A Study in Engaging Students with Complex Topics through Knowledge Graphs

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This project aims to serve the national interest by improving sustainability science instruction and learning at a general education level for undergraduate students. Educating future generations about sustainability science is a critical problem for humanity’s collective future. Recognizing the importance of this topic, many colleges and universities have established or are developing general education courses on sustainability science that every student must take. This project will improve undergraduate STEM education by developing and studying the effectiveness of educational modules that engage students from many different majors with sustainability science and helping them grapple with the complexity of the topic. It is based on the key observation that knowledge graphs, an emerging means of storing information computationally, provide a potential way to span across disciplines and unpack complexity one layer at a time. They allow students to engage with problems that more accurately represent the challenges of sustainability science than traditional techniques. The contributions of the project include: (1) a new knowledge graph-based approach to supporting student learning of concepts in sustainability science that addresses a critical shortcoming in the sustainability education landscape; (2) assessments of this approach in terms of engagement and efficacy at helping students learn key concepts in sustainability; and (3) a publicly available computational scaffolding for this technique.The central goal of the project is to assess three core research questions: (1) Can knowledge graph-based educational modules help students improve their understanding of sustainability concepts within and across fields? (2) Can student contributions to a shared knowledge graph form a useful foundation for later pedagogical activities? (3) Can students contribute accurate and relevant sustainability information to a global, public knowledge graph through their coursework? The team will investigate these questions by developing a novel computational platform for education and deploying it with more than 2,000 students across two universities. The platform developed as part of this grant will enable students to make their own knowledge graphs based on course content and integrate their graphs with those of their peers, as well as complete further activities based on revising the collective graph. Assessment will involve both quantitative and qualitative evaluations of the course modules and their effect on student learning, as well as computational analyses of the collectively-constructed graph. The NSF IUSE: EHR Program supports research and development projects to improve the effectiveness of STEM education for all students. Through the Engaged Student Learning track, the program supports the creation, exploration, and implementation of promising practices and tools.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.