Career: Example-Enhanced Intelligent Tutoring

NSF Award Search · 01002526DB NSF RESEARCH & RELATED ACTIVIT · $670,000 · view on nsf.gov ↗

Abstract

The rapidly evolving workplace landscape calls for the development of scalable upskilling and reskilling programs for maintaining a competent and competitive workforce. According to the World Economic Forum’s 2023 future of jobs report, six in ten workers will require training before 2027, but about half of the workforce does not have access to adequate training opportunities today. From what we know about human learning, it is clear that deliberate practice, appropriate scaffolding, and timely feedback are needed for learning to be effective. Practical implementation of such features requires substantial investment from domain experts or instructors, which makes it difficult to provide these opportunities at scale. The overarching goal of this project is to make expertise sharing more efficient through helping experts create example-based intelligent tutors. The research team will partner with other universities, local community colleges, and public schools to test the developed tools, which will then be made publicly available. Through this work, the project will make it easier to develop effective training programs that scale well to millions of workers, improving both their own opportunities and the U.S. economy as a whole. This project focuses on the teaching and learning of complex problem-solving tasks, e.g. “Identify a recent economic phenomenon that involves market failure, explain which type of market failure it is, and propose a solution.” To capture the expert

Key facts

NSF award ID
2442990
Awardee
Regents of the University of Michigan - Ann Arbor (MI)
SAM.gov UEI
GNJ7BBP73WE9
PI
Xu Wang
Primary program
01002526DB NSF RESEARCH & RELATED ACTIVIT
All programs
CAREER-Faculty Erly Career Dev, Cyber-Human Systems
Estimated total
$670,000
Funds obligated
$413,700
Transaction type
Continuing Grant
Period
07/01/2025 → 06/30/2030