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"SBIR Phase I: Education and Training for an AI Integrated Future: Mixed-Reality, Competency Based Learning" is currently closed and not accepting applications.
SBIR Phase I: Education and Training for an AI Integrated Future: Mixed-Reality, Competency Based Learning is sponsored by National Science Foundation (NSF). This Small Business Innovation Research (SBIR) Phase I project supports the development of an adaptive learning platform to accelerate the acquisition of essential competencies in AI literacy, data science, healthcare technical roles, and vocational skills through immersive, evidence-based learning experiences.
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SBIR Phase I: Education and Training for an AI Integrated Future: Mixed-Reality, Competency Based Learning - National Science Foundation SBIR Phase I: Education and Training for an AI Integrated Future: Mixed-Reality, Competency Based Learning DeFalco, Jeanine A (Former PI) The broader/commercial impact of this SBIR Phase I project leverages adaptive and personalized mixed-reality training solutions to address the critical challenge of workforce displacement due to artificial intelligence (AI).
AI and automation technologies will displace between 400 million and 800 million individuals globally by 2030, requiring up to 375 million workers to switch occupational categories and learn new skills. An adaptive learning platform will democratize access to high-quality, personalized training experiences, serving displaced workers, older persons, economically disadvantaged youth, and vocational learners.
The platform accelerates the acquisition of essential competencies in AI literacy, data science, healthcare technical roles, and vocational skills through immersive, evidence-based learning experiences. This technology bridges the growing skills gap by validating existing competencies while developing new ones, enabling faster workforce transitions and creating new pathways to employment in an AI-integrated economy.
This Small Business Innovation Research (SBIR) Phase I project develops a novel adaptive learning platform through three core technological innovations: a skills engine, an authoring tool, and an extended reality (XR) player. The skills engine uses Generative AI and RAG to identify and map key competencies, creating personalized learning pathways based on individual skill profiles.
The authoring tool transforms the creation of adaptive learning content through AI-assisted scenario generation, automated asset creation, and integrated assessment tools, reducing development time and costs while maintaining high educational standards. The XR player delivers these experiences through augmented and virtual reality, adapting in real-time to learner performance and capturing analytics for competency validation.
The platform architecture integrates these components seamlessly while maintaining compliance with IEEE standards and RAMP certification requirements, establishing new benchmark for evidence-based, adaptive learning in mixed reality environments. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
NSF Program Director: Lindsay Portnoy Status Closed Effective start/end date 01/01/25 → 12/31/25 MIXTA RE, INC: $304,200. 00 (SBIR/STTR) America's Seed Fund Artificial Intelligence (excluding ML) Immersive Technology and edge devices Machine Learning Training Data Congressional District at Award District n. 03 of Connecticut Current Congressional District District n.
03 of Connecticut Core Based Statistical Area (CBSA) County: South Central Connecticut, CT https://www. nsf. gov/awardsearch/showAward?
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According to the current listing, eligibility includes: Small businesses, particularly those developing innovative technologies with commercial and/or societal impact and a level of technical risk. Participation is encouraged from all Americans and first-time entrepreneurs. Confirm the full requirements in the official notice before applying.
The current listing shows up to $275,000 (Phase I). Verify award ceilings, matching requirements, and allowable costs in the official notice.
The most recent published deadline was December 31, 2025, which has passed. This is an annual program, so a new cycle should follow. Check the funder's website for the next application window.
SBIR Phase I: Education and Training for an AI Integrated Future: Mixed-Reality, Competency Based Learning is funded by National Science Foundation (NSF). Verify program details on the funder's official page before applying.
Yes — this listing is flagged as national in scope, so applicants across the U.S. may apply, subject to the sponsor's other eligibility criteria.
Start from the official opportunity page linked in this listing — it carries the sponsor's submission instructions.
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