Myths and FAQs about Project Reporting


The purpose of this post is to help you shorten the learning curve of Research.gov reporting, answer some of the common questions we hear from you, and debunk the persistent myths and old habits that no longer fit with current practice. Continue reading

DEB Numbers: Analysis of Broader Impacts


A recent paper in Bioscience by a AAAS Fellow (Sean Watts), an Einstein Fellow (Melissa George), and an NSF Program Director (Doug Levey) explores how the Broader Impacts Criterion was applied and reported in DEB proposals between 2000 and 2010. A major conclusion is that activities aimed at recruiting and mentoring students from underrepresented groups are proposed more than twice as often as they are eventually reported by PIs; of all the types of broader impact activities, broadening participation is by far the toughest to achieve. This result and others are discussed in the context of a recent review of the Merit Review Criteria by the National Science Board and resulting revisions to the Proposal & Award Policies & Procedures Guide (PAPPG).

What’s your DEB Story?


Sometimes, it can be hard to fit what you want to tell us into your annual report. Other times, the coolest results, recognition of important research outcomes, and broader impacts only come to fruition in the years after a grant was closed and the final reports compiled.

We’re interested in unearthing the dark data on award outcomes. Help us tell the full story of DEB funding: from personal experiences to news-making discoveries, we want to hear from you. Comment, email us, or schedule a time to talk with us to share your experiences. Continue reading

Assessing the Value of the Doctoral Dissertation Improvement Grant


Caveat: This post is based on the research and analysis of Kara Shervanick, a 2013 Summer Student in DEB. She did valuable work but her time was relatively brief for this complex information gathering and analysis process. This work does provide some context for understanding DDIG program outcomes, however, we point out that the small sample size limits the power of these analyses.

See our other recent posts on the DDIG program here and here. Continue reading