Big Data

Dear Colleague Letter: STEM Education for the Future

Wednesday, June 20, 2018

Read DCL NSF 18-084 Online

Dear Colleagues:

NSF invites proposals to solve educational challenges created by the technology revolution. To effectively respond to many of the problems facing our nation, new scientific advances are needed, as defined in the Big Ideas for Future NSF Investments. Achieving these advances will require changes in what people learn and how they learn it. Through this STEM Education for the Future Dear Colleague Letter (DCL), existing NSF education and workforce development programs encourage innovative proposals to prepare scientists and engineers for work in new contexts created by technology and big data.

Specifically, through this DCL, NSF aims to support STEM educational research and development projects whose results can enable our country to: better prepare its scientific and technical workforce for the future; use technological innovations effectively for education; advance the frontiers of science; and adapt to both new work environments and new education pathways needed to prepare students at all levels for those environments.

Technology, Computation, and Big Data are driving changes to daily life. Computing, sensing, data storage, data access, communication, and hardware technologies continue to change our lives and work. These technologies produce unprecedented volumes of data and vast interconnectivity capabilities, such as data provided by ubiquitous sensing and the Internet of Things. Personal, behavioral, transactional, and environmental data in a myriad of formats (numerical, image, audio, and others) are available at ever greater speeds, propelling innovations such as artificial intelligence-aided automation. Such automation in the home, office, and classroom also challenges long-standing expectations about privacy, security, and the veracity of the underlying data

Although it is expected that technology, computation, and big data will have positive impacts on the human condition, the world still faces persistent societal, cultural, and economic challenges, e.g., hunger, poverty, our dynamic Earth, and energy security. Moreover, we must continue work to ensure equitable access to precisely those technologies that give rise to these changes. Equally important is the challenge of ensuring equitable access to high quality education, which leads directly to questions important to the NSF: How do these new technologies change the way we learn and do science, math, and engineering? How do we navigate such change? How do we use technological innovations to ensure full participation of all groups in the STEM workforce?

To answer these questions related to learning, researchers will need to cross disciplines, define the potential impact of technologies, and develop new technical competencies. Furthermore, all scientific and technical workers will need new knowledge and skills so they can perform new tasks or perform current tasks with new tools.

This DCL seeks proposals related to harnessing the data revolution and the future of work at the human-technology frontier. This DCL encourages educational research and development proposals that are original, creative, and transformative, and that can help the nation educate the STEM workforce of the future, in contexts of:

All proposals responding to this DCL should address education issues related to FW-HTF, HDR, or to both. Proposals can also include activities that are relevant to other NSF Big Ideas.

This DCL will support three categories of proposals:

  1. Proposals focused on educational transformation: These proposals will leverage technology, computation and/or big data to develop, implement, and analyze educational interventions designed to prepare a diverse workforce, researchers, and innovators of the future. Proposals that explore how students learn to integrate knowledge across disciplines to solve complex problems fall into this category.
  2. Proposals focused on the science of teaching and learning: These proposals will leverage technology, computation and/or big data to develop, implement, and analyze new tools for assessing and evaluating convergent education strategies that aim to promote student learning at all levels.
  3. Planning grants, Research Coordination Networks, Conference Proposals: These proposals will create communities of STEM educators to address convergent curriculum and pedagogical challenges across disciplinary boundaries brought about by the human-technology frontier, the data revolution, or both.

This DCL emphasizes proposals that cross departmental and disciplinary boundaries. This DCL encourages original proposals for curricular innovations that cross boundaries, so that students gain the tools and knowledge needed to thrive in the technology revolution and become the creators/innovators of the future.

This DCL encourages proposals that reflect a coordinated effort from interdisciplinary research teams of at least two PIs from different disciplines. Such teams can make learning a convergence experience and accomplish learning goals that are not otherwise achievable. Examples include, but are not limited to: computational skills in an application area such as genetics; automation and sensing in natural and manufactured environments; calculus, modeling and simulation of physical contexts and objects; art, psychology, conceptual design and mechanical design for better product development; or sociology and earth sciences to address adaptation to our environment. Proposals that use convergence approaches to instill the development of needed non-technical abilities for the 21st century are also appropriate, including ones that focus on development of teamwork, higher level thinking, problem solving, creativity, adaptability, and the ability to communicate across disciplinary boundaries.

In summary, competitive proposals will propose an approach that reflects convergence in education and human resource development, using technology and data beyond disciplinary boundaries to create student outcomes that will benefit society.

Responding to the STEM Education for the Future DCL
Proposals responding to this DCL should be submitted by the due date of the applicable funding opportunities listed below.

To determine whether a research topic is within the scope of this DCL, principal investigators are strongly encouraged to contact the cognizant NSF Program Officer(s) of the participating program(s) to which they plan to submit their proposal. These programs include:

Program Program Link and
Solicitation
Due dates
EHR Accelerating Discovery:
Educating the Future STEM
Workforce (AD)
AD (PD 18-1998) April 2, 2018 - January 16, 2019
DUE Improving Undergraduate
STEM Education: Education and
Human Resources [i]
IUSE: EHR (NSF 17-590) Accepted anytime (Exploration and
Development Tier) Dec 11, 2018 (Development and
Implementation Tier)
DUE Advanced Technological
Education [ii]
ATE (NSF 17-568) October 4, 2018
DGE Innovations in Graduate
Education [iii]
IGE (NSF 17-585) September 27, 2018
HRD Historically Black Colleges
and Universities -
Undergraduate Program [iv]
HBCU-UP (NSF 18-522) See solicitation
HRD Tribal Colleges and
Universities Program [v]
TCUP (NSF 16-531) See solicitation
HRD/DUE Improving Undergraduate
STEM Education: Hispanic-
Serving Institutions (HSI Program) [vi]
HSI See program page
DRL Innovative Technology
Experiences for Students and
Teachers [vii]
ITEST (NSF 17-565)

 

August 8, 2018
DRL Advancing Informal STEM
Learning[viii]
AISL (NSF 17-573) November 7, 2018
BIO/EHR Research Coordination
Networks in Undergraduate
Biology Education [ix]
RCN-UBE (NSF 18-510) January 22, 2019
EEC Research in the Formation
of Engineers[x]
RFE (NSF 17-514) February 28, 2019
GEO Ocean Education Program [xi] OCE Contact Elizabeth Rom,
jmeriwet [at] nsf [dot] gov
GEO Polar Special Initiatives
Program [xii]

OPP

Contact Elizabeth Rom,
jmeriwet [at] nsf [dot] gov

To ensure proper consideration, principal investigators must indicate the relevant Big Idea(s) in the title, the overview statement of the Project Summary, and the Project Description. For example, the title of a proposal about the Future of Work at the Human Technology Frontier and Rules of Life should begin with "FW-HTF/RoL" and a proposal addressing educational challenges relevant to Harnessing the Data Revolution should precede its title with "HDR." Table 1 lists the NSF Big Ideas and designated acronyms. In summary, proposals responding to this DCL:

  1. Should focus on education and/or workforce development in the context of the Future of Work at the Human-Technology Frontier, Harnessing the Data Revolution, or both.
  2. May intersect with additional Big Ideas for Future NSF Investment.
  3. Should include PIs from different disciplines.
  4. Must be submitted to one of the programs listed in this DCL.
  5. Must comply with the relevant program/solicitation-specific requirements.
  6. Must present novel ideas or approaches (high risk/high reward proposals are encouraged).
  7. Must have titles that adhere to the naming convention noted above.

 

Table 1. NSF's Six Research Big Ideas for Future NSF Investment

The Future of Work at the Human-Technology Frontier FW-HTF
Harnessing the Data Revolution HDR
Understanding the Rules of Life: Predicting Phenotype RoL
Navigating the New Arctic NNA
Windows on the Universe: The Era of Multi-Messenger Astrophysics MMA
The Quantum Leap: Leading the Next Quantum Revolution QL

Sincerely,

William (Jim) Lewis
Assistant Director (Acting)
Directorate for Education & Human Resources

Joanne S. Tornow
Assistant Director (Acting)
Directorate for Biological Sciences

Dawn M. Tilbury
Assistant Director
Directorate for Engineering

William E. Easterling
Assistant Director
Directorate for Geosciences

___________________________________________

 

[i]The IUSE: EHR program supports projects that have the potential to improve student learning in STEM through development of new curricular materials and methods of instruction, and development of new assessment tools to measure student learning in science and engineering classrooms.

[ii]The Advanced Technological Education (ATE) program focuses on the education of technicians for the high-technology fields that drive our nation's economy. The program involves partnerships between academic institutions and industry to promote improvement in the education of science and engineering technicians at the undergraduate and secondary school levels. The ATE program supports curriculum development; professional development of college faculty and secondary school teachers; career pathways; and other activities.

[iii]The IGE program is designed to encourage the development and implementation of bold, new, and potentially transformative approaches to STEM graduate education and training. IGE projects pilot, test, and validate novel approaches and generate the knowledge required to add to our understanding of graduate student learning, thereby allowing others to adapt/adopt successful, evidence-based approaches.

[iv]HBCU-UP is committed to enhancing the quality of undergraduate STEM education and research at Historically Black Colleges and Universities (HBCUs) as a means to broaden participation in the nation's STEM workforce. The HRD HBCU-UP tracks realize this purpose by providing awards to develop, implement, and study innovative approaches for making dramatic improvements in the preparation and success of HBCU undergraduate students so that they may participate successfully in graduate programs and/or careers in science, technology, engineering, and mathematics (STEM) disciplines.

[v]The Tribal Colleges and Universities Program (TCUP) provides awards to Tribal Colleges and Universities, Alaska Native-serving institutions, and Native Hawaiian-serving institutions to promote high quality science (including sociology, psychology, anthropology, economics, statistics, and other social and behavioral sciences as well as natural sciences and education disciplines), technology, engineering, and mathematics (STEM) education, research, and outreach. Support is available to TCUP-eligible institutions.

[vi]The HSI Program seeks to enhance the quality of undergraduate STEM education at HSIs and to increase retention and graduation rates of undergraduate students pursuing degrees in STEM fields at HSIs. In addition, the HSI Program seeks to build capacity at HSIs that typically do not receive high levels of NSF grant funding.

[vii]ITEST is a research and development program that supports projects to promote PreK-12 student interests and capacities to participate in the STEM and information and communications technology (ICT) workforce of the future

[vii]The AISL program seeks to advance new approaches to and evidence-based understanding of the design and development of STEM learning opportunities for the public in informal environments; provide multiple pathways for broadening access to and engagement in STEM learning experiences; advance innovative research on and assessment of STEM learning in informal environments; and engage the public of all ages in learning STEM in informal environments.

[ix]The goal of the RCN program is to advance a field or create new directions in research or education by supporting groups of investigators to communicate and coordinate their research, training, and educational activities across disciplinary, organizational, geographic, and international boundaries. The RCN-UBE program originated as a unique RCN track to "catalyze positive changes in biology undergraduate education" (NSF 08-035) and is now supported by the collaborative efforts of the Directorate for Biological Sciences (BIO) and the Directorate for Education and Human Resources (EHR). It has been responsive to the national movement to revolutionize undergraduate learning and teaching in the biological sciences. RCN-UBE accepts workshop proposals, incubator proposals, and full RCN proposals in undergraduate biology education.

[x]The RFE program advances research about the underlying processes and mechanisms involved in the formation of engineers by deepening our fundamental understanding of how professional formation is or can be accomplished.

[xi]The OCE Education program supports efforts to integrate ocean research and education. In particular, the program is interested in receiving proposals related to the Ocean Observatories Initiative (OOI).

[xii]Polar Special Initiatives Program welcomes proposals related to the training of students with "Big Data" tools focusing on polar regions' satellite imagery, digital elevation maps, "3D virtual" ice sheets dynamics and/or proposals related to Navigating the New Arctic.

Critical Techniques, Technologies and Methodologies for Advancing Foundations and Applications of Big Data Sciences and Engineering (BIGDATA)

Wednesday, February 21, 2018

Program Solicitation: NSF 18-539

Submission Window Date(s) (due by 5 p.m. submitter's local time):

     May 07, 2018 - May 14, 2018

 

SUMMARY OF PROGRAM REQUIREMENTS

General Information

Synopsis of Program:

The BIGDATA program seeks novel approaches in computer science, statistics, computational science, and mathematics leading towards the further development of the interdisciplinary field of data science. The program also seeks innovative applications in domain science, including social and behavioral sciences, education, physical sciences, and engineering, where data science and the availability of big data are creating new opportunities for research and insights not previously possible.

The solicitation invites two categories of proposals:

  • Foundations (BIGDATA: F): those developing or studying fundamental theories, techniques, methodologies, and technologies of broad applicability to big data problems, motivated by specific data challenges and requirements; and
  • Innovative Applications (BIGDATA: IA): those engaged in translational activities that employ new big data techniques, methodologies, and technologies to address and solve problems in specific application domains. Projects in this category must be collaborative, involving researchers from domain disciplines and one or more methodological disciplines, e.g., computer science, statistics, mathematics, simulation and modeling, etc.

Proposals are expected to be well motivated by specific big data problems in one or more science and engineering research domains. All proposals are expected to clearly articulate the big data aspect(s) that motivate the research. Innovative Applications proposals must provide clear examples of the impacts of the big data techniques, technologies and methodologies on applications in one or more domains.

In FY 2018, the BIGDATA program continues the cloud option that was introduced in FY 2017, in partnership with Amazon Web Services (AWS), Google Cloud, and Microsoft Azure (see Use of Cloud Resources, at the end of Section II, Program Description).

Before preparing a proposal in response to this BIGDATA solicitation, applicants are strongly urged to review other related programs and solicitations and contact the respective NSF program officers to identify whether those solicitations are more appropriate. In particular:

 

Award Information

Anticipated Type of Award:

Standard Grant or Continuing Grant or Cooperative Agreement

Estimated Number of Awards: 25 to 33

About 25-33 projects will be funded, subject to availability of funds.

Anticipated Funding Amount: $24,000,000

Up to $24,000,000 will be invested by NSF in proposals submitted to this solicitation, subject to the availability of funds. Additional cloud credits/resources will be provided by AWS, Google, and Microsoft.

Projects will typically receive NSF funding in the range of $200,000 to a maximum of $500,000 per year, for 3 to 4 years of support. The minimum award size will be $600,000 of total NSF funding, reflecting the minimum expected level of effort for BIGDATA projects. The maximum award size will be $2,000,000 of total NSF funding. BIGDATA projects are expected to be multidisciplinary in nature and include significant student involvement. Any allocation of cloud credits/resources from AWS, Google or Microsoft will be in addition to the NSF funding. If additional cloud providers join the program, resources/credits from those providers will be available under the same terms and conditions as described in this solicitation.

Eligibility Information

Who May Submit Proposals:

The categories of proposers eligible to submit proposals to the National Science Foundation are identified in the NSF Proposal & Award Policies & Procedures Guide (PAPPG), Chapter I.E.

Who May Serve as PI:

There are no restrictions or limits.

Limit on Number of Proposals per Organization:

There are no restrictions or limits.

Limit on Number of Proposals per PI or Co-PI: 1

An individual may participate as Principal Investigator (PI), co-PI, Senior Personnel, consultant, or any other role in no more than one proposal, or related subaward, submitted in response to this solicitation.

In the event that an individual exceeds this limit, any proposal submitted to this solicitation with this individual listed as a PI, co-PI, senior personnel, consultant or any other role after the first proposal is received at NSF will be returned without review. No exceptions will be made.

Proposals submitted in response to this solicitation may not duplicate or be substantially similar to other proposals concurrently under consideration by NSF.

Proposal Preparation and Submission Instructions

A. Proposal Preparation Instructions

  • Letters of Intent: Not required
  • Preliminary Proposal Submission: Not required
  • Full Proposals:

B. Budgetary Information

  • Cost Sharing Requirements:

    Inclusion of voluntary committed cost sharing is prohibited.

  • Indirect Cost (F&A) Limitations:

    Not Applicable

  • Other Budgetary Limitations:

    Not Applicable

C. Due Dates

  • Submission Window Date(s) (due by 5 p.m. submitter's local time):

         May 07, 2018 - May 14, 2018

Proposal Review Information Criteria

Merit Review Criteria:

National Science Board approved criteria. Additional merit review considerations apply. Please see the full text of this solicitation for further information.

Award Administration Information

Award Conditions:

Additional award conditions apply. Please see the full text of this solicitation for further information.

Reporting Requirements:

Standard NSF reporting requirements apply.

 

TABLE OF CONTENTS

  1. Introduction
     
  2. Program Description
     
  3. Award Information
     
  4. Eligibility Information
     
  5. Proposal Preparation and Submission Instructions
    1. Proposal Preparation Instructions
    2. Budgetary Information
    3. Due Dates
    4. FastLane/Grants.gov Requirements
       
  6. NSF Proposal Processing and Review Procedures
    1. Merit Review Principles and Criteria
    2. Review and Selection Process
       
  7. Award Administration Information
    1. Notification of the Award
    2. Award Conditions
    3. Reporting Requirements
       
  8. Agency Contacts
     
  9. Other Information

Training-based Workforce Development for Advanced Cyberinfrastructure (CyberTraining)

Tuesday, November 8, 2016

NSF 17-507

Synopsis of Program:

The overarching goal of this program is to prepare, nurture and grow the national scientific workforce for creating, utilizing, and supporting advanced cyberinfrastructure (CI) that enables cutting-edge science and engineering and contributes to the Nation's overall economic competitiveness and security. For the purpose of this solicitation, advanced CI is broadly defined as the resources, tools, and services for advanced computation, data handling, networking and security. The need for such workforce development programs are highlighted by the (i) National Strategic Computing Initiative announced in 2015 (NSCI), which is co-led by NSF and aims to advance the high-performance computing ecosystem and develop workforce essential for scientific discovery; (ii) 2016 National Academies' report on Future Directions for NSF Advanced Computing Infrastructure to Support U.S. Science and Engineering in 2017-2020; and (iii) Federal Big Data Research and Development Strategic Plan, which seeks to expand the community of data-empowered experts across all domains.

This solicitation calls for developing innovative, scalable training programs to address the emerging needs and unresolved bottlenecks in scientific and engineering workforce development of targeted, multidisciplinary communities, at the postsecondary level and beyond, leading to transformative changes in the state of workforce preparedness for advanced CI in the short and long terms. A primary goal is to broaden CI access and adoption by (i) increasing or deepening accessibility of methods and resources of advanced CI and of computational and data science and engineering by a wide range of institutions and scientific communities with lower levels of CI adoption to date; and (ii) harnessing the capabilities of larger segments of diverse underrepresented groups. Proposals from and in partnership with the aforementioned communities are especially encouraged. For student training, a key concern is not to increase the time to degree; hence the emphasis shall be on out-of-class, informal training.

Prospective principal investigators (PIs) are encouraged to engage all relevant stakeholders by forging alliances, and forming backbones for collective impact, which is particularly necessary in order to address unresolved bottlenecks (John Kania & Mark Kramer, “Collective Impact,” Stanford Social Innovation Review, Winter 2011). PIs may seek public-private partnerships for relevance, enrichment, pursuit of national and international dimensions, and sustainability. All projects shall include training activities. In the short term, the projects shall result in innovative, scalable, informal training models and pilot activities, complementing and leveraging the state of art in curricular offerings, material, and best practices in academia and elsewhere. In the long term, the projects should contribute to the larger goals of an educational ecosystem enabling “Computational and Data Science for All,” with an understanding of computation as the third pillar (President’s Information Technology Advisory Committee Report, Computational Science: Ensuring America’s Competitiveness, 2005) and data-driven science as the fourth pillar of the scientific discovery process (2016 National Academies report), in addition to the traditional first and second pillars, respectively, of theory and experimentation. Furthermore, in the long term, projects should contribute toward an ubiquitous educational cloud infrastructure for online, dynamic, personalized lessons and certifications in CI and other multidisciplinary areas (Continuous Collaborative Computational Cloud in Higher Education, Chapter 1, NSF Advisory Committee for Cyberinfrastructure Task Force on Cyberlearning and Workforce Development Report, 2011).

There are three tracks for submissions:

(i) CI Professionals (CIP): aimed at the training and career pathway development of research cyberinfrastructure and professional staff who develop, deploy, manage, and support effective use of advanced CI for research;

(ii) Domain science and engineering (DSE): aimed primarily at the communities of CI Contributors and sophisticated CI Users, and aligned with the research and education priorities of the participating domain directorates; and

(iii) Computational and data science literacy (CDL): aimed at the CI User community at the undergraduate level.

The communities of CI Professionals, Contributors, and Users supported by the above three tracks are defined in Section I - Introduction.

Each CyberTraining award shall range from $300,000 to $500,000 per award and shall be up to 3 years in duration. Based on the community response and needs, the CyberTraining solicitation may be expanded to accommodate larger projects in the future.

Programmatic Areas of Interest

The CyberTraining program includes all divisions within the Directorates of Engineering (ENG), Geosciences (GEO), and Mathematical and Physical Sciences (MPS), as well as the Divisions of Advanced Cyberinfrastructure (ACI) and Computing and Communication Foundation (CCF) in the Directorate for Computer and Information Science and Engineering (CISE), and the Division of Graduate Education (DGE) in the Directorate for Education and Human Resources (EHR). The appropriate contact for the CyberTraining program in any directorate/division is the Cognizant Program Officer (PO) for the respective directorate/division listed.

All projects must advance cyberinfrastructure training and education goals as described in the full text of this solicitation, in addition to addressing specific domain needs. Not all directorates/divisions are participating at the same level and some have specific research and education priorities as described below. Prospective PIs are strongly encouraged to contact the Cognizant Program Officers in CISE/ACI and in the participating directorate/division(s) relevant to the proposal to ascertain whether the focus and budget of the proposed activities are appropriate for this solicitation. Such consultations should be completed at least one month in advance of the submission deadline. PIs should include the names of the Cognizant Program Officers consulted in their Project Summary as described in Section V(A) - Proposal Preparation Instructions.

The Directorate for Education and Human Resources (EHR) supports the development of a diverse and well-prepared workforce of scientists, technicians, engineers, mathematicians and educators. EHR is interested in engaging the CI and education research communities to use advanced cyberinfrastructure and other approaches to analyze, visualize, and harness data to better understand issues of workforce development in science and engineering. Topics of particular interest include preparation of the workforce in areas of data security and privacy in connection with EHR’s investment in the CyberCorps(R): Scholarships for Service (SFS) and Secure and Trustworthy Cyberspace (SaTC) programs, as well as the other aspects associated with preparation of the technical workforce for proficiency in using advanced cyberinfrastructure, which is supported by EHR’s Advanced Technological Education (ATE) program. In this context, EHR is interested in supporting: (a) innovations in formal and informal educational settings that lead to the broadest participation by all learners; (b) advances in pedagogical curricular design, and introduction of research and internship opportunities; and (c) assessments of training, learning and program evaluation. Prospective PIs may wish to separately submit proposals to the EHR Core Research (ECR) program, which welcomes proposals seeking to advance basic research on the learning of challenging CI content in formal and informal settings, exploring the evaluation of models for broadening participation such as collective impact, and studying the development of the STEM professional workforce.

The Directorate for Engineering (ENG) is interested in training students, postdocs and educators in the areas of reusable, sustainable high-performance computing software tools, models and algorithms; Big Data management and analytics tools to advance research across the domain areas of ENG; fluidic processes and materials; catalysis and biocatalysis; and those supported by the Innovations at the Nexus of Food, Energy, and Water Systems (INFEWS), Understanding the Brain (UtB), and Nanoscale Science and Engineering (NSE) programs. Proposals are also invited to address training and education needs in advanced multi-scale, multi-physics computational models and simulations for engineering for natural hazards mitigation suitable for community sharing on the Natural Hazards Engineering Research Infrastructure (NHERI) cyberinfrastructure (http://designsafe-ci.org/). In support of the broader goals of this solicitation, proposals for workshops and summer institutes are encouraged; lectures, problem sessions, and hands-on activities are expected to achieve the intended impact.

The Directorate for Mathematical and Physical Sciences (MPS) is interested in supporting workshops and summer schools focused on training students and postdocs in computational methods on advanced computing architectures. High-performance computing and data analytics methods are to be introduced in the context of specific scientific applications relevant to the MPS communities. Lectures must be accompanied by problem sessions and hands-on activities on the actual machines. Online sharing of workshop materials and recorded presentations on dedicated websites is strongly encouraged.

The Directorate of Geosciences (GEO), and the Divisions of Advanced Cyberinfrastructure (ACI) and Computing and Communication Foundation (CCF) in the Directorate for Computer and Information Science and Engineering (CISE) are not highlighting specific areas in the context of this solicitation. Rather, they welcome proposals that broadly enhance the communities of CI Professionals, Contributors, and Users in consultation with the Cognizant POs.

Investments through this solicitation at the undergraduate and graduate levels complement NSF’s Improving Undergraduate STEM Education (IUSE) and graduate education strategic frameworks, respectively. IUSE is NSF's comprehensive, Foundation-wide framework for an integrated vision of the agency's investments in undergraduate science, technology, engineering, and mathematics (STEM) education. Similarly, NSF has recently published a Strategic Framework for Investments in Graduate Education (https://www.nsf.gov/pubs/2016/nsf16074/nsf16074.pdf).

Prospective PIs contemplating submissions that primarily target communities relevant to those directorates/divisions that are not participating in this solicitation are directed to instead explore the education and workforce development programs of the respective directorates/divisions.