SUMMARY

The field of engineering design is constantly growing and new research is expanding into the design process. The current standard for testing advances in engineering design is to present participants with a design problem and evaluate their performance across ideation metrics. This methodology, however, suffers in repeated measures testing, as a design problem cannot be given repeatedly to a participant without biasing results. Currently, using different design problems yields varying results and therefore cannot be used to compare a common group. This study investigates four design problems, updated by the author, peanut, corn, alarm, and coconut, for equivalency using between-subjects and within-subjects testing. All design problems were given during between-subjects testing, while resources limited the within-subjects testing to the peanut and corn problems. The within-subjects analysis revealed correlations on three of five metrics tested. This indicates that the problems used are close to equivalent with further research needed to close the gap. Additionally, the between-subjects analysis revealed that the design problems do not show group mean equivalency. These results, paired with the within-subjects results, suggest that between-subjects analysis is insufficient in assessing equivalency and within-subjects analysis should be used in future studies of design problem equivalency. Three problem characteristics were also investigated in the between-subjects analysis for their impact on metric scores. While trends emerged, such as higher difficulty leads to fewer and lower quality solutions, more research needs to be done to understand how manipulating these problem characteristics and couplings of characteristics can be used to make equivalent design problems.