I-Corps: Translation Potential of a Self-regulated and Learning Engagement Tool

Award ID: 2513503

This I-Corps project focuses on the development of an intelligent, chatbot-based, learning assistant designed to enhance student engagement and self-regulated learning. This technology addresses critical gaps in current digital learning environments by providing students with personalized support, timely reminders, and real-time feedback, fostering better academic performance and retention. By integrating with widely used digital learning management systems, this innovation has the potential to benefit millions of students across diverse educational settings, from K-12 to higher education. Additionally, it offers educators a powerful tool to monitor student progress and provide timely interventions, ultimately improving teaching efficiency. The potential of this project is significant, as educational institutions increasingly seek scalable, data-driven solutions to enhance learning outcomes. By leveraging advanced generative artificial intelligence technologies, this innovation can be adapted for various markets, including online education platforms, corporate training programs, and workforce development initiatives, making it a transformative tool for the future of education. This I-Corps project utilizes experiential learning coupled with a first-hand investigation of the industry ecosystem to assess the translation potential of the technology. This solution is based on the development of a generative, artificial intelligence (AI)-powered chatbot that integrates with digital learning management systems to deliver personalized, contextualized assistance to students. The underlying technology leverages large language models, retrieval-augmented generation, and natural language processing to answer student queries, generate customized reminders, and provide contextualized academic support. These techniques enable real-time information retrieval, intent recognition, and adaptive response generation, enhancing student engagement and instructor insights. The project builds upon research on self-regulated learning theory and gamification, incorporating evidence-based strategies to promote student self-regulation and engagement. Initial field experiments have demonstrated promising results, including increased student engagement, higher assignment completion rates, significantly improved academic performance, and positive testimonials from participating instructors. Through iterative testing and user feedback, this project aims to establish a robust, AI-driven solution for promoting learning engagement and self-regulated learning and expanding access to high-quality, chatbot-based, learning support. 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: Ruth Shuman