Conference: Accelerating the Future of AI and Data-driven Education

Award ID: 2230697

This NSF Convergence Accelerator Workshop will create smart and integrated platforms, devices and processes for education technology. Current educational technologies often do not sufficiently leverage basic research on learning, nor have a culture of continuous improvement, nor meet the needs of diverse learners, nor leverage the growing power of computers. One issue is the disconnected, fragmented, and often closed nature of different sectors: educators, parents, commercial ventures, not-for-profit organizations, stakeholders, researchers, and communities. A concerted effort among diverse stakeholders is needed now to create real and immediate solutions. Significant technology exists for digital instruction. Experts in academia (learning science, AI, human-computer interaction, education, psychology), industry and government will identify barriers and solutions to the delivery of high-quality online education; they will inform best practices in design, generate future development and testing, and leverage technology and new modes of platform design. This workshop will support communities to reason about fruitful near-term approaches for scaling up innovative pedagogies. We will increase the number of trials of new products; test more often and fail faster; identify promising interventions, and evaluate the conditions and circumstances that increase the probability of successful products. The scientific agenda will investigate and augment human learning at large scale in authentic education settings (online, hybrid, and on-the-job). The workshop will establish a framework for new AI, learning science, and education theory and technologies to understand, model, infer, and respond to learning. It will explore new theory, algorithms, big data, and systems that optimize every point in the education process to understand students, organize what they can learn, and optimize how they learn. The workshop will couple use-inspired AI research with foundational AI and learning science research in a virtuous cycle and forge new partnerships among diverse stakeholders as they bridge the divide with novel tools from engineers, makers, technologists, and designers. It will make a laser focus on projects that present well-defined deliverables within 3-years. 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.

NSF Program Director: Michael Reksulak