NSF award 2500101 · Stanford University

Exploration and adaptation of experience sampling to understand the impact of artificial intelligence tools on the work of teaching

Final report due

29 December 2028

in 803 days · The award ends on 31 August 2028.

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Decide about an extension3 May 2028in 563 days
award ending 2028-08-31 · Research.gov
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Extension request17 Jul 2028in 638 days
award ending 2028-08-31 · Research.gov
PAPPG 24-1: “at least 45 days prior to the end date”
No-cost extension notice21 Aug 2028in 673 days
award ending 2028-08-31 · Research.gov
PAPPG 24-1: “at least ten calendar days prior to the end date”
Final report due29 Dec 2028in 803 days
award ending 2028-08-31 · Research.gov
PAPPG 24-1: “no later than 120-days following the end date of the award”
Project outcomes report due29 Dec 2028in 803 days
award ending 2028-08-31 · Research.gov
PAPPG 24-1: “no later than 120 days following the end date”
Award is closed out29 Dec 2028in 803 days
award ending 2028-08-31 · Research.gov
PAPPG 24-1: “financially closed out 120 days after their expiration date”

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NSF lists this award's end date as 31 August 2028.
NSF rules say the final report is due no later than 120 days after that.
So the final report is due by 29 December 2028.

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Award card

Award number: 2500101
Period of support: 1 Sep 2025 – 31 Aug 2028
Amount: $499,715
Awardee: Stanford University, Stanford, CA
Program: ITEST-Inov Tech Exp Stu & Teac, ECR-EDU Core Research
Directorate: EDU

Abstract

Despite popular discourse about how generative artificial intelligence (AI) tools might increase efficiencies in education, it is yet to be determined how--or even if--AI tools for teachers are having that envisioned effect. There is currently a baseline assumption that AI should increase teacher efficiency through offloading. However, there is limited research to support such claims, and there is reason to believe…

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