Innovation and success in today’s competitive world are largely driven by knowledge and intellectual capital. Academic communities are uniquely situated to utilize their expansive knowledge bases to drive new thinking and progress within their problem spaces. Yet, the distributed nature of research and increasing virtual collaborations among researchers pose unique challenges to understanding communities as social systems. The problem of understanding the state of knowledge within a problem space is compounded by the lack of techniques and tools for organizing and characterizing the significant amount of data being produced within the problem space at any given time.

In this talk, we demonstrate new techniques and tools developed as part of the Interactive Knowledge Network for Engineering Education (iKNEER) project that tap into a community’s knowledge and network resources. We attempt to understand the current state of institutional knowledge within the engineering education problem space. Using a combination of data mining, social network analysis, and interactive visualization algorithms, we demonstrate the dynamic and evolving nature of knowledge networks within engineering education research. We also show how new methods of data mining and visualization developed as part of this effort allow users to interactively mine vast amounts of knowledge and interact with the underlying data intuitively. This project is a collaboration between researchers at Purdue University and Virginia Tech and is supported through National Science Foundation grants EEC-0957015, EEC-0935109, and EEC‑0935124.

Dr. Krishna Madhavan is an Assistant Professor in the School of Engineering Education at Purdue University. Prior to his arrival at Purdue, he was an Assistant Professor with a joint appointment in the School of Computing and the Department of Engineering and Science Education at Clemson University. Dr. Madhavan also served as a Research Scientist at the Rosen Center for Advanced Computing, Information Technology at Purdue University, where he led the education and the educational technology effort for the NSF-funded Network for Computational Nanotechnology (NCN). He was the Chair of the IEEE/ACM Supercomputing Education Program 2006 and was the curriculum director for the Supercomputing Education Program 2005. In January 2008, he was awarded the NSF CAREER award for work on transforming engineering education through learner-centric, adaptive cyber-tools and cyber-environments. He was one of 49 faculty members selected as the nation’s top engineering educators and researchers by the US National Academy of Engineering to the Frontiers in Engineering Education symposium.