Grant List
Represents Grant table in the DB
GET /v1/grants?page%5Bnumber%5D=2&sort=end_date
{ "links": { "first": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1&sort=end_date", "last": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1392&sort=end_date", "next": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=3&sort=end_date", "prev": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1&sort=end_date" }, "data": [ { "type": "Grant", "id": "14848", "attributes": { "award_id": "2406488", "title": "Implementation Project: Leveraging Innovation and Discovery for STEM Success (LIDSS)", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Directorate for STEM Education (EDU)", "Hist Black Colleges and Univ" ], "program_reference_codes": [], "program_officials": [ { "id": 27246, "first_name": "Alfred", "last_name": "Hall", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2024-07-15", "end_date": null, "award_amount": 3000000, "principal_investigator": { "id": 31528, "first_name": "Connie", "last_name": "Walton", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [ { "id": 31527, "first_name": "Stacey", "last_name": "Duhon", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 2502, "ror": "https://ror.org/05mnb6484", "name": "Grambling State University", "address": "", "city": "", "state": "LA", "zip": "", "country": "United States", "approved": true }, "abstract": "The Historically Black Colleges and Universities - Undergraduate Program (HBCU-UP) provides support to strengthen STEM undergraduate education and research at HBCUs. This Implementation Project: Leveraging Innovation and Discovery for STEM Success (LIDSS) is a comprehensive effort at Grambling State University to prepare highly competitive STEM graduates to meet the challenges of an ever-changing world. Discovery and Innovation are the core of the design for each strategic activity. This project aligns with the goals of HBCU-UP in its work to foster STEM student success via its support of faculty research experiences, student support programs, and outreach initiatives for K-12 students and teachers.<br/><br/>The overarching goal of this project is to enhance the ability of Grambling State University to train highly prepared STEM majors to meet workforce needs, while reversing the effects that the pandemic has had on education at all levels. The components of this project were identified using a challenge-based learning approach. STEM faculty and students identified the problems and provided possible solutions. The overall premise is STEM education must not remain static but constantly evolve to meet a changing world. The model used to design each component of this project has discovery and innovation as the core for STEM Learning. The LIDSS project aims to improve the recruitment, retention and graduation of STEM students. A priority will be given to the recruitment of veterans as STEM majors. A STEM Entrepreneurship Academy and a Makers Space will support faculty being able to integrate entrepreneurship within curricula to further nurture the creativity of STEM majors. A Student Success Initiative will be established that will create a judgement free zone where students can enhance skills with assistance from faculty/student leader teams. This project aims to establish partnerships with research intensive institutions to expand the research capacity of STEM faculty through collaboration and mentoring opportunities. The results of this project should be of great interest to educators who also face challenges related to recruiting, retaining and graduating STEM students who are prepared to be innovative leaders. A Biennial Symposium that will focus on the use of innovative educational practices to promote STEM learning will be hosted on campus. Data collected in this project, including the symposia, will advance the knowledge of best practices that will lead to improved STEM programs that are nimble and able to utilize innovative strategies to respond to ever changing needs.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "14081", "attributes": { "award_id": "2103191", "title": "PostDoctoral Research Fellowship", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Mathematical and Physical Sciences (MPS)", "Workforce (MSPRF) MathSciPDFel" ], "program_reference_codes": [], "program_officials": [ { "id": 2352, "first_name": "Stefaan De", "last_name": "Winter", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2021-09-01", "end_date": null, "award_amount": 150000, "principal_investigator": { "id": 30602, "first_name": "Jacob", "last_name": "Russell-Madonia", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 2408, "ror": "", "name": "Russell-Madonia, Jacob", "address": "", "city": "", "state": "TX", "zip": "", "country": "United States", "approved": true }, "abstract": "This award is made as part of the FY 2021 Mathematical Sciences Postdoctoral Research Fellowships Program. Each of the fellowships supports a research and training project at a host institution in the mathematical sciences, including applications to other disciplines, under the mentorship of a sponsoring scientist. <br/><br/>The title of the project for this fellowship to Jacob Russell-Madonia is \"The mapping class group via hierarchical hyperbolicity\". The host institution for the fellowship is Rice University, and the sponsoring scientist is Christopher Leininger.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "12800", "attributes": { "award_id": "2302813", "title": "Collaborative Research: Adaptable Game-based, Interactive Learning Environments for STEM Education (AGILE STEM)", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Computer and Information Science and Engineering (CISE)", "Cyberlearn & Future Learn Tech" ], "program_reference_codes": [], "program_officials": [ { "id": 1414, "first_name": "Soo-Siang", "last_name": "Lim", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2023-09-15", "end_date": null, "award_amount": 350000, "principal_investigator": { "id": 28719, "first_name": "Daniell", "last_name": "DiFrancesca", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [ { "id": 28719, "first_name": "Daniell", "last_name": "DiFrancesca", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 219, "ror": "", "name": "Pennsylvania State Univ University Park", "address": "", "city": "", "state": "PA", "zip": "", "country": "United States", "approved": true }, "abstract": "Learners of all ages are expected to be prepared to interact with emerging and technology-driven work environments. In addition, the growing reliance on online learning and its unprecedented and unexpected acceleration due to the COVID-19 pandemic are expected to change the education landscape forever. Thus, there is a need to grow the development of digital platforms for teaching and learning. Emerging technologies such as machine learning and high fidelity simulated environments have the potential to create customized and adaptable learning environments to support STEM learning outcomes. This project serves the national interest by advancing the knowledge about designing and creating adaptable game-based, interactive learning environments for STEM. The inclusion of underrepresented minority and female learners in the design stages of these learning environments, their portability, as well as the capability of these environments to be customized and adaptive have the potential to enhance education equality, engagement, and learning outcomes, and broaden their usability to several STEM domains. Moreover, the narratives and simulation models are inspired by real-world systems. Therefore, the learning environments are expected to enhance the learner’s understanding of complex system concepts that are challenging to understand using traditional teaching approaches and will help build the much-needed skills for the U.S. future STEM workforce. The proposed emerging technologies do not necessarily need access to specialized equipment, which eliminates barriers to scalability and border implementation and use. <br/><br/>The primary goals of this project are to automatically customize and adapt three-dimensional (3D) simulated game-based learning environments to improve engagement, and provide a deeper understanding of their design, development, and deployment, impact on learning and self-regulated learning (SRL) skills, and knowledge transferability from the learning environments to real-life applications. The project addresses the lack of scientific evidence and/or work in the following thrust areas: 1) the potential of reducing the barriers to content generation of 3D simulated game-based learning environments using emerging and advanced machine-learning methods; 2) creating customized content and adaptive 3D simulated game-based learning environments that improve and maintain learners motivation and engagement, enhance learning via instructional assistive content scaffolding, and increase knowledge transferability from game to real-life applications; 3) assessing the effectiveness of the learning environments for all learner groups in online and residential settings; and 4) exploring how learner decision-making and behavior data in the simulated game-based learning environments, and eye-tracking, facial expressions, bio-signals, and usage data, enhance knowledge about the relationships between decision-making/usage and SRL skills development.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "14337", "attributes": { "award_id": "2100493", "title": "Collaborative Research: Two-way Coupled Fluid/Particulate Transport in Fractured Media - Bridging the Scales from Microscopic Origins to Macroscopic Networks", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Geosciences (GEO)", "XC-Crosscutting Activities Pro" ], "program_reference_codes": [], "program_officials": [ { "id": 7676, "first_name": "Justin", "last_name": "Lawrence", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2021-08-01", "end_date": null, "award_amount": 348253, "principal_investigator": { "id": 30930, "first_name": "Peter", "last_name": "Kang", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [ { "id": 30929, "first_name": "Peter K", "last_name": "Kang", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 227, "ror": "", "name": "University of Minnesota-Twin Cities", "address": "", "city": "", "state": "MN", "zip": "", "country": "United States", "approved": true }, "abstract": "This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2). <br/><br/>The contamination of hydrologic systems such as oceans, rivers, lakes, and aquifers with particulates has emerged as one of the most urgent environmental issues of today. Recent field data suggests a clear presence of solid contaminants, such as microplastics and pathogens, in fractured aquifers which make up a significant portion of the world's drinking water supply and in other subsurface media. Understanding and predicting particulate transport in subsurface fracture flows poses both fundamental and practical challenges, as it requires a quantitative understanding of particle/fluid transport across many length scales that range from individual particles to a network of fractures. To overcome these challenges, our research will uncover the physical origin of the coupled particle/fluid transport and its effects on the large-scale particle transport, by combining laboratory experiments, theoretical modeling, and computations both at the particle scale and the network scale. The resultant particulate transport models will greatly improve our predictive capabilities for wide-ranging subsurface processes, which include contaminant transport, geological nuclear waste disposal, hydraulic fracturing, and enhanced geothermal systems. In addition, this project will provide training opportunities for graduate students and post-docs from diverse backgrounds, as well as collaborative educational activities for high school summer interns who will gain project-based experience as part of interdisciplinary teams.<br/><br/>The investigators will explore and quantify the effects of two-way coupled particle/fluid motion on particulate transport in fractured media, across a wide range of scales. Towards this end, they will combine detailed laboratory experiments as well as particle-resolving simulations at the single-fracture scale, with novel upscaling approaches to the fracture network scale. Traditional particulate transport models in subsurface systems treat particles as passive scalars that do not affect the surrounding flow field, although their preliminary experiments demonstrate that particles can actively modify the fluid flow and even trigger hydrodynamic instabilities. By overcoming this deficiency of traditional models, this research project will provide the next generation of large-scale subsurface particulate transport models. Specifically, they will address three research questions: 1) the microscopic origins of the two-way coupling; 2) the hydrodynamic instabilities and dispersion in a single fracture; 3) the effects of two-way coupling on network-scale particulate transport. They will conduct systematic laboratory experiments to characterize particle-scale instabilities and collective particle behavior at the single fracture scale, which will be verified and supplemented by particle-resolving Navier-Stokes simulations of concentrated suspensions in rough fractures. The resulting data will provide effective dispersivities and stochastic rules of particulate motion that capture the two-way coupling effects on particulate transport. These results from the single fracture study will be incorporated into fracture network models, in order to assess the influence of two-way coupling on particulate transport at the network scale and to develop upscaled particulate transport models.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "13824", "attributes": { "award_id": "2111403", "title": "Collaborative Research: Integrating Perspective-taking and Systems Thinking for Complex Problem-Solving", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Directorate for STEM Education (EDU)", "IUSE" ], "program_reference_codes": [], "program_officials": [ { "id": 1869, "first_name": "Thomas", "last_name": "Kim", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2021-10-15", "end_date": null, "award_amount": 372888, "principal_investigator": { "id": 30167, "first_name": "Rebecca", "last_name": "Jordan", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [ { "id": 30167, "first_name": "Rebecca", "last_name": "Jordan", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 521, "ror": "https://ror.org/05hs6h993", "name": "Michigan State University", "address": "", "city": "", "state": "MI", "zip": "", "country": "United States", "approved": true }, "abstract": "This project aims to serve the national interest by using computer modeling to present multiple perspectives, helping students to improve systems thinking and complex socio-technical problem-solving. The topics with which STEM fields grapple are often not merely scientific problems; they are also at times ideologically and emotionally charged issues. Such contemporary “socio-scientific” issues affect multiple stakeholders in different ways and have real and diverse consequences, both economic and societal. Understanding and responding to these socio-scientific issues, such as genetically modified crops, vaccine development/deployment and climate change mitigation, requires that individuals not only understand scientific content and how systems work, but also how these systems look from different vantage points. The goal of this project is to develop and assess new teaching strategies to improve understanding and decision-making related to such complex social and environmental problems. This project will build on research from previous studies to develop the state-of-the-art undergraduate instruction strategies. The software, curricular tools, and case studies being designed will be used by college instructors across the United States to promote perspective-taking and problem-solving. Formally engaging students in this type of thinking is essential to the training of America’s future workforce. <br/><br/>Specifically, students will engage with a series of case studies on complex socio-scientific issues, and use the MentalModeler (www.mentalmodeler.org) software to map out the system from the perspectives of different stakeholders. We believe this approach will promote systems thinking, model-based reasoning, perspective taking, and problem-solving ability in the undergraduate classroom. We intend to test the hypothesis that integrating novel perspective taking and systems modeling across different undergraduate courses: 1) helps students overcome some of the cognitive and motivational obstacles elicited by controversial socio-scientific topics, 2) leads to a deeper and more accurate understanding of the system itself, and 3) helps learners create and support arguments regarding the effect of interventions on system-level outcomes. The NSF IUSE: EHR Program supports research and development projects to improve the effectiveness of STEM education for all students. Through the Engaged Student Learning track, the program supports the creation, exploration, and implementation of promising practices and tools.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "13057", "attributes": { "award_id": "2150405", "title": "REU Site: Undergraduate Research in Basic and Applied Science of Psychology", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Computer and Information Science and Engineering (CISE)", "RSCH EXPER FOR UNDERGRAD SITES" ], "program_reference_codes": [], "program_officials": [ { "id": 1351, "first_name": "Josie Welkom", "last_name": "Miranda", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2022-06-01", "end_date": null, "award_amount": 347895, "principal_investigator": null, "other_investigators": [ { "id": 29062, "first_name": "Charles A", "last_name": "Scherbaum", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 2223, "ror": "", "name": "CUNY Baruch College", "address": "", "city": "", "state": "NY", "zip": "", "country": "United States", "approved": true }, "abstract": "This project is funded from the Research Experiences for Undergraduates (REU) Sites program in the Directorate for Social, Behavioral and Economic Sciences (SBE). It has both scientific and societal benefits in addition to integrating research and education. The REU site at Baruch College offers advanced research training in psychological science to undergraduate students who attend Baruch College, Colleges within the City University of New York, or other educational institutions in the New York metropolitan area. Baruch College and CUNY in general boast a diverse student body. Although the recruitment is open to any NSF eligible undergraduate students, this program is designed to increase the representation of minority, low-income, first-generation college students, and disabled students in scientific psychology. Specifically, the program plans to (a) identify early promising minority, disabled, and economically disadvantaged students in the New York metropolitan area, (b) prepare REU students for advanced graduate training in psychology and ultimately for careers in academic settings, (c) develop a pipeline to provide a pool of talented and diverse undergraduate students to become the research scientists of the future, and (d) increase psychological scientists exposure to cultural and minority issues in psychological research. <br/><br/>REU Students in the program conduct independent research under the supervision of their respective REU faculty member in one of the four areas of psychology (i.e., clinical, developmental, industrial/organizational, and social). Each student focuses on planning and executing studies with the intention of presenting papers at professional conferences and submitting manuscripts to peer-reviewed journals. Specifically, REU students develop research questions and hypotheses that are grounded in the literature. In order to answer these newly developed research questions and hypotheses, REU students design research protocols and plan data collection. REU students learn via hands-on experience the value of statistical analysis, use of statistical software to draw inferences about the data, and presentation skills to disseminate the findings gained in their research. Alongside with the conduct of their research projects, REU students complete a series of structured activities aimed at preparing them to apply to graduate school. These activities, such as attending professional development seminars and workshops, participating at colloquium in the field of psychology, listening to invited guest speakers from graduate program admission officers, are coordinated by the Baruch College REU program.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "13568", "attributes": { "award_id": "2144751", "title": "CAREER: Efficient, Dynamic, Robust, and On-Device Continual Deep Learning with Non-Volatile Memory based In-Memory Computing System", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Computer and Information Science and Engineering (CISE)", "Software & Hardware Foundation" ], "program_reference_codes": [], "program_officials": [ { "id": 977, "first_name": "Sankar", "last_name": "Basu", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2022-01-15", "end_date": null, "award_amount": 500000, "principal_investigator": { "id": 8714, "first_name": "Deliang", "last_name": "Fan", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 173, "ror": "", "name": "The University of Central Florida Board of Trustees", "address": "", "city": "", "state": "FL", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 147, "ror": "https://ror.org/03efmqc40", "name": "Arizona State University", "address": "", "city": "", "state": "AZ", "zip": "", "country": "United States", "approved": true }, "abstract": "This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2).<br/><br/>Over past decades, there have existed grand challenges in developing high performance and energy-efficient computing solutions for big-data processing. Meanwhile, owing to the boom in artificial intelligence (AI), especially Deep Neural Networks (DNNs), such big-data processing requires efficient, intelligent, fast, dynamic, robust, and on-device adaptive cognitive computing. However, those requirements are not sufficiently satisfied by existing computing solutions due to the well-known power wall in silicon-based semiconductor devices, the memory wall in traditional Von-Neuman computing architectures, and computation-/memory-intensive DNN computing algorithms. This project aims to foster a systematic breakthrough in developing AI-in-Memory computing systems, through collaboratively developing ahybrid in-memory computing (IMC) hardware platform integrating the benefits of emerging non-volatile resistive memory (RRAM) and Static Random Access Memory (SRAM) technologies, as well as incorporating IMC-aware deep-learning algorithm innovations. The overarching goal of this project is to design, implement, and experimentally validate a new hybrid in-memory computing system that is collaboratively optimized for energy efficiency, inference accuracy, spatiotemporal dynamics, robustness, and on-device learning, which will greatly advance AI-based big-data processing fields such as computer vision, autonomous driving, robotics, etc. The research will also be extended into an educational platform, providing a user-friendly learning framework, and will serve the educational objectives for K-12 students, undergraduate, graduate, and under-represented students.<br/><br/>This project will advance knowledge and produce scientific principles and tools for a new paradigm of AI-in-Memory computing featuring significant improvements in energy efficiency, speed, dynamics, robustness, and on-device learning capability. This cross-layer project spans from device, circuit, and architecture to DNN algorithm exploration. First, a hybrid RRAM-SRAM based in-memory computing chip will be designed, optimized, and fabricated. Second, based on this new computing platform, the on-device spatiotemporal dynamic neural network structure will be developed to provide an enhanced run-time computing profile (latency, resource allocation, working load, power budget, etc.), as well as improve the robustness of the system against hardware intrinsic and adversarial noise injection. Then, efficient on-device learning methodologies with the developed computing platform will be investigated. In the last thrust, an end-to-end DNN training, optimization, mapping, and evaluation CAD tool will be developed that integrates the developed hardware platform and algorithm innovations, for optimizing the software and hardware co-designs to achieve the user-defined multi-objectives in latency, energy efficiency, dynamics, accuracy, robustness, on-device adaption, etc.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "13056", "attributes": { "award_id": "2121416", "title": "Development and Evaluation of a Comprehensive Utility Value Intervention for General Chemistry", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Directorate for STEM Education (EDU)", "IUSE" ], "program_reference_codes": [], "program_officials": [ { "id": 8035, "first_name": "Dawn", "last_name": "Rickey", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2022-07-15", "end_date": null, "award_amount": 278389, "principal_investigator": { "id": 29061, "first_name": "Scott", "last_name": "Lewis", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 235, "ror": "https://ror.org/032db5x82", "name": "University of South Florida", "address": "", "city": "", "state": "FL", "zip": "", "country": "United States", "approved": true }, "abstract": "Many students who start college intending to major in a science, technology, engineering, or mathematics (STEM) field ultimately do not complete a degree in a STEM field. Addressing the issue of students leaving STEM majors is important because there may soon be a shortage of STEM professionals to meet the Nation’s demands. Prior research shows that some students experience a loss of motivation to pursue a STEM major particularly while taking introductory STEM courses. Learning theory suggests that motivation may be enhanced when a student sees the value of engaging with an activity due to its relevance for their future plans, referred to as its utility value. This Improving Undergraduate STEM Education (IUSE: EHR) Engaged Student Learning Level 1 project aims to serve the national interest by developing, implementing, and evaluating a comprehensive utility value intervention (UVI) for general chemistry courses. The UVI will be designed to improve students’ perceptions of the usefulness of general chemistry coursework, which is required for many STEM majors, and thus enhance students’ motivation to persist in general chemistry and STEM majors. <br/><br/>The hypothesized mechanism underlying the design of the UVI is informed by Eccles’ Expectancy Value Theory, which explains an individual’s engagement as the result of their expectations for success and subjective task value, including utility value. An expectation based on this theory is that improving students’ utility value of general chemistry will enhance students’ persistence and result in improved academic performance, as well as motivation to engage in similar courses in the future. The project team will implement the UVI in three course sections of first-semester General Chemistry and three course sections of second-semester General Chemistry at the University of South Florida. The UVI will include prompts for each student to relate general chemistry topics to their future plans, provide individualized feedback that incorporates links to chemistry-related news articles tailored to the plans each student identifies, and brief presentations on the applicability of general chemistry topics to STEM careers and everyday life applications. The intervention design will also be informed by interviews with senior undergraduate chemistry students and STEM professionals regarding the utility value of the general chemistry. The UVI will be evaluated using a quasi-experimental design that will examine intervention and comparison group students’ pre- and post-course perceived utility and course performance, as well as their STEM course enrollments one-year after the intervention. In addition, the team will conduct focus groups to provide a qualitative description of the impact of the intervention on students’ perceived utility value of chemistry. The implementation of the UVI will directly impact over 1200 students, and the dissemination plan includes professional development and support for thirty additional general chemistry instructors to incorporate UVIs into their courses. The NSF IUSE: EHR program supports research and development projects to improve the effectiveness of STEM education for all students. Through the Engaged Student Learning track, the program supports the creation, exploration, and implementation of promising practices and tools.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "13825", "attributes": { "award_id": "2121980", "title": "ADVANCE Adaptation: CSU STEPS for Gender Equity: Advancing Structures through Evidence-based Practices for Gender Equity", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Directorate for STEM Education (EDU)", "ADVANCE" ], "program_reference_codes": [], "program_officials": [ { "id": 2408, "first_name": "Chrystal", "last_name": "Smith", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2021-10-15", "end_date": null, "award_amount": 999312, "principal_investigator": { "id": 30169, "first_name": "Emily", "last_name": "Fischer", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [ { "id": 30169, "first_name": "Emily", "last_name": "Fischer", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 30170, "first_name": "Laura B Sample", "last_name": "McMeeking", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 30171, "first_name": "Meena", "last_name": "Balgopal", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 30172, "first_name": "Gregg A", "last_name": "Dean", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 323, "ror": "https://ror.org/03k1gpj17", "name": "Colorado State University", "address": "", "city": "", "state": "CO", "zip": "", "country": "United States", "approved": true }, "abstract": "Colorado State University will tackle the significant nation-wide problem of inequity among faculty members in Science, Technology, Math and Engineering (STEM) disciplines. Specifically, this project aims to improve equity in recruitment, retention and promotion, with a focus on gender equity that recognizes the other types of cultural, ethnic, physical, and economic backgrounds people have. The work thus targets improved diversity in STEM disciplines. This problem is important because more diverse workforces are more effective at solving problems, and in a more just society, university faculty composition would reflect availability of doctoral graduates without bias. This problem has not already been solved because inequities are complex and embedded into the history of US society and academia. It is not intractable, however, and through carefully executing projects, Colorado State aims to improve equity across the STEM faculty. To address inequities, the project team aims to adapt a number of evidence-based best practices to particular situations at Colorado State. The project targets four major changes. 1) A revised approach to recruiting new faculty. 2) Improved unit climates through training allies to intervene when they notice inequities. 3) Improved performance review processes with training and support for review committees. 4) Enhanced leadership through education in equity who are both empowered to and accountable for making change. The expected outcomes of the project activities are improved climate and culture for all, and improved recruitment and retention leading to greater equity and diversity in STEM units across campus.<br/><br/>The overarching goal of ADVANCE Adaptation: CSU STEPS for Gender Equity: Advancing Structures through Evidence-based Practices for Gender Equity is to transform university and unit structures and culture to improve climate and gender equity on STEM faculties, with an intersectional focus on women with identities that historically have been marginalized. The specific aims are as follows: 1) enhance recruitment, 2) improve retention through training Promotion and Tenure Committees, creating a cadre of equity-minded Allies, and collecting qualitative data to understand departures and retentions, and 3) support and train unit leaders in equity efforts. Thus, the scope of the project encompasses equity across all phases of faculty careers and on into leadership. The research methods include quantitative and qualitative approaches to evaluate success in providing participants with new skills, in improving department climate, and in retention outcomes. Expected results include an increase in equitable recruitment and retention, improved climate, and a better understanding of the specific barriers faculty face. The project aims to contribute to research literature in organizational change and equity. Outcomes and findings will be disseminated at conferences, in academic publications, and in articles and talks for broad audiences. The NSF ADVANCE program is designed to foster gender equity through a focus on the identification and elimination of organizational barriers that impede the full participation and advancement of diverse faculty in academic institutions. Organizational barriers that inhibit equity may exist in policies, processes, practices, and the organizational culture and climate. ADVANCE \"Adaptation\" awards provide support for the adaptation and adoption of evidence-based strategies to academic, non-profit institution of higher education as well as non-academic, non-profit organizations.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "13569", "attributes": { "award_id": "2134864", "title": "Terrestrial Organics since The Oligocene (TOTO): The Rains Down in Africa", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Geosciences (GEO)", "Marine Geology and Geophysics" ], "program_reference_codes": [], "program_officials": [ { "id": 29707, "first_name": "Joseph", "last_name": "Carlin", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2022-01-15", "end_date": null, "award_amount": 613617, "principal_investigator": { "id": 6732, "first_name": "Kevin", "last_name": "Uno", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [ { "id": 29727, "first_name": "Rachel L", "last_name": "Lupien", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 196, "ror": "https://ror.org/00hj8s172", "name": "Columbia University", "address": "", "city": "", "state": "NY", "zip": "", "country": "United States", "approved": true }, "abstract": "Terrestrial Organics since The Oligocene (TOTO): The Rains Down in Africa<br/><br/>Today, nearly 100 million people depend on the lands in the Sahel region, which is highly sensitive to flooding, droughts, and wildfires, putting food and other resources at risk. Africa is also rich in human evolutionary history, including early human fossil sites, evidence for multiple dispersals out of Africa, and the earliest stone tool innovations. Despite the region’s importance for understanding climate change and human evolution, there is a lack of understanding of tropical Africa over long intervals. To that end, the investigators will generate new West African records of rain, vegetation, and fire over the last 25 million years to study changes in the Sahel ecosystem, which runs east-west across Africa south of the Sahara desert, and to quantify the effects of natural cycles in Earth’s orbit and long-term changes in global and regional conditions on ecosystem change and human evolution. The investigators will convene a new African Climate Conference to facilitate knowledge sharing, networking events, and laboratory tours at Lamont to directly combat the long history of the exclusion of African researchers in Western science by forming deep, lasting collaborations.<br/><br/>The Tropics comprise half of Earth’s surface, serve as the global hydrological pump, and contain the world’s largest potential source of methane, yet there is a dearth of data and understanding of tropical climate over the Cenozoic. Tropical Africa, in particular, has been historically under-studied, despite its importance for understanding human evolution, tropical hydroclimate, and terrestrial ecosystem responses to climate change. Projections of future climate scenarios require quantification of past climatic responses to orbital forcings and boundary conditions (i.e., regional albedo, ice volume, global temperature). The investigators will generate new long-term and high-resolution precipitation, vegetation, and fire reconstructions using biomarkers preserved in a marine sediment core that capture the last 25 million years of tropical West African climate. Statistical and time series analyses will evaluate the amplitudes, periodicities, means, and relationships between hydroclimate, ecosystem, and fire proxies through time to decipher the differences in the amplitude of variability in the study windows to characterize sensitivity in the context of various boundary conditions. This project will provide crucial environmental context for the evolution of our earliest ancestors and will inform models of future terrestrial responses to global warming in this highly sensitive region.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.", "keywords": [], "approved": true } } ], "meta": { "pagination": { "page": 2, "pages": 1392, "count": 13920 } } }