Sketch Model Review Results and Review
To view the ideas presented by a team section and to provide feedback, click on the links below. Each idea will be reviewed in detail by at least 4 different course staff members.
If you missed the presentations please be sure to watch the presentation videos linked above. If you were not able to make class on Friday it may be worth looking at the class notes (.pdf) for overall feedback on the presentations.
A 5 tier rank order based on the ideas, models, research and presentation effectiveness is below. The rank order is based on the input of 25 course staff members and mentors. The error bars represent the standard deviation of the mean.
The purpose of ranking is to provide overall feedback that can be used to improve our projects— we want to use the review as a learning opportunity. These results reflect the three minute impression of people not familiar with your projects. While you might not agree with a ranking the results capture the impression of the audience. It is worth looking at the higher ranked projects and thinking about what lead to the positive impressions. If your project has a lower ranking, it may mean the idea was not clearly presented, there were gaps in research, or that there were either concerns or misunderstandings about the idea.
The ranking is not used for the sketch model grade, which is determined by your lab instructor. Also, because there are many presentation factors that can lead to a higher or lower overall ranking—not just the merits of the concept alone—do not use this as a score-card for deciding which ideas should be continued.
If you find that the ranking information is driving your decision process, please stop, step back and think about all factors that can influence how things were ranked, and then make a decision for what you understand to be the best product opportunity.
Overall impression of course instructors and mentors, rank ordering (1
is highest). The opportunity ranking is based on the reviewer's perception of needs and potential for a product. Model learning is based on reviewer's perception of how information derived from the models might inform product decisions. Model execution refers to the quality of the sketch model's implementation.