"It answers questions that I didn't know I had": Ph.D. Students' Evaluation of an Information Sharing Knowledge Graph (2406.07730v2)

Abstract: Interdisciplinary PhD programs can be challenging as the vital information needed by students may not be readily available, it is scattered across university's websites, while tacit knowledge can be obtained only by interacting with people. Hence, there is a need to develop a knowledge management model to create, query, and maintain a knowledge repository for interdisciplinary students. We propose a knowledge graph containing information on critical categories and their relationships, extracted from multiple sources, essential for interdisciplinary PhD students. This study evaluates the usability of a participatory designed knowledge graph intended to facilitate information exchange and decision-making. The usability findings demonstrate that interaction with this knowledge graph benefits PhD students by notably reducing uncertainty and academic stress, particularly among newcomers. Knowledge graph supported them in decision making, especially when choosing collaborators in an interdisciplinary setting. Key helpful features are related to exploring student faculty networks, milestones tracking, rapid access to aggregated data, and insights into crowdsourced fellow students' activities. The knowledge graph provides a solution to meet the personalized needs of doctoral researchers and has the potential to improve the information discovery and decision-making process substantially. It also includes the tacit knowledge exchange support missing from most current approaches, which is critical for this population and establishing interdisciplinary collaborations. This approach can be applied to other interdisciplinary programs and domains globally.