Understanding the Engineering Education Research problem space using Interactive Knowledge Networks

Abstract

For any knowledge intensive undertaking (such as a discipline) it is critical to chart its birth and growth to understand where the discipline stands and what innovative endeavors lead to the creative accomplishments currently witnessed in its knowledge products. In this paper, we describe the research and development of a knowledge platform called Interactive Knowledge Networks for Engineering Education Research (iKNEER). Using a theoretical model that combines ultra large-scale data mining techniques, network mapping algorithms, and time-series analysis of knowledge product evolution, we attempt to characterize and provide insights into the topology of the networks and collaborations within engineering education research. More importantly, our goal is to provide members of the Engineering Education Research (EER) community with tools and infrastructure that allows them to understand the structure and networks of knowledge within the community at any given time. In this paper, we also provide a detailed description of the algorithms, workflows, and the technical architecture we use to make sense of publications, conference proceedings, funding information, and a range of other knowledge products. We plan on announcing its open availability to the EER community. © 2011 American Society for Engineering Education.