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Frequently Asked Questions (FAQs)

What is the NSF Cyberlearning: Transforming Education program?

The National Science Foundation (NSF) Cyberlearning: Transforming Education program (NSF 11-587) is a research and development funding opportunity focused on improving learning through the tight integration of advanced technologies and modern learning sciences. It supports projects that create learning technologies and produce rigorous evidence about how, why, and under what conditions technology productively supports learning.

What is the main goal of this program?

The program aims to generate new knowledge about learning when technology is part of the experience and to create tools and approaches that make learning more effective, more inclusive, and more measurable. It is not focused on simply adding technology to existing instruction, but on transforming learning experiences and understanding learning processes and outcomes through evidence.

What kinds of learning does NSF want to support through this opportunity?

NSF is interested in projects that explain and demonstrate how technology can productively support learning for individuals and for groups collaborating in technology-mediated environments.

What does NSF mean by the "full cycle of cyberlearning innovation"?

The full cycle refers to: (1) using technology to collect, analyze, share, and manage learning-related data; (2) using that evidence to understand learning processes and outcomes; and (3) using those insights to design and refine learning environments. The program emphasizes connecting these stages rather than treating them as separate activities.

Are projects expected to build new technology, or can they improve existing tools?

Both are allowed. Proposals can focus on developing new technologies, improving existing technologies, repurposing existing technologies, or advancing theory and practice for integrating technologies into real learning settings so their potential is actually realized.

Does NSF expect research evidence, or is it mainly about building tools?

The program values both the creation of learning technologies and the rigorous research needed to show how, why, and under what conditions they work. Evidence-building and research on learning are central to the solicitation as described.

What priority directions does NSF highlight?

The solicitation highlights several priority directions, including personalized learning, broadening participation, expanding access to learning resources anytime and anywhere, and technology-enabled assessment approaches that can measure learning more authentically and continuously than traditional tests.

What is meant by personalized learning in this program?

Personalized learning includes systems that adapt to learners' needs, pace, prior knowledge, and goals.

How does the program address broadening participation?

The program emphasizes designing technologies that better serve learners who are not well supported by current educational practices, including underrepresented or underserved populations.

What kinds of learning contexts are included under "anytime and anywhere" access?

This can include mobile, online, hybrid, and informal learning contexts, with an emphasis on expanding access to learning resources beyond traditional settings.

What types of assessment innovations are of interest?

NSF is interested in new approaches to assessment, especially technology-enabled ways to measure skills and capabilities more authentically and continuously than traditional tests, and to use assessment data to improve learning and instruction.

What project categories (award types) are available under this program?

The program includes Exploratory (EXP), Design and Implementation (DIP), and Integration and Deployment (INDP) awards. It also supports Capacity Building Projects (CAP) and a Cyberlearning Resource Center (CRC) intended to coordinate and disseminate program outcomes.

What are Exploratory (EXP) awards intended to support?

Exploratory awards support earlier-stage, high-potential ideas where investigators test promising concepts, frameworks, or enabling technologies.

What are Design and Implementation (DIP) awards intended to support?

DIP awards support more developed work, typically involving building and studying learning technologies or environments in meaningful contexts, with stronger evidence-building and iterative design.

What are Integration and Deployment (INDP) awards intended to support?

INDP awards focus on later-stage efforts to integrate proven approaches into practice at broader scale, studying adoption, effectiveness, sustainability, and the conditions needed for successful implementation.

What are Capacity Building Projects (CAP)?

CAPs are smaller projects meant to strengthen the community and infrastructure for cyberlearning research. Examples mentioned include planning, partnership-building, or developing shared resources.

What is the Cyberlearning Resource Center (CRC)?

The CRC is intended to help coordinate, disseminate, and amplify program outcomes across the cyberlearning community.

What is the award mechanism for this opportunity?

This is described as a discretionary NSF opportunity using cooperative agreements, which indicates an expectation of substantial NSF involvement during the award period compared to a standard grant.

Which NSF areas does this solicitation span?

The opportunity spans multiple NSF program areas, reflected in CFDA numbers for Computer and Information Science and Engineering (47.070), Social, Behavioral, and Economic Sciences (47.075), Education and Human Resources (47.076), and the Office of Cyberinfrastructure (47.080).

Does the cross-cutting scope imply interdisciplinary teams are important?

Yes. The mix of program areas signals that competitive projects often bring together interdisciplinary teams, such as learning scientists, computer scientists, data scientists, education researchers, and practitioners working in real learning settings.

How much funding is available overall?

NSF anticipated making about 49 awards with an estimated total program funding level of $36,000,000.

What is the funding range for individual awards?

Individual awards range from a minimum (floor) of $25,000 to a maximum (ceiling) of $2,500,000, supporting both small targeted efforts and larger development, evaluation, and deployment projects.

Is cost sharing or matching required?

No. The solicitation states there is no cost sharing or matching requirement.

Who is eligible to apply?

Eligibility is described as unrestricted (open to any type of entity), subject to any additional eligibility details in the full solicitation (NSF Publication 11-587).

When was this opportunity originally posted?

The original posting date shown is September 16, 2011.

What are the key deadline details mentioned?

The listing notes multiple target and deadline dates by project type across 2012 and early 2013, including a letter of intent deadline specifically for Integration and Deployment Projects. A current closing date is shown as July 15, 2013, with additional target and deadline dates listed for the different project categories.

Is a letter of intent required?

A letter of intent deadline is specifically mentioned for Integration and Deployment Projects (INDP). The listing does not describe letter of intent requirements for other categories.

Where can applicants find the official requirements and instructions?

Applicants are directed to NSF Publication 11-587 for full requirements.

Who should applicants contact for technical help with Grants.gov?

NSF provides a Grants.gov support contact for access or technical issues (the listing indicates support is available for Grants.gov-related problems).

What outcomes is NSF hoping to achieve through funded projects?

The program is aimed at producing both practical learning innovations and durable scientific understanding of technology-supported learning. NSF expects the resulting knowledge and tools to enable new forms of educational practice and, over time, contribute to a more actively engaged and productive citizenry and workforce through better learning opportunities, better evidence about what works, and better pathways to scale effective cyberlearning approaches.