The goal of this project was to create a novel workflow environment that supports efficient assessment of student learning through interactive generation and execution of various assessment workflows. Unlike most of the existing workflow systems, some types of assessment involve steps that cannot be fully automated, such as obtaining student registry information, e.g. student gender, and using questionnaires to acquire student motivation levels. The system provided effective assistance in executing such manual steps. The results from the manual steps should be seamlessly integrated with other steps.
Funding Agency: National Science Foundation
Investigators: Jihie Kim, Gisele Ragusa, and Erin Shaw, University of Southern California