Opportunity Information: Apply for 14 526
Apply for 14 526
- The National Science Foundation in the science and technology and other research and development sector is offering a public funding opportunity titled "Cyberlearning and Future Learning Technologies" and is now available to receive applicants.
- Interested and eligible applicants and submit their applications by referencing the CFDA number(s): 47.041 Engineering Grants 47.070 Computer and Information Science and Engineering 47.075 Social, Behavioral, and Economic Sciences 47.076 Education and Human Resources.
- This funding opportunity was created on Aug 8, 2015 and posted on Dec 20, 2013.
- Applicants must submit their applications by Dec 18, 2015 Integration Projects (INTs) Capacity Building Projects (CAPs) Capacity Building Projects (CAPs) Capacity Building Projects (CAPs) Letter of Intent Integration (INT) Projects only Exploration Projects (EXPs) Development and Implementation (DIPs). (Agency may still review applications by suitable applicants for the remaining/unused allocated funding in 2026.)
- The funding agency has allocated a total of $18,000,000.00 to eligible and selected applicants.
- Each selected applicant is eligible to receive up to $2,500,000.00 in funding.
- The number of recipients for this funding is limited to 34 candidate(s).
- Eligible applicants include: Unrestricted (i.e., open to any type of entity above), subject to any clarification in text field entitled Additional Information on Eligibility.
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Opportunity Summary:
The National Science Foundation (NSF) Cyberlearning and Future Learning Technologies program (Funding Opportunity NSF 14-526) supports research and development that connects emerging technologies with established and emerging knowledge about how people learn. The central goal is to push learning technologies beyond incremental classroom add-ons and toward genuinely new forms of learning and assessment that are enabled by technology-rich environments. In practical terms, NSF is looking for work that does more than digitize existing instruction; the emphasis is on advancing learning experiences for learners and generating generalizable knowledge about learning in these environments.
The program is organized around three tightly connected thrusts that proposals are expected to address together. First is innovation: inventing and improving next-generation genres (types) of learning technologies, finding new ways technology can foster and assess learning, and creating new approaches for integrating multiple learning technologies into coherent learning environments. Second is advancing the understanding of learning in technology-rich settings: building stronger scientific understanding of how people learn when the environment itself can capture detailed data, support interaction, and enable computational modeling of learners and groups in ways that are not feasible in traditional settings. Third is promoting broad use and transferability: extracting lessons from research and development experiences so that what is learned can inform the design and effective use of new learning technology genres across different disciplines, learner populations, and learning contexts, rather than remaining locked to a single course or niche implementation.
A key boundary of the opportunity is that it prioritizes learner-centered advances. NSF states that innovations aimed mainly at making teaching easier are not a fit for this program. Projects involving teachers or facilitators can be supported, but only when teachers are treated as learners and the purpose is to help them learn approaches that ultimately improve learner outcomes and learner experiences. The expectation is that funded work will illuminate how technology can enable new educational practices, including practices that would be difficult or impossible without those technologies.
NSF highlights several especially desirable directions for proposed technological advances. These include technologies that help learners develop deep conceptual understanding while also building strong practices and skills (not just memorization or superficial completion). The program also values approaches that broaden participation by engaging learners who are not well served by current educational practices, whether due to access barriers, mismatches with conventional instruction, or other systemic gaps. A third priority area is assessment: creating new ways to assess learners understanding, engagement, and capabilities, particularly through the kinds of data streams and interactions available in technology-rich environments.
The solicitation also makes clear what it does not intend to fund. Projects that simply implement and evaluate a specific software application or technology for a particular course are not supported. In other words, a straightforward classroom deployment study of an existing tool, without advancing the underlying technology genre, learning science understanding, and transferable insights, would generally fall outside the program’s scope.
Awards are structured across multiple categories that correspond to stages of research and development. Exploration (EXP) projects support early-stage, high-potential ideas and foundational investigations. Design and Implementation (DIP) projects support building and studying learning technologies and environments in a more developed form. Integration (INT) projects focus on integrating and scaling insights, technologies, or approaches in ways that emphasize broader applicability and coherent learning ecosystems. The program also supports smaller Capacity Building (CAP) projects such as conferences, workshops, and partnership-building efforts that strengthen the field and help form communities and collaborations. In addition, the program participates in NSF-wide mechanisms such as EAGER, RAPID, INSPIRE, and CAREER, which provide additional pathways for certain types of high-risk, urgent, interdisciplinary, or early-career work.
From the funding details provided, the opportunity is a discretionary NSF grant program with an estimated total funding level of about $18,000,000 and an expected 34 awards. Individual award sizes range from a $20,000 floor up to a $2,500,000 ceiling, and there is no cost-sharing requirement. Eligibility is listed as unrestricted, meaning a wide range of organization types may apply, subject to any specific clarifications in the full solicitation. The opportunity aligns with multiple NSF program areas and CFDA numbers spanning Engineering, Computer and Information Science and Engineering, Social, Behavioral, and Economic Sciences, and Education and Human Resources, reflecting its intentionally interdisciplinary nature. The original posting date was December 20, 2013, with multiple due dates tied to project type (including a letter of intent requirement for Integration projects), and the opportunity was later archived on August 27, 2017.
Frequently Asked Questions (FAQs)
What is the NSF Cyberlearning and Future Learning Technologies program (NSF 14-526)?
The NSF Cyberlearning and Future Learning Technologies program (Funding Opportunity NSF 14-526) supports research and development that connects emerging technologies with established and emerging knowledge about how people learn. Its aim is to move learning technologies beyond incremental classroom add-ons and toward new forms of learning and assessment that are enabled by technology-rich environments.
What is the central goal of this opportunity?
The central goal is to advance learning experiences and assessment in ways that would be difficult or impossible without technology-rich environments, while also producing generalizable knowledge about how people learn in these environments. The program emphasizes more than simply digitizing existing instruction.
What kinds of projects is NSF looking for under this program?
NSF is looking for projects that (1) innovate by inventing or improving next-generation learning technology genres, (2) advance scientific understanding of learning in technology-rich settings (including the use of detailed data and computational modeling), and (3) promote broad use and transferability so that insights can inform learning technology design across disciplines, populations, and contexts.
What are the three thrusts proposals are expected to address together?
Proposals are expected to address these tightly connected thrusts together:
- Innovation: Create or improve next-generation genres of learning technologies; develop new ways technology can foster and assess learning; integrate multiple learning technologies into coherent learning environments.
- Advancing understanding of learning: Build stronger scientific understanding of how people learn in technology-rich environments that can capture detailed data, support interaction, and enable computational modeling of learners and groups.
- Broad use and transferability: Extract general lessons so results can inform design and effective use across different disciplines, learner populations, and learning contexts (not just a single course or niche setting).
Does the program prioritize learner-centered work?
Yes. A key boundary is that the program prioritizes learner-centered advances. Innovations aimed mainly at making teaching easier are stated to be a poor fit for this program.
Are projects involving teachers or facilitators allowed?
They can be supported when teachers are treated as learners and the purpose is to help them learn approaches that ultimately improve learner outcomes and learner experiences.
What does NSF mean by moving beyond "incremental classroom add-ons"?
The program is not focused on small enhancements that merely add technology on top of existing instruction. Instead, it emphasizes technology-enabled learning experiences and assessment approaches that represent genuinely new possibilities enabled by technology-rich environments.
What are some especially desirable directions for technological advances?
NSF highlights several desirable directions, including:
- Technologies that help learners develop deep conceptual understanding while also building strong practices and skills (not just memorization or superficial completion).
- Approaches that broaden participation by engaging learners who are not well served by current educational practices due to access barriers, mismatches with conventional instruction, or other systemic gaps.
- New approaches to assessment of understanding, engagement, and capabilities, particularly using the data streams and interactions available in technology-rich environments.
Is this program focused on assessment as well as instruction?
Yes. Assessment is explicitly called out as a priority area, with an emphasis on creating new ways to assess understanding, engagement, and capabilities using the kinds of rich data and interactions that technology-rich environments can provide.
What types of projects are explicitly not intended to be funded?
The solicitation states it does not intend to fund projects that simply implement and evaluate a specific software application or technology for a particular course. A straightforward classroom deployment study of an existing tool, without advancing the underlying technology genre, learning science understanding, and transferable insights, would generally be outside the program scope.
Does the program fund work that digitizes existing instruction?
Work that primarily digitizes existing instruction is not the emphasis. The program seeks advances that go beyond digitization by enabling new forms of learning and assessment and by producing generalizable knowledge about learning in technology-rich environments.
How are awards structured (project categories)?
Awards are structured across multiple categories corresponding to stages of research and development:
- Exploration (EXP): Early-stage, high-potential ideas and foundational investigations.
- Design and Implementation (DIP): Building and studying learning technologies and environments in a more developed form.
- Integration (INT): Integrating and scaling insights, technologies, or approaches with emphasis on broader applicability and coherent learning ecosystems.
- Capacity Building (CAP): Smaller projects such as conferences, workshops, and partnership-building efforts to strengthen the field and form communities and collaborations.
Are there additional NSF mechanisms associated with this program?
Yes. The program participates in NSF-wide mechanisms such as EAGER, RAPID, INSPIRE, and CAREER, which provide additional pathways for certain types of high-risk, urgent, interdisciplinary, or early-career work.
What is the estimated total funding level and expected number of awards?
The estimated total funding level is about $18,000,000, with an expected 34 awards.
What is the range of individual award sizes?
Individual award sizes range from a $20,000 floor up to a $2,500,000 ceiling.
Is cost sharing required?
No. The information provided states there is no cost-sharing requirement.
Who is eligible to apply?
Eligibility is listed as unrestricted, meaning a wide range of organization types may apply, subject to any specific clarifications in the full solicitation.
Is this opportunity intended to be interdisciplinary?
Yes. The opportunity aligns with multiple NSF program areas and CFDA numbers spanning Engineering, Computer and Information Science and Engineering, Social, Behavioral, and Economic Sciences, and Education and Human Resources, reflecting its intentionally interdisciplinary nature.
When was the opportunity posted, and what is its current status?
The original posting date was December 20, 2013. The opportunity was later archived on August 27, 2017.
Are there multiple due dates, and is a letter of intent required?
Yes. The opportunity has multiple due dates tied to project type, and Integration (INT) projects include a letter of intent requirement.
What is meant by "broad use and transferability" in this program?
It means the project should produce lessons and insights that can inform the design and effective use of new learning technology genres across different disciplines, learner populations, and learning contexts, rather than remaining limited to a single course or niche implementation.
What is meant by "learning technologies" in the context of this program?
In this program, learning technologies refer to technology-rich learning environments and next-generation genres of tools and systems that can foster learning, support interaction, enable the capture of detailed data, and make possible new forms of assessment and computational modeling of learners and groups.
What does NSF emphasize about scientific understanding in technology-rich settings?
NSF emphasizes building stronger scientific understanding of how people learn when the environment can capture detailed data, support interaction, and enable computational modeling in ways that are not feasible in traditional learning settings.
How does the program view projects that focus mainly on making teaching easier?
The program states that innovations aimed mainly at making teaching easier are not a fit. Projects should be learner-centered and designed to improve learner outcomes and experiences.
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