Computação na Escola

Advances in mobile applications providing image classification enabled by Deep Learning require innovative User Experience solutions in order to assure their adequate use by users. To aid the design process, usability heuristics are typically customized for a specific kind of application. Therefore, based on a literature review and analyzing existing mobile applications with image classification, we propose an initial set of AIX heuristics for Deep Learning powered mobile applications with image classification decomposed into a checklist. These results of this research can be used to guide the design of the interfaces of such applications as well as support the conduction of heuristic evaluations supporting the development of image classification apps that people can understand, trust, and can engage with effectively.

Online Course
In order to facilitate the usage of the checklist we also developed an online course presenting the concepts and heuristics available online for free in Brazilian Portuguese.

Online tool
In to facilitate evaluations using the proposed heuristics and checklist, we also developed a web tool that guides the evaluation by presenting each item of the checklist by its name, brief explanation, image with example and its corresponding response alternatives. In the end, the tool summarizes the results by presenting a list of the checklist items and visually indicating the items that are not satisfied, as well as general percentage of the items that are satisfied. The report can also be downloaded in pdf format. The tool has been developed in javascript and is available online for free in English and Brazilian Portuguese.

More information

C. Gresse von Wangenheim, G. Dirschschnabel. UX Heuristics and Checklist for Deep Learning powered Mobile Applications with Image Classification. arXiv:2307.05513 [cs.HC], 2023.

G. Dirschnabel. Desenvolvimento de um checklist de avaliação de heurísticas de experiência de usuário de aplicativos com Inteligência Artificial. 2023. Trabalho de Conclusão de Curso. (Graduação em Ciência da Computação) – Universidade Federal de Santa Catarina.

App desenvolvido pela equipe da iniciativa  como caso exemplo de desenvolvimento de apps com Inteligência Artificial para classificação de imagens ganha menção honrosa no App of the Season Appathon organizado pela App Inventor Foundation/EUA.

App developed by the team of the initiative Computação na Escola/INCoD/INE/UFSC as an example of developing apps with Artificial Intelligence for image classification wins honorable mention in the App of the Season Appathon organized by the App Inventor Foundation/USA.
The app was developed in cooperation with LTH/UFSC and CRLAB/LACEN/SC.

Mais informações