SBIR Phase I: A K12 Goal-Setting And Reflection Platform That Builds Student Learning Skills And Mindset

This SBIR Phase I project will develop an Artificial Intelligence (AI) /Machine Learning (ML) driven solution to automate the process of giving qualitative feedback on student reflections. The automated reading of student reflections for quality and content is a new and innovative technology that is currently not available in the market, as all applications in this realm focus on grammar and writing structures. The innovation will understand the specific actions and strategies students are using (many of which are unique to an individual learner), and help students get the support they need to improve in those techniques or try new ones. This process would build learning skills and growth-oriented belief systems in students, both of which lead to significantly improved academic and career outcomes. Fundamentally, the proposed project will help students learn how to learn. This SBIR Phase I project will build the first phase of personalized insights for impactful student goal-setting and reflection. The company will leverage natural language processing (NLP) and ML algorithms to 1) parse, process, and analyze reflections written by students, 2) return a score for each reflection based on a research-based rubric, and 3) notify teachers when a student has a low score and needs support. At the end of Phase I, the company will examine whether the prototype functions as intended with 90%+ accuracy, if teachers can integrate the prototype into their classroom practice, and if it shows early promise of improving the quality of student reflections and learning. With a proprietary dataset of 400K+ written student reflections and data points, the company is uniquely positioned to develop and scale this product vision. Phase II research will develop personalized feedback, strategies and suggestions to help students and teachers find the best strategies faster. 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.