I-Corps: Translation Potential of Using Generative Artificial Intelligence (AI) and Data Analytics to Enhance STEM Course Success through Data-driven Dashboards

The broader impact of this I-Corps project is the development of a software platform to broaden participation in science, technology, engineering, and math (STEM) and increase the number of STEM professionals. Currently, as the demand for STEM professionals continues to grow, there is a focus on STEM education models that promote equity and broaden the participation of underrepresented groups in STEM. The implementation of these initiatives often faces significant challenges due to limited resources. This technology aims to support programs that improve student success in STEM courses by automating workflows and providing data analytics with the goal of streamlining processes for students, faculty, and administrators. In addition, the platform may offer a solution for building and sustaining STEM programs and enhancing student outcomes, particularly for minority-serving institutions, leading to more efficient and effective teaching and learning practices and support for students completing their STEM degrees. Overall, this technology may contribute to the development of a diverse and skilled STEM workforce. This I-Corps project utilizes experiential learning coupled with a first-hand investigation of the industry ecosystem to assess the translation potential of a software as a service (SaaS) platform that integrates evidence-based pedagogical STEM education models with artificial intelligence (AI) tools. The platform facilitates data analysis and workflow automation to expand student access to STEM opportunities. The technology is based on a STEM pedagogical model focused on learning environments rich in social interactions, which have been shown to improve student retention and success in STEM courses. Prior research across institutions has shown that peer support is associated with increased course pass rates, specific practices associated with students’ disciplinary identity (a predictor of persistence), and metacognitive awareness (a predictor of course performance). The platform is designed to support faculty-student interactions through AI-driven tools for content knowledge and pedagogical practice. By leveraging these technologies, the goal is to develop a scalable solution that can be broadly adopted to foster inclusive and effective STEM learning environments. In addition, this project may advance the understanding of how technology can contribute to developing a diverse STEM workforce by democratizing access to quality STEM education. 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.