Systematic tool support of engineering education performance management

Abstract

Engineering schools must adopt or develop their own systems and processes for graduate attribute assessment. In this paper, we take a systems engineering approach to graduate attribute assessment and propose a system architecture and tool-supported continuous improvement process with key algorithms and mathematical analysis to process the data and provide performance management reporting. Over several iterations, we have introduced and evaluated improved systems support in a collection of tools called the Graduate Attribute Information Analysis system (GAIA). GAIA integrates course indicators as well as external indicators from a variety of sources. It provides a tool-supported continuous improvement process with templates and notifications for all deliverables. There are sound algorithms and tool support and built-in mathematical analysis for data collection and reporting that includes quantitative and qualitative data; weighted grading; historic trend analysis; improved visualization of results; and standardized reports at both the course level and the program level that can be used either for accreditation or to inform program improvement.