The NSF Innovative Technology Experiences for Students and Teachers (ITEST) is interested in supporting research and development projects to expand upon work with proven success. As stated in the ITEST solicitation (22-585) NSF intends to fund 3 to 5 awards for Scaling, Expanding, and Iterating Innovations (SEI) with durations up to five years and budgets up to $3,500,000. Proposals are due on August 9, 2024.
When planning to scale your work, consider that SEI projects:
- Broaden the implementation and research of an innovation at a significant scale of five to ten times greater than the original implementation.
- Extend an innovation to different student populations, regions of the country, grade levels or ages of students with varying skills, and educators' capacities in PreK-12 formal and informal settings.
- Examine issues of transferability and generalizability and the factors that support or inhibit scaling.
- Assess cognitive and social-emotional student outcomes and measure student STEM knowledge and whether students continue to pursue further STEM and ICT education or careers.
NSF ITEST Office Hours: Scaling Expanding and Iterating (SEI) Project Type
On Tuesday, June 18 and Thursday, June 20, STELAR as we hosted NSF Program Officers for Q&A sessions in support of those developing a Scaling, Expanding, and Iterating Innovations (SEI) project type proposal ahead of the ITEST solicitation (22-585) deadline on August 9, 2024. These sessions were not recorded, but the resources listed below provide detailed information for proposal writers.
Resources
NSF Webinar: Guidance for ITEST SEI Proposals on Scaling Prior Research
In April of 2023, NSF Program Officers Arlene de Strulle and Stephanie Teasley presented the essential components of successful Scaling, Expanding, and Iterating Innovations (SEI) ITEST proposals. Review the slides from this webinar by clicking the box below.
ITEST SEI Concept Worksheet
In advance of the 2024 ITEST solicitation deadline, NSF Program Officers invite those preparing to submit a Scaling, Expanding, and Iterating Innovations (SEI) proposal to complete a concept worksheet to submit for NSF feedback. Worksheets must be received by NSF no later than Friday, June 28.
Recent Video
Videos
Scale-up Experiences, Successes, & Challenges
Below you will find a series of videos from the 2022 ITEST PI Meeting featuring several ITEST Principal Investigators sharing their SEI work at different stages.
Click the fullscreen icon in the video for better viewing
Conceptualizing a Scale-up Proposal | ITEST PI Meeting 2022
NSF Program Office Arlene de Strulle poses questions to guide researchers' proposal conceptualization for an ITEST Scaling, Expanding, and Iterating Innovations (SEI) award.
Defining Scaling for your Project| ITEST PI Meeting 2022
As the resource center for the NSF ITEST Program, STELAR would like to highlight additional tools, resources, and information that are freely available to assist proposal writers.
Collecting Sufficient Data for a Scale Up Award | ITEST PI Meeting 2022
The Drone Research Opportunities for Native Elementary Students (DRONES) project is preparing for a potential scale up by expanding their research practices and understanding how they can scale their work.
Adapting Curriculum and PD to Scale in New Regions | ITEST PI Meeting 2022
With demonstrated growth in student STEM content knowledge, teacher STEM awareness, and teacher self-efficacy teaching integrated STEM, the Teachers and Researchers Advancing Integrated Lessons in STEM (TRAILS) project received an award to scale up their work to reach 10,000 students. In this clip, the presenters relate how they located partners in rural populations, and their approach adapting their curriculum and PD using place-based knowledge.
Determining Sufficient Evidence to Scale| ITEST PI Meeting 2022
The Youth Astronomy Network (YouthAstroNet) project shares how they knew they had sufficient evidence to apply for a Scaling, Expanding, and Iterating Innovations (SEI) award. They identified 34 different instructional experiences the students might have had ran a regression model and factor analysis to better understand which of these interventions mattered for learning, interest, and identity gains.