Reading 3# : "Those Look Similar!" Issues in Automating Gesture Design Advice

Comments:
Yue Li
Summary:
A user interface design tool, QUILL, was designed to give unsolicited advice (active feedback) to help designers create and improve gestures. The advice was given based on similarity metrics of Rubine.

Interface challenges, implementation challenges and similarity metrics challenges that authors encountered in QUILL were all discussed in the paper.  Long discussed the time of advice, the length and frequency of advice, the content of advice, background analysis, advice for hierarchies and similarity metrics. All his design was in the point of users' view and desired to make users more comfortable.  For example, Quill always gave a concise message with a hyperlink to find more details.

Long also gave the future work of quill, such as collecting more date to improve the similarity model etc.
Discussion:
The paper mainly discussed the design of an automating system. Many challenges that they encountered in the design will also occur in our design. Advice on how to deal with these challenges seems beneficial to designers, especially to novice designers. But I expect more details on some core problems, such as similarity metrics and the analysis about the performance of Rubine's recognizer.

Besides, maybe the system could be better by giving other options of recognizers besides Rubine.  Users can find the best recognizer for their own gesture datasets. It will make quill more popular.