Prototyping is an important component of user interface development, during which key decisions are made regarding methods of information presentation and the organization of user interaction. Assessing inclusivity at this stage makes it possible to account for relevant factors before the final implementation of the interface and to adjust design decisions accordingly. The goal of the study is to develop a model for fuzzy multi-criteria assessment of the user interface inclusivity at the prototyping stage, taking into account the relative importance of factors and the preference degree of alternatives. The relative priority of factors is established by the pairwise comparison method using the Saaty scale. To demonstrate the application of the model, three different options for the interface solution at the prototyping stage are considered. For their comparison, fuzzy preference relations are formed for each factor, their intersection and weighted convolution are performed. Sets of non-dominated alternatives and the resulting membership function are determined. A structural-functional model and pseudocode of the assessment algorithm are developed. The proposed approach makes it possible to quantitatively compare prototypes based on a set of inclusivity factors and determine the optimal interface solution.

Prototyping is an important component of user interface development, during which key decisions are made regarding methods of information presentation and the organization of user interaction. Assessing inclusivity at this stage makes it possible to account for relevant factors before the final implementation of the interface and to adjust design decisions accordingly. The goal of this study is to develop a model for fuzzy multi-criteria assessment of user interface inclusivity at the prototyping stage, taking into account the relative importance of the criteria and the preference degree of alternatives. The relative priorities of the criteria are established by the pairwise comparison method using the Saaty scale. To demonstrate the application of the model, three alternative interface prototypes are considered. For their comparison, fuzzy preference relations are formed for each criterion, and their intersections and weighted convolutions are performed. Sets of non-dominated alternatives and the resulting membership function are determined. A structural–functional model and pseudocode of the assessment algorithm are developed. The proposed approach makes it possible to quantitatively compare prototypes based on a set of inclusivity factors and determine the optimal interface solution.