(1)

In June 2008, the National Academy of Engineering (NAE) identified advancing personalized learning as one of the grand challenges for engineering. Further, the NAE identified initial work in web-based intelligent, recommender systems that use advanced computational algorithms such as genetic algorithm (GA) as a potential approach to addressing personalized learning. Despite algorithmic advances in intelligent tutoring and recommender systems, current web-based cyber- environments used for engineering research and learning are largely content-centric and agnostic to individual learner characteristics. In this talk, we focus on the dual role of cyberinfrastructure in developing viable approaches to tackling the problem of personalized learning.

In its first role, cyberinfrastructure acts as a platform for delivering learning content. This is commonly referred to as cyberlearning or cyber-enabled learning. In this problem space, our work focuses on the problem of building cyberlearning environments such that they are learner-centric and adaptive (a key pre-requisite for personalizing learning). A qualitative analysis of engineering education literature drawn from several leading journals spanning the past 10 years (over 500 papers) shows a clear lack of a major theoretical framework that includes cyberinfrastructure (or more generally technology) at its core. A significant part of the problem is the absence of a model of technology adoption and use among undergraduate engineering students. Based on a pilot survey of 509 undergraduate engineering students (384 male and 125 female students), we show the beginnings of a base model of technology adoption and use among engineering students. Using tenets of semantic grid theory, we show how this base model can be translated into learner- centric, personalized cyber-environment design.

In the second role, cyberinfrastructure has the great potential to act as a platform for expediting the transition from research data to pedagogical practice. This is done essentially through the development of a virtual organization for engineering education research. In this talk, we define the characteristics of a virtual organization and highlight some of the methodological challenges in developing a virtual organization for engineering education research. Further, we outline the initial stages of a multi-university effort to address these challenges. We also provide empirical evidence that makes a case for a virtual organization that focuses on engineering education research.

Krishna P.C. Madhavan is an Assistant Professor at Clemson University with a joint appointment in the Department of Engineering and Science Education and the School of Computing. Before his appointment at Clemson, he served as a Research Scientist in the Science Gateways Group 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). Dr. Madhavan 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 for work on transforming engineering education through learner-centric, adaptive cyber-tools and cyber-environments.

(1) This work is supported by National Science Foundation CAREER Award EEC-0747795.