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Iterative methodology and designer training in human-computer interface design

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Published:01 May 1993Publication History

ABSTRACT

One of the most promising methods for user interface design is the iterative design methodology. To this point only case study support for this method has been given. There are still many unanswered questions about the effectiveness of this method.

One difficulty encountered in user interface design is knowing what set of knowledge and skill the designer must possess to ensure good user interface design. Many different people have designed user interfaces for computer systems. These people came from a variety of backgrounds and viewpoints. Two of the most common groups involved in user interface design are human factors specialists and programmers.

This study investigates these two issues. One factor in this study is the iterative design methodology. An empirical evaluation of this method was conducted. The strengths and weaknesses of this method are discussed. A second factor in this study is a comparison of human factors specialists and programmers in an actual user interface design task.

The results of this study indicate that iterative design methodology can improve the usability of a product. The amount of the improvement may be constrained by the original design. This study also supports the use of human factors specialists in user interface design. A significant difference between designs produced by human factors specialists and programmers was found.

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        • Published in

          cover image ACM Conferences
          CHI '93: Proceedings of the INTERACT '93 and CHI '93 Conference on Human Factors in Computing Systems
          May 1993
          547 pages
          ISBN:0897915755
          DOI:10.1145/169059
          • Chairmen:
          • Bert Arnold,
          • Gerrit van der Veer,
          • Ted White

          Copyright © 1993 ACM

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          Publication History

          • Published: 1 May 1993

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          CHI '93 Paper Acceptance Rate62of330submissions,19%Overall Acceptance Rate6,199of26,314submissions,24%

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