for teacher education, in platforms for online tutoring, and other new environments. These observatories will record their data in a shared format that allows researchers to compile a dataset of one million moments where teachers interact with students. From these data, researchers will be able to gain a deeper understanding of STEM teacher practice, identify highly effective practices, and develop training data that can inform a new generation of artificially intelligent tools to support teachers and student learning. Given important issues of privacy, security, and trust, representatives of teachers and community members will play a vital role in the ethical development of the tutor observatories and million tutor moves dataset.

During the period of this incubator grant, the network will convene five working groups related to human and computer tutoring platforms, classroom recordings, teaching simulations, emerging models for tutor observatories, and family and teacher engagement. These working groups will conduct a set of tasks focused on stakeholder engagement, visioning, prototyping, pilot testing, and dissemination. Together the network will develop detailed prototypes for a network of tutor observatories, guidelines for protecting teacher and student privacy, and community engagement, and a plan for implementation and evaluation, including a set of partner sites lined up for application to the Mid-scale Research Infrastructure grant. The expected benefit to the field is a large dataset that can be used to investigate questions about how to optimize students' STEM learning experiences, the foundation for technology to build more intelligent STEM tutors, and the groundwork for critical digital infrastructure to make the U.S. more resilient to future interruptions in learning.

This project is supported through a partnership with the Bill & Melinda Gates Foundation, Schmidt Futures, and the Walton Family Foundation. Funding is also provided by the Discovery Research preK-12 program (DRK-12) program at NSF. The DRK-12 program seeks to significantly enhance the learning and teaching of science, technology, engineering and mathematics (STEM) by preK-12 students and teachers, through research and development of innovative resources, models and tools. Projects in the DRK-12 program build on fundamental research in STEM education and prior research and development efforts that provide theoretical and empirical justification for proposed projects.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

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