Alice Agogino, Shuang Song, and Jonathan Hey
UC Berkeley, Berkeley CA 94720, USA
This paper reports on research conducted on design teams at UC Berkeley over several years at the undergraduate and graduate levels. The paper provides a triangulation of indicators of successful design teams drawn from different research methods. The research sources include questionnaires, team documents, email communication, individual design journals, faculty evaluations, and ratings from external design judges. Computational linguistic algorithms are used to analyze the text documents with a focus on latent semantic analysis and semantic coherence. Sketches are analyzed using a comprehensive list of metrics, including Shah’s `variety’ measure for quantifying the breadth of the solution space explored during the generation process. A synthesis of the results provides interesting and counter intuitive indicators for predicting the success of student design teams. This analysis, in turn, provides insight into learning how the student design teams negotiate and learn the design process and can assist educators in improving the teaching of design.