Gestalt Prototyping Framework - Evaluation Tool

• Autores: Ripalda, Daniel; Guevara, César; Garrido, Alejandra
• Año de publicación: 2021
• Idioma: inglés
• Tipo de recurso: documento de conferencia
• Materia: Ciencias de la Computación; Gestalt; User Interfaces; Usability; Mobile; Agile Software Development
• Institución: Comisión de Investigaciones Científicas de la Provincia de Buenos Aires

The Gestalt Prototyping Framework linked the Nielsen Usability Heuristics to the principles of human perception and presents some parameters that can be used in developing high and low-fidelity prototypes for mobile application interfaces. The link between the fundamentals of usability and Gestalt principles focuses on the graphical components of the interfaces and the functions that they fulfill in the development of different functional actions. Previous articles have presented promising experimental results in reducing trial-error regressions in the interface design process and improving interface redesign processes; There have been positive results in parameters such as learnability, ease of use, perception of simplicity, and user preference. Within this same line of research, the present work describes the development process of an application that summarizes the fundamental aspects of the Gestalt prototyping framework in an evaluative model, which helps application designers, software engineers, and usability experts, to assess the prototypes of the interfaces and the incidence of the different graphic components in usability interactions. The tool is based on the most widely used usability parameters and is structured based on the responses that the development team fills in an automated LIKERT assessment. The results are processed based on an algorithm that simulates and predicts the results that could be obtained in high-fidelity prototype tests. This application issues specific recommendations on the visual components of the interfaces, to obtain better results in the production of high and low-fidelity prototypes.
Publicada en: Russo D., Ahram T., Karwowski W., Di Bucchianico G., Taiar R. (eds) Intelligent Human Systems Integration 2021. IHSI 2021. Advances in Intelligent Systems and Computing, vol 1322. Springer, Cham. https://doi.org/10.1007/978-3-030-68017-6_111