National Science Foundation (NSF) Cyberlearning and Future Learning Technologies

National Science Foundation (NSF) Cyberlearning and Future Learning Technologies is sponsored by National Science Foundation (NSF). Supports projects that advance learning through innovative technologies, including media projects by individuals.

NSF 17-520: Cyberlearning and Future Learning Technologies (RITEL) | NSF - U.S. National Science Foundation Archived funding opportunity This solicitation is archived. Important information for proposers and award recipients All proposals must be submitted in accordance with the requirements specified in the funding opportunity and in the Proposal & Award Policies & Procedures Guide (PAPPG) and its supplements .

All NSF grants and cooperative agreements are subject to the applicable set of NSF award terms and conditions . NSF has updated its research security policies for NSF funded projects. NSF 17-520: Cyberlearning and Future Learning Technologies (Cyberlearning) Download the solicitation (PDF, 0.

6mb) National Science Foundation Directorate for Computer & Information Science & Engineering Directorate for Education & Human Resources Directorate for Engineering Full Proposal Deadline(s) (due by 5 p. m. submitter's local time): Important Information And Revision Notes This solicitation calls for proposals to only one proposal category, Exploration (EXP).

Proposals in the following categories may no longer be submitted to this program: Development and Implementation Projects (DIP); and Capacity Building Projects (CAP). Additionally, a Cyberlearning proposal may no longer be submitted to the Faculty Early-Career Development (CAREER) or CISE Research Initiation Initiative (CRII) programs. Letters of Intent and Target Deadlines no longer apply to this solicitation.

Any proposal submitted in response to this solicitation should be submitted in accordance with the revised NSF Proposal & Award Policies & Procedures Guide (PAPPG) ( NSF 17-1 ), which is effective for proposals submitted, or due, on or after January 30, 2017. Please be advised that proposers who opt to submit prior to January 30, 2017, must also follow the guidelines contained in NSF 17-1.

Summary Of Program Requirements Cyberlearning and Future Learning Technologies The purpose of the Cyberlearning and Future Learning Technologies program is to integrate opportunities offered by emerging technologies with advances in what is known about how people learn to advance three interconnected thrusts: Cyber innovation : Developing next-generation cyberlearning approaches through high-risk, high-reward advances in computer and information science and engineering; Learning innovation : Inventing and improving next-generation genres (types) of learning technologies, identifying new means of using technology for fostering and assessing learning, and proposing new ways of integrating learning technologies with each other and into learning environments to foster and assess learning; and Advancing understanding of how people learn in technology-rich learning environments : Enhancing understanding of how people learn and how to better foster and assess learning, especially in technology-rich learning environments that offer new opportunities for learning and through data collection and computational modeling of learners and groups of learners that can be done only in such environments.

The intention of this program is to advance technologies that specifically focus on the experiences of learners; innovations that simply focus on making teaching easier will not be funded.

Proposals that focus on teachers or facilitators as learners are invited; the aim in these proposals should be to help teachers and facilitators capitalize on the affordances of technology and fundamental knowledge about how people learn to make the learning experiences of learners more effective. Proposals are expected to address all three of the program's thrusts.

Of particular interest are technological advances that (1) foster deep understanding of content coordinated with masterful learning of practices and skills; (2) draw in and encourage learning among populations not served well by current educational practices; and/or (3) provide new ways of assessing understanding, engagement, and capabilities of learners.

It is expected that research funded by this program will shed light on how technology can enable new forms of educational practice. This program does not support proposals that aim simply to implement and evaluate a particular software application or technology in support of a specific course. Cognizant Program Officer(s): Please note that the following information is current at the time of publishing.

See program website for any updates to the points of contact. Tatiana Korelsky, co-lead, Amy L. Baylor, co-lead EHR, William Bainbridge, Program Officer, Kamau Bobb, Program Officer, John Cherniavsky, Program Officer, Elliot Douglas, Program Officer, Kevin Lee, Program Officer, Sushil K.

Prasad, Program Officer, Robert Russell, Program Officer, Chia Shen, Program Officer, Maria Zemankova, Program Officer, Applicable Catalog of Federal Domestic Assistance (CFDA) Number(s): --- Computer and Information Science and Engineering --- Education and Human Resources Anticipated Type of Award: Standard Grant Estimated Number of Awards: 12 Contingent upon availability of funds.

Anticipated Funding Amount: $6,000,000 Each EXP Project will be funded for a duration of 2 to 3 years and up to a total funding amount of $550,000. With appropriate justification, some EXP projects may be funded for up to $750,000. Proposers should receive permission from a program officer before submitting a budget larger than $550,000.

Who May Submit Proposals: The categories of proposers eligible to submit proposals to the National Science Foundation are identified in the Grant Proposal Guide, Chapter I, Section E. 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: 2 An individual may participate as PI or co-PI in no more than a total of two (2) proposals in response to this solicitation.

In the event that an individual exceeds the limit for this solicitation, proposals received within the limit will be accepted based on earliest date and time of proposal submission (i.e. the first two proposals received will be accepted and the remainder will be returned without review). No exceptions will be made. Proposal Preparation and Submission Instructions A.

Proposal Preparation Instructions Letters of Intent: Not required Preliminary Proposal Submission: Not required Full Proposals submitted via FastLane: NSF Proposal and Award Policies and Procedures Guide, Part I: Grant Proposal Guide (GPG) Guidelines apply. The complete text of the GPG is available electronically on the NSF website at: https://www. nsf.

gov/publications/pub_summ. jsp? ods_key=gpg .

Full Proposals submitted via Grants. gov: NSF Grants. gov Application Guide: A Guide for the Preparation and Submission of NSF Applications via Grants.

gov Guidelines apply (Note: The NSF Grants. gov Application Guide is available on the Grants. gov website and on the NSF website at: https://www.

nsf. gov/publications/pub_summ. jsp?

ods_key=grantsgovguide ) Cost Sharing Requirements: Inclusion of voluntary committed cost sharing is prohibited. Indirect Cost (F&A) Limitations: Other Budgetary Limitations: Full Proposal Deadline(s) (due by 5 p. m.

submitter's local time): Proposal Review Information 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 Additional award conditions apply. Please see the full text of this solicitation for further information. Standard NSF reporting requirements apply.

The purpose of the Cyberlearning and Future Learning Technologies (Cyberlearning) program is to integrate opportunities offered by emerging technologies with advances in what is known about how people learn to further design of the next generation of learning technologies and increase understanding of how people learn in technology-rich learning environments.

The program’s purpose derives from a multi-part vision: New and emerging technologies have the potential to expand and transform learning opportunities, learning interests, and learning outcomes in all phases of life, making it possible for learning opportunities to be tailored to the interests, needs, and resources of individual learners and groups of learners.

This includes populations who are not reached well by current educational resources (nationally and worldwide). The best technological genres and socio-technical systems designed for these purposes will be informed by what is known about how people learn, how to foster learning, and the design and implementation of environments for productive learning.

With these systems in place, the opportunity exists to make significant progress in formulating a cutting-edge understanding of learning that aims towards predictive computational models of individual and group learning in real-world learning environments.

The program has two goals: (1) to invent, explore, and learn to effectively use the new technologies that will address society’s educational goals; and (2) to advance understanding of how people learn and how to better foster learning in the context of the new kinds of learning experiences that technology makes possible.

To achieve these goals, NSF invites proposals that integrate advances in what is known about how people learn with the opportunities offered by emerging technologies to address three interconnected thrusts: Cyber innovation : Developing next-generation cyberlearning approaches through high-risk, high-reward advances in computer and information science and engineering; Learning innovation : Inventing and improving next-generation genres (types) of learning technologies, identifying new means of using technology for fostering and assessing learning, and proposing new ways of integrating learning technologies with each other and into learning environments to foster and assess learning; and Advancing understanding of how people learn in technology-rich learning environments : Enhancing understanding of how people learn and how to better foster and assess learning, especially in technology-rich learning environments that offer new opportunities for learning and through data collection and computational modeling of learners and groups of learners that can be done only in such environments.

The answers to several critical and timely questions that have arisen from previously-funded NSF projects and programs will enable new designs and uses of technology for fostering and assessing learning.

Projects that help answer one or more of these sets of questions are encouraged: What new technology and socio-technical models are needed to capitalize on the interests and leverage the cognitive, cultural, social, language and developmental resources of different learners and populations of learners so as to draw in learners who might not be reached without those innovations, and help all learners learn more deeply than they would otherwise?

What new technology and socio-technical models are needed to help learners develop new interests, deepen their understanding of complicated concepts and phenomena, and foster their learning of complex practices and skills?

What new technology and socio-technical models are needed so that the big data generated by scientists and engineers can be made available and accessible to learners at all levels in ways that will engage them and help them learn? Under what conditions do these approaches work and why? What new technology and socio-technical models for blended and online education are needed to foster deep understanding and masterful capabilities?

How and under what conditions can these new models be effectively executed, and what makes them work? What new models for educating will emerge from integrating learning technologies with each other or incorporating them into the lives of learners, communities, or organizations? What new technological models and platforms are needed to support such new models?

Under what conditions do these new models work well and why? What data need to be collected, how can they be collected, and how should they be analyzed to assess, foster, and understand learning? How can such analysis and the models that come from these analyses be used to tailor learning experiences and to inform learners, educators and educational institutions ?

The technological focus of the Cyberlearning program is on design and exploration of new types, or "genres," of learning technologies that can be used to achieve the ambitious goals referred to in the questions. A “technological genre” is a type or category of learning technology or a new type of configuration of learning technologies rather than a particular application or tool.

The "socio-technical" systems of interest are the combination of social and technological infrastructures and environments that support learning and assessment.

Other NSF programs (e.g., Discovery Research PreK-12 (DRK-12) , Advancing Informal STEM Learning (AISL) ) support design of resources, tools, and models for learning particular content and skills; the Cyberlearning program funds projects that imagine the new types of technological resources, tools, and models that might be used to foster and assess learning as emerging technologies become more available and capable.

Proposed new genres may be designed for formal or informal learning environments and may represent new technologies, new ways of using technology, or new types of socio-technical systems. The resources, tools, and models developed as part of Cyberlearning projects should serve as exemplars from which more broadly applicable and transferable knowledge about design and use of learning technologies can be extracted.

It is expected that the proposed novel technologies will advance the state of the art in computer and information science and engineering as well as social and behavioral sciences. At the same time, it is expected that research and development plans will draw on the most up-to-date scholarly literature on how people learn and the uses of technology to foster learning.

“How people learn” refers to cognitive, neurobiological, behavioral, cultural, social, volitional, epistemological, developmental and other processes involved in individual learning, the processes by which communities increase their understanding and capabilities, and influences on those processes. "Fostering learning" refers to providing whatever help learners need to advance their understanding and capabilities.

This might include helping learners better understand difficult concepts and become masterful at skills; recognize when that understanding and those skills are applicable and knowing how to use them; become interested in learning particular content and skills; become excited about learning; make connections between what they are learning and the world in which they life; and identify their interests.

"Assessing learning" is also broadly defined, meaning interpretation of what learners understand, are capable of, and are feeling, among other things. Some assessment might be done automatically by technology, while other assessment will require technology and people to work together.

Assessment might be done by computers along with teachers or mentors, or it might be done by computers along with learners themselves or groups of learners. The results of assessment are useful only to the extent that they are presented well to those who need to use those results, and designing new ways of helping teachers and learners interpret assessment results is included in the ambitious goals of this program.

Proposed technological innovations should focus primarily on the experiences of learners; innovations that simply focus on making teaching easier will not be funded. Proposals that focus on teachers or facilitators as learners are invited; the aim in these proposals should be to help teachers and facilitators learn to make the learning experiences of learners more effective.

This revision of the Cyberlearning and Future Learning Technologies solicits research in the Exploration (EXP) category. The purpose of an EXP project is to try out new ideas, especially risky ones, and explore issues associated with fostering or assessing learning in the context of the proposed innovation.

Every proposal is expected to address all three of the program’s thrusts: technology innovation, learning innovation, and advancing understanding of learning in technology-rich learning environments. While the three thrusts are listed separately, it is important to note that they are highly interconnected, and it is expected that these three parts of every proposal will be interconnected .

Technological innovations, for example, are expected to address some important societal challenge or take advantage of some forward-looking technology opportunity, be informed by what is known about how people learn, and be aimed at strengthening and improving our understanding of how learning happens or how to foster learning or encourage and sustain engagement.

Similarly, research activities in support of advancing understanding of learning and promoting generalizability and transferability of new types of learning technologies may be highly interconnected. While it is essential that proposed innovations have the potential to improve significantly on the status quo , proposals do not have to address any particular content, populations, or learning environments.

There are no requirements for coverage of any particular content or skills, though support of learning in areas supported by NSF is encouraged. Learners may be of any age, and targeted learning environments may be formal or informal, traditional or non-traditional, collaborative or individual, or may combine or bridge several different types of learning venues.

The following sections provide general and specific requirements for EXP proposals. The Methodology subsection includes advice about incorporating suggestions from the joint NSF/Department of Education publication Common Guidelines for Education Research and Development. Section V.

A, Proposal Preparation Instructions , includes more specific information about organizing proposals and what to include in each section. The Three Interconnected Thrusts 1. Cyber innovation and 2.

Learning innovation The proposed innovation may be technological, advancing some new or emerging genre (type) of learning technology or exploring new ways of using technologies for learning or assessment, or coherently integrating such technologies with each other; or it may be socio-technical , representing a new or emerging type of technologically-rich learning environment.

Proposed innovations should be informed by the substantial literatures in computer and information science and engineering and on how people learn, how to foster deep learning, and the uses of extant technology in fostering learning.

Proposed projects should produce a “minimally viable product" that will allow PIs to understand how to design and use the new type of innovation, answer research questions, and extract guidelines on scalability and transferability.

Note that incremental advances in existing technologies will not be funded through this program; rather, proposals must aim to lay the foundations for designing or refining new and emerging genres of learning technologies. As stated earlier, the intention of this program is to advance technologies that specifically focus on the experiences of learners.

Innovations that simply focus on making teaching easier will not be funded, but projects that focus on helping teachers or facilitators learn to make learning more effective and engaging for the learners with whom they work are appropriate for this program. 3.

Advancing understanding of how people learn in technology-rich learning environments It is expected that each proposal will include an explicit set of foundational research questions that, when answered, will advance understanding of processes involved in learning (e.g., neurobiological, behavioral, cognitive, cultural, social, epistemological, and/or developmental) and/or how to foster or assess learning, along with a plan for answering or exploring the answers to these questions.

In general, these will be research questions that can only be answered in the context of use of the new type of technology or learning environment. Questions may be about development of understanding or capabilities, processes involved in learning, influences on learning, how to foster learning, or how to assess learning. Note that these questions are distinct from evaluation questions.

Foundational research questions should be explanatory, uncovering why, how, to what extent, or under what circumstances phenomena occur. Their answers should contribute new understandings that endure beyond the proposed implementation. No particular methodologies are required for answering research questions; rather research methodology and data collection should be chosen to answer the important questions PIs are seeking to answer.

The National Science Foundation and the Institute of Education Sciences in the U.S. Department of Education have released a collaborative publication, Common Guidelines for Education Research and Development . The Guidelines describe six types of research studies that can generate evidence about how to increase student learning.

Research types include those that generate the most fundamental understandings related to education and learning; examinations of associations between variables; iterative design and testing of strategies or interventions; and assessments of the impact of a fully-developed intervention on an education outcome.

For each research type, there is a description of the purpose and the expected empirical and/or theoretical justifications, types of project outcomes, and quality of evidence. The Guidelines publication can be found on the NSF website (NSF 13-126; https://nsf-gov-resources. nsf.

gov/pubs/2013/nsf13126/nsf13126. pdf? VersionId=Q_gbdvjhLu9vQTRmQY.

ex3Md4dnJ5LL9). A set of FAQs regarding the Guidelines are available (NSF 13-127; https://nsf-gov-resources. nsf.

gov/pubs/2013/nsf13127/nsf13127. pdf? VersionId=oHQOKysGhw5JLkogfSsJeE7uBqZGJhwN).

Grant proposal writers and PIs are encouraged to familiarize themselves with both documents and use the information therein to help in the preparation of their Cyberlearning proposals. Project teams and advisory boards: It is expected that all proposal teams will include appropriate interdisciplinary expertise.

The project team (including PIs, senior personnel and supporting investigators, post-docs, advisory board members, and others) should be appropriate for addressing proposed technical and research goals. Expertise in any area may exist in a single person or among the set of people working together, including PIs or advisory board members.

Advisory boards are required and should include two types of advisors, some who complement the expertise of PIs and senior personnel and provide advice about design, implementation, and analysis; and some who have enough distance from the project to contribute to critical review.

Each project team should include expertise in how people learn and the targeted content, technology learners, and practices of educating in the targeted learning environment. It is especially important that each team have at least one key participant who is expert at design of learning experiences or several key participants whose complementary expertise supports sophisticated design of learning experiences.

Every Cyberlearning proposal requires a Collaboration and Management Plan , included as a Supplementary Document .

The plan may be up to 3 pages long and should be used to articulate the roles of all team members, why the proposed team is an appropriate one, the expertise each team member brings, how the team will work together, and how the integrated contributions of the members of the proposal team are greater than the sum of the contributions of each individual member of the team. Proposal Preparation Instructions in Section V.

A has more detail on the specific requirements of the Collaboration and Management Plan. EXPLORATION PROJECTS (EXP) This solicitation funds projects in the Exploration (EXP) category.

Exploration Projects (EXP projects) explore the proof-of-concept or feasibility of a novel or innovative technology and use of such technology for assessment or to promote learning; EXP projects are particularly suited to trying out new ideas, especially risky ones.

Prerequisites : Ateam with a shared vision that takes into account what is known about how people learn, learning in the targeted domain, and the use of the technology for such learning, and what is already known about effective use of the particular technologies being proposed as well as the challenges to technology effectiveness is required.

Cyber and Learning innovation : The “minimally viable product” should be sufficient for exploring the feasibility of technology and its role in the new genre and identifying challenges to its effective use.

EXP projects should explore, at a minimum, the usability of the technology, the ways learners are (effectively or not effectively) using it for learning or assessment, pathways toward engaging learners in sustained use, and challenges to effective use.

Advancing understanding of learning in technology-rich learning environments : EXP projects should aim to shed light on the answers to foundational questions related to learning, learning with technology, linking learning and assessment, and/or learning in technology-rich environments or point the way towards focused fundamental research questions that can be addressed in the context of the proposed new genre.

Promoting broad use and transferability of the new genre : EXP projects should focus on the affordances (opportunities offered) of the proposed innovation for fostering learning or automating assessment and challenges or barriers to its effective use. It is important to study the use of the innovation in situ , i.e., to get close to the learners and their interactions with the technology, in order to address these issues.

Guidelines for effective design or use may or may not be extracted from EXP studies. Methodology : It is not expected that EXP projects will include summative evaluations or comparative studies. However, proposals must describe expected results and associated success measures.

Project team: Project teams should include, at a minimum, the expertise needed to successfully carry out the design and iterative refinement of the technology, identification of affordances and challenges to effective use of the new technology, and research that will shed light on answers to proposed research questions. The advisory board may also include people whose expertise will be needed in later phases of research and development.

Duration and funding : 2 to 3 years and up to a total of $550,000. With appropriate justification, some EXP projects may be funded for up to $750,000. Proposers should receive permission from a program officer before submitting a budget larger than $550,000.

CIRCL (the Center for Innovative Research in Cyberlearning; http://circlcenter. org ) provides capacity-building aid to NSF’s cyberlearning-related programs.

CIRCL helps PIs collaborate to synthesize findings across NSF’s cyberlearning portfolio, fosters national awareness of research contributions from NSF’s cyberlearning portfolio, and helps build NSF’s cyberlearning community through summits, envisioning and synthesis meetings, research-to-practice meetings, special interest meetings, and matchmaking facilitation.

All Cyberlearning and Future Learning Technologies projects are required to share their findings with CIRCL, to participate in at least some of the meetings and in synthesis activities, and to be responsive to requests for information from other cyberlearning PIs and from CIRCL. Approximately $6 million is anticipated to fund EXP proposals for durations of 2 to 3 years and up to a total funding amount of $550,000 per EXP project.

Some EXP projects may be funded for up to $750,000 with approval from a cognizant program officer (see Section VIII) before submission. IV. Eligibility Information Who May Submit Proposals: The categories of proposers eligible to submit proposals to the National Science Foundation are identified in the Grant Proposal Guide, Chapter I, Section E.

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: 2 An individual may participate as PI or co-PI in no more than a total of two (2) proposals in response to this solicitation.

In the event that an individual exceeds the limit for this solicitation, proposals received within the limit will be accepted based on earliest date and time of proposal submission (i.e. the first two proposals received will be accepted and the remainder will be returned without review). No exceptions will be made. V.

Proposal Preparation And Submission Instructions A. Proposal Preparation Instructions Full Proposal Preparation Instructions : Proposers may opt to submit proposals in response to this Program Solicitation via Grants. gov or via the NSF FastLane system.

Full proposals submitted via FastLane: Proposals submitted in response to this program solicitation should be prepared and submitted in accordance with the general guidelines contained in the NSF Grant Proposal Guide (GPG). The complete text of the GPG is available electronically on the NSF website at: https://www. nsf.

gov/publications/pub_summ. jsp? ods_key=gpg .

Paper copies of the GPG may be obtained from the NSF Publications Clearinghouse, telephone (703) 292-7827 or by e-mail from nsfpubs@nsf. gov . Proposers are reminded to identify this program solicitation number in the program solicitation block on the NSF Cover Sheet For Proposal to the National Science Foundation.

Compliance with this requirement is critical to determining the relevant proposal processing guidelines. Failure to submit this information may delay processing. Full proposals submitted via Grants.

gov: Proposals submitted in response to this program solicitation via Grants. gov should be prepared and submitted in accordance with the NSF Grants. gov Application Guide: A Guide for the Preparation and Submission of NSF Applications via Grants.

gov. The complete text of the NSF Grants. gov Application Guide is available on the Grants. gov website and on the NSF website at: ( https://www.

nsf. gov/publications/pub_summ. jsp?

ods_key=grantsgovguide ). To obtain copies of the Application Guide and Application Forms Package, click on the Apply tab on the Grants. gov site, then click on the Apply Step 1: Download a Grant Application Package and Application Instructions link and enter the funding opportunity number, (the program solicitation number without the NSF prefix) and press the Download Package button.

Paper copies of the Grants. gov Application Guide also may be obtained from the NSF Publications Clearinghouse, telephone (703) 292-7827 or by e-mail from nsfpubs@nsf. gov .

In determining which method to utilize in the electronic preparation and submission of the proposal, please note the following: Collaborative Proposals. All collaborative proposals submitted as separate submissions from multiple organizations must be submitted via the NSF FastLane system. Chapter II, Section D.

5 of the Grant Proposal Guide provides additional information on collaborative proposals. See Chapter II. C.

2 of the GPG for guidance on the required sections of a full research proposal submitted to NSF. Please note that the proposal preparation instructions provided in this program solicitation may deviate from the GPG instructions. The following information SUPPLEMENTS (does not replace) the guidelines provided in the NSF PAPPG and the NSF Grants.

gov Application Guide. Proposal Titles: Proposal titles must begin with "EXP" followed by a colon, and then the title of the proposed project. If you submit a proposal as one in a set of collaborative proposals, "EXP" should be followed by a colon, then "Collaborative Research" followed by a colon, and then the project title.

For example, if you are submitting a collaborative project, the title of each associated proposal would be "EXP: Collaborative Research: Project Title." Project Description: Project Descriptions should include the following: The proposal should clearly state the societal need or opportunity, its importance, along with investigators’ big-picture vision of addressing that need through the proposed project.

The vision should be justified by the relevant theories or learning and technological possibilities on which it is based. The proposal should present an overview of the proposed innovation and its role in the proposed vision, along with the research questions that will be addressed in the context of the proposed innovation and the issues of generalizability and transferability that will be addressed.

Proposals should describe and justify the new or emerging technological genre or type of socio-technical system, describe the representative implementation that will be developed, and justify its appropriateness as a representative of the genre that will be generalizable to other implementations and serve as a venue for answering foundational research questions.

Proposals should make clear the initial proposed design of their innovation; the theories, literature, prior work, and practical issues that inform its design; how it will be integrated into the learning environment; the expected experience of learners and learning outcomes; and the means by which learning is expected to happen.

Up to five extra screen shots or graphics are allowed in supplementary documentation to make the imagined experiences of learners clear to readers; PIs are encouraged to include such screen shots and to refer to these screen shots in the proposal text. The plan for iterative refinement should be described, including the data that will be collected and analyzed in support of formative evaluation.

Proposals should make clear how iterative refinements will be focused, the literature that informs that focus, and the ways the results from formative