National Science Foundation (HCC Award #0917328)

The goal of the proposed project is 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 should provide effective assistance in executing such manual steps. The results from the manual steps should be seamlessly integrated with other steps.

The new PedWorkflow effort will include 1) knowledge-based modeling of noncomputational assessment tools as well as computational tools as workflow components 2) interactive generation of hybrid workflows that address high-level pedagogical assessment goals by propagating and combining constraints from both non-computational and computational steps, and 3) management and interactive execution of hybrid workflows that incorporates new constraints that are inferred from execution of non-computational steps. Evaluations will focus on the effects of PedWorkflow technology on learning assessment performance. We will evaluate tools in the context of two undergraduate engineering courses at USC.

The intellectual merit of the project includes a novel hybrid-workflow framework and the evaluation of technological innovations in student learning assessment, i.e. the assessment of pedagogical discourse. We expect broad impact through the facilitation of assessment workflows. The new workflow technology will empower instructors with large scale complex diagnose and assessment of student learning. We expect increased engagement of instructors (and administrators) in the assessment process and promote continued deep understanding of student learning. The assessment of STEM student learning with respect to gender, ethnicity and other background information will point to directions to improve learning and retention of female, increasing their participation in STEM area. The finding will provide benefits to society by sharing results and technology with instructors and educational experts.