Requirement Volatility Metrics as an Assessment Instrument for Design Team Performance Prediction

John M. Feland III
Department of Engineering Mechanics, HQ USAFA/DFEM, USAF Academy, CO 80840, USA
E-mail: gohogs@cdr.stanford.edu

Larry J. Leifer
Learning Lab, Stanford University
Stanford CA 94309, USA
E-mail: leifer@cdr.stanford.edu

Abstract:
Predicting and assessing student team performance in design projects presents a host of challenges. Most involve turning qualitative interpretations into quantitative assessments. This challenge is simplified when all student teams are working on the same project. Establishing a relative performance metric based on the top and bottom performers simplifies the task. However, in classes where the projects are diverse and/or sponsored by outside industry representatives the challenge is increased. In classes where formalized requirement documentation exists, requirement volatility (change over time) can be used to simplify student team performance assessment, as well as serving as a predictor of future performance on the project. In an analysis based on project requirement documents from the graduate design class at Stanford, ME210, requirement volatility metrics proved to have surprising power as a predictor of student design team performance. Tracked over time, the metric predicted of team rank-order performance. This document will summarize a method for volatility measurement and the results of our initial analysis.

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