(HISTORICAL) Science of Learning Centers

 
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    CFDA#

    47.041
     

    Funder Type

    Federal Government

    IT Classification

    C - Funds little to no technology

    Authority

    National Science Foundation (NSF)

    Summary

    The Science of Learning program supports potentially transformative basic research to advance the science of learning. 

    The goals of the SL Program are to develop basic theoretical insights and fundamental knowledge about learning principles, processes and constraints. Projects that are integrative and/or interdisciplinary may be especially valuable in moving basic understanding of learning forward but research with a single discipline or methodology is also appropriate if it addresses basic scientific questions in learning.  The possibility of developing connections between proposed research and specific scientific, technological, educational, and workforce challenges will be considered as valuable broader impacts, but are not necessarily central to the intellectual merit of proposed research.

    The program will support  research addressing learning in a wide range of domains at one or more levels of analysis including: molecular/cellular mechanisms; brain systems; cognitive affective, and behavioral processes; and social/cultural influences. The program supports a variety of methods including: experiments, field studies, surveys, secondary-data analyses, and modeling.

    The Science of Learning Program also accepts proposals for Workshops, EArly-concept Grants for Exploratory Research (EAGER), Rapid Response Grants (RAPID), and Supplements to existing awards.  PIs must contact the NSF program officer prior to submission of an EAGER or RAPID proposal.

     

    History of Funding

    Recent awards made through this program can be found at https://www.nsf.gov/news/news_summ.jsp?cntn_id=243658&org=NSF&from=news.

    Additional Information

    Examples of general research questions within scope of the Science of Learning program include:
    • How does learning transfer from one context to another or from one domain to another?  How is learning generalized from specific experiences?  What is the basis for robust learning that is resilient against potential interference from new experiences?  How is learning consolidated and reconsolidated from transient experience to stable memory?
    • How does the structure of the learning environment impact rate and efficacy of learning? For example, how do timing, content, learning context, developmental time point and type of engagement (e.g., active learning, group learning) impact learning processes and outcomes? 
    • How can we integrate research findings and insights across levels of analysis, relating understanding of cellular and molecular mechanisms of learning in the neurons to circuit and systems-level computations of learning in the brain, to cognitive, affective, social, and behavioral processes of learning? What concepts, tools, or questions will provide the most productive linkages of across levels of analysis?
    • How can insights from biological learners contribute and derive new theoretic perspectives to computational learning systems, neuromorphic engineering, materials science, and nanotechnology? Biological and non-biological systems and social systems can all display learning. What can integration across these different domains contribute to a general understanding of learning?

    Contacts

    Kurt A. Thoroughman

    Kurt A. Thoroughman
    4201 Wilson Boulevard
    Arlington, VA 22230
    (703) 292-7281
    (703) 292-9068

    Soo-Siang Lim

    Soo-Siang Lim
    4201 Wilson Boulevard
    Arlington, VA 22230
    (703) 292-7878

    Cori Anderson

    Cori Anderson
    4201 Wilson Boulevard
    Arlington, VA 22230
    (703) 292-8740
     

  • Eligibility Details

    Unrestricted (i.e., open to any type of entity above), subject to any clarification in text field entitled "Additional Information on Eligibility"

    Deadline Details

    Proposals are to be submitted by July 11, 2018; Second Wednesday in July, Annually Thereafter and January 16, 2019; Third Wednesday in January, Annually Thereafter.

    Award Details

    Award amounts vary.

    Related Webcasts Use the links below to view the recorded playback of these webcasts


    • Funding Classroom Technology to Empower Students and Teachers - Sponsored by Panasonic - Playback Available
    • Maximizing Technology-friendly Workforce Development Grants - Sponsored by Panasonic - Playback Available
    • Funding Data-driven Workforce Development Projects - Sponsored by NetApp - Playback Available

 

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