The National Science Board (NSB) held its quarterly meeting on February 23rd and 24th. First on the agenda was a report from the National Science Foundation’s (NSF) Director Dr. Sethuraman “Panch” Panchanathan. The director spoke about NSF values and how they align with both the NSB’s and the new Administration’s vision, specifically in leadership, partnership, innovation and research. Dr. Panchanathan characterized this as a new and exciting time for the organization. He emphasized that the DNA of NSF is intertwined with outside values and goals, such that NSF is always needed, helpful, and supported. Panchanathan also spoke about the future strategy of NSF and the 2022-2026 strategic plan. This proposal focuses on urgency, speed, scale, translation, innovation, and partnerships. NSF is striving to expand knowledge in science, engineering, and learning, as well as advance the capability of the nation to meet current and future challenges.
The meeting had a significant focus on the diversity and inclusion initiatives set forward by the organization and the Biden Administration. Director Panchanathan was key to the Vision 2030 initiative, as he helped establish NSF’s Racial Equity Task Force. The task force’s primary role is to review organizational policies and practices to make sure they comply with Title IX and break down potential barriers to diversity and inclusivity. The Task force has two working groups, one is internal and the other is external, and recently hosted an NSF webinar titled “Black Scientists & Engineers at Our Nation’s HBCUs: Making American History Now.” The panelists offered key insights into HBCUs’ contributions to their local economies and roles in advancing science and technology innovation. NSF is optimistic about the future of inclusion.
STEM workforce support and retention are central to the NSF mission, and the COVID-19 pandemic has negatively affected the industry’s new researchers and students. Without new scientists and scholars, the future of American research is damaged significantly. Recent studies have shown that the mentor-to-student model does not work as it should and could be improved upon. The current model is contingent on a successful relationship between student and mentor, however, if that relationship fails the student’s prospects could be shattered. Triads, collective, and network style mentorship programs are seen to be much more effective. Director Panchanathan offered possible solutions including the use of evidence-based approaches, structured feedback systems, support for multiple mentorship styles, rewarding effective mentorship, and mitigating negative mentorship experiences. He also suggested integrating mentoring educations, tools, research, and evaluation into grant-based activities.
The NSB passed two resolutions. One aims to address unconscious biases and improve the preparedness of proposal reviewers, while the second seeks to increase the potential of proposals’ Broader Impacts (BI) to benefit society.
Both resolutions require an evaluation and report back to the NSB within 12 months:
“Training to improve peer reviewing in merit review process states that the NSF Director implement policies—such as mandatory training for reviewers—to maximize reviewers’ preparedness to fulfill their responsibilities. NSF’s merit review training video provides guidance on key elements of those responsibilities. These include that reviewers fairly and transparently consider all proposals, are aware of their own possible implicit biases, and give grant applicants useful written feedback. While over 90% of reviewers who watch the video deem it valuable, only 20% of reviewers have watched it.
Broader impacts experts to serve on Committees of Visitors (COV) states that the Director develop a plan to ensure BI expertise is included on COV panels. COVs provide external expert evaluations and recommendations that inform NSF and NSB evaluations of existing programs and processes and future directions for NSF. Recent COV reports call attention to disparities between how reviewers discuss BI and Intellectual Merit (IM) goals of proposals in written reviews, with BI analysis being more cursory and less rigorous than analyses of IM. Yet a significant number of proposals reviewed in this way are still recommended for funding.”
