Human-Computer Interaction: Ergonomics and User Interfaces - Vol. 1

By Hans-Jörg Bullinger; Jürgen Ziegler | Go to book overview
Top level category Proportion redundant
sub categories
Average similarity to
other labels.
Business & Finance .00 4.35
Computers & Internet .14 4.12
Entertainment & Media .20 4.30
Health & Fitness .00 4.35
Home & Family .80 4.75
Interests & Lifestyles .89 5.15
People & Communities .83 4.25
News & Information .80 5.08
Reference & Education .60 4.25
Sports & Recreation .20 4.45
Travel & Leisure .33 4.57

Table 3. Redundancy and similarity scores for each top-level category.

4
Discussion

The major conclusion that can be drawn from this study is that tracking traversal patterns through a browse hierarchy is a useful and insightful way to monitor user experience. This study has shown that traversal data contained valuable information about usability problems in one browse hierarchy. More importantly, analysis of the traversal data revealed the source of confusion, and permitted diagnosis of why it occurred. Specifically, the users in this study experienced a significant amount of confusion in using a browse hierarchy. The source of confusion was pin pointed to two major categories by mapping the data into a network representation that makes inter relations among categories explicit. Finally, the patterns observed in the network representation were validated against measures of learnable category structures. This demonstrated that those patterns were indeed rooted in users' psychological experience of the browse hierarchy and provided both an explanation for why confusion was occurring where it did and what to do to alleviate it.

The next step is to generalize the methods and approach used in this small scale study to data from large numbers of people carrying out their own information retrieval tasks in real world settings. Tools for automatically collecting and analyzing such data will need to be developed to make such work tractable. However, the opportunity to continually monitor user experience in a dynamic and changing software environment is likely to be worth the effort.


5
References

Chen, C. ( 1997). "Structuring and visualizing the WWW by generalized similarity analysis". In Proceedings of the 8th ACM Conference on Hypertext, ( Southampton, U.K., April). pp. 177-186.

Chi, M. T.K. & Koeske, R. D. ( 1983). "Network representation of a child's dinosaur knowledge". Developmental Psychology, 19, 29-39.

Markman, E. M. ( 1980). "Developmental differences in the acquisition of basic and superordinate categories." Child Development, 51, 708-719.

Rosch, E. H. ( 1975). "Cognitive representations of semantic categories". Journal of Experimental Psychology: General, 104, 192-233.

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