SBIR Phase II: A Digital Platform That Engages Elementary Aged Girls in STEM Through Personalized Informal Learning

Award ID: 2321914

The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase II project is an increase in the representation of women in Science, Technology, Engineering, and Math (STEM) employment areas, enabling the US to meet the increasing demand for STEM workers and maintain competitiveness in the global innovation community. The factors contributing to the underrepresentation of girls and women in STEM often take effect early in their education and extend beyond traditional classrooms settings. Very few solutions specifically address the support needed by parents to facilitate STEM informal learning in a way that is engaging to their young daughters. This project intends to deliver personalized learning pathways designed to catalyze positive STEM experiences for girls early in their learning journeys so that they are more likely to embrace STEM careers. This project seeks to deliver a learning platform that operates using a novel recommender system, which applies algorithmic modeling of surprise and curiosity as well as best practices regarding the unique STEM learning needs of young girls. The main technical hurdles that will be addressed in this project are as follows: (1) refinement of algorithmic model, which will be applied to generate recommendation sequences that elicit curiosity in manner that both increases interest in STEM and prompts additional STEM learning and career awareness; (2) expansion of a dataset and data representation through the enhanced features and improvements to the data model; (3) visualization and gamification of learner interest inputs and (4) implementation of an engaging user interface and experience. The refinement of algorithmic models is expected to expand the research knowledge on recommendations for behavior change, recommender systems for a young target audience, and surprise and curiosity modeling in artificial intelligence systems. The solution will ultimately deliver a commercial application that personalizes STEM career exploration, particularly suited for young women. 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: Rajesh Mehta