A method to evaluate properness of GUI design based on complexity indexes of size, local density, aliment, and grouping

Tetsuya Miyoshi; Atsuo Murata

A method to evaluate properness of GUI design based on complexity indexes of size, local density, aliment, and grouping

Research output: Contribution to journal › Conference article › peer-review

Abstract

This paper presents a numerical tool for evaluating the usability of a screen design based on its complexity measures. An objective performance (search time) and a subjective evaluation (opinion of the ease of search) were analyzed as a function of the complexity of the screen. In developing the tool, we defined four measures of complexity: size, local density, aliment, and grouping factors. Multiple regression analysis was used to model the relationship between the modified measures of complexity and search time. A subjective evaluation of the screen layout with respect to its ease of search was performed using the pairwise comparison technique. The results of the subjective evaluation are discussed in comparison with the numerical results of the multiple regression model.

Original language	English
Pages (from-to)	221-226
Number of pages	6
Journal	Proceedings of the IEEE International Conference on Systems, Man and Cybernetics
Volume	1
Publication status	Published - Dec 1 2001
Externally published	Yes
Event	2001 IEEE International Conference on Systems, Man and Cybernetics - Tucson, AZ, United States Duration: Oct 7 2001 → Oct 10 2001

Keywords

Complexity of screen
Evaluation of screen
GUI
Regression model
Usability of software

ASJC Scopus subject areas

Control and Systems Engineering
Hardware and Architecture

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title = "A method to evaluate properness of GUI design based on complexity indexes of size, local density, aliment, and grouping",

abstract = "This paper presents a numerical tool for evaluating the usability of a screen design based on its complexity measures. An objective performance (search time) and a subjective evaluation (opinion of the ease of search) were analyzed as a function of the complexity of the screen. In developing the tool, we defined four measures of complexity: size, local density, aliment, and grouping factors. Multiple regression analysis was used to model the relationship between the modified measures of complexity and search time. A subjective evaluation of the screen layout with respect to its ease of search was performed using the pairwise comparison technique. The results of the subjective evaluation are discussed in comparison with the numerical results of the multiple regression model.",

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N2 - This paper presents a numerical tool for evaluating the usability of a screen design based on its complexity measures. An objective performance (search time) and a subjective evaluation (opinion of the ease of search) were analyzed as a function of the complexity of the screen. In developing the tool, we defined four measures of complexity: size, local density, aliment, and grouping factors. Multiple regression analysis was used to model the relationship between the modified measures of complexity and search time. A subjective evaluation of the screen layout with respect to its ease of search was performed using the pairwise comparison technique. The results of the subjective evaluation are discussed in comparison with the numerical results of the multiple regression model.

AB - This paper presents a numerical tool for evaluating the usability of a screen design based on its complexity measures. An objective performance (search time) and a subjective evaluation (opinion of the ease of search) were analyzed as a function of the complexity of the screen. In developing the tool, we defined four measures of complexity: size, local density, aliment, and grouping factors. Multiple regression analysis was used to model the relationship between the modified measures of complexity and search time. A subjective evaluation of the screen layout with respect to its ease of search was performed using the pairwise comparison technique. The results of the subjective evaluation are discussed in comparison with the numerical results of the multiple regression model.

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KW - Regression model

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